Sunzida Siddique | Physical Models with AI | Best Researcher Award

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Ms. Sunzida Siddique | Physical Models with AI | Best Researcher Award

Student at Daffodil International University, Bangladesh

Ms. Sunzida Siddique is a skilled software engineer and researcher with a strong academic foundation in Computer Science. She holds a Master of Science in Computer Science from Jahangirnagar University and a Bachelor of Science in Computer Science & Engineering from Daffodil International University. Currently working as a Jr. Software Engineer at Silicon Orchard Ltd., she specializes in AI, machine learning, deep learning, and cybersecurity. Ms. Siddique has contributed to several impactful projects, including Bengali speech-based gender classification and machine learning-based book reading level prediction. Her leadership experience includes roles as an organizer and research instructor in various tech-related clubs. With expertise in programming, web development, and advanced computational techniques, she is committed to advancing research and technology.

 

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Education

Ms. Sunzida Siddique has an impressive academic background, which reflects her dedication and aptitude in the field of Computer Science and Engineering. She holds a Master of Science (M.Sc.) in Computer Science from Jahangirnagar University, where she graduated with a remarkable CGPA of 3.83. Her academic journey also includes a Bachelor of Science (B.Sc.) in Computer Science & Engineering from Daffodil International University, where she achieved a strong CGPA of 3.70. Prior to her university education, Ms. Siddique completed her Higher Secondary Certificate from Narsingdi Model College in 2015, securing a perfect 5.00 in the Science group. She also earned a Secondary School Certificate from Brahmondi Girl’s High School in 2013, where she similarly excelled with a perfect score of 5.00. Ms. Siddique’s consistent academic excellence throughout her educational journey highlights her commitment to mastering her field and her readiness to contribute to cutting-edge research and technological advancements.

Experience

Ms. Sunzida Siddique has gained valuable professional experience in both technical and administrative roles. Since February 2023, she has been working as a Jr. Software Engineer at Silicon Orchard Ltd., where she applies her skills in AI, machine learning, deep learning, cybersecurity, and generative AI to solve complex analytical problems. Her work focuses on leveraging cutting-edge technologies to address challenges in various domains. Prior to this, Ms. Siddique served as an Office Executive at Future Cloud Bangladesh Ltd. from April 2021 to January 2023, where she handled customer service, administrative duties, and maintained effective communication through email and phone. This role honed her multitasking and communication skills while allowing her to gain valuable experience in organizational operations. Her professional journey reflects a strong

Research Interests

Ms. Sunzida Siddique’s research interests lie at the intersection of Artificial Intelligence (AI), Machine Learning, Deep Learning, and Cybersecurity. She is particularly focused on exploring innovative solutions through AI-driven techniques, such as natural language processing and computer vision, to address real-world challenges. Her work includes projects like Bengali Continuous Speech Voice-Based Gender Classification and Machine Learning-based Book Reading Level Prediction, where she applies machine learning algorithms to enhance language processing and educational tools. Additionally, Ms. Siddique is interested in the integration of Physics Guided Neural Networks and Knowledge Graphs to solve complex scientific problems. Her passion for advancing Generative AI and Cybersecurity further drives her research, as she aims to create secure, efficient, and intelligent systems that can transform industries and improve everyday life.

Skills

Ms. Sunzida Siddique possesses a diverse skill set that combines technical proficiency with strong interpersonal capabilities. She is well-versed in programming languages such as C, Java, and Python, with a particular focus on AI and Machine Learning applications. Her expertise extends to utilizing frameworks and libraries to develop solutions in deep learning and cybersecurity. In addition to her programming skills, Ms. Siddique is proficient in web development technologies, including HTML5, CSS3, Bootstrap5, and JavaScript. She is also adept at using tools like Microsoft Word, Excel, and PowerPoint, which support her in documentation, data analysis, and presentation tasks. Her multitasking abilities, coupled with strong communication and leadership skills, enable her to collaborate effectively and manage projects efficiently. These skills, along with her commitment to continuous learning, position Ms. Siddique as a highly capable and adaptable professional.

 

Publication Top Noted

Title: Survey on machine learning biases and mitigation techniques

  • Authors: S Siddique, MA Haque, R George, KD Gupta, D Gupta, MJH Faruk
  • Journal: Digital
  • Volume: 4
  • Issue: 1
  • Pages: 1-68
  • Cited by: 9
  • Year: 2023

Title: Machine learning-based model for predicting stress level in online education due to coronavirus pandemic: a case study of Bangladeshi students

  • Authors: S Siddique, S Baidya, MS Rahman
  • Conference: 2021 5th International Conference on Electrical Information and Communication Technology (EICT)
  • Cited by: 8
  • Year: 2021

Title: Cyber Security issues in the industrial applications of digital twins

  • Authors: S Siddique, MA Haque, RH Rifat, R George, K Shujaee, KD Gupta
  • Conference: 2023 IEEE Symposium Series on Computational Intelligence (SSCI)
  • Pages: 873-878
  • Cited by: 4
  • Year: 2023

Title: Challenges and opportunities of computational intelligence in industrial control system (ICS)

  • Authors: S Siddique, MA Haque, RH Rifat, LR Das, S Talukder, SB Alam, KD Gupta
  • Conference: 2023 IEEE Symposium Series on Computational Intelligence (SSCI)
  • Pages: 1158-1163
  • Cited by: 2
  • Year: 2023

Title: Deep Learning Modeling for Gourd Species Recognition Using VGG-16

  • Authors: MM Hasan, K Alam, S Siddique, TA Topu, MT Habib, MS Uddin
  • Book: Computer Vision and Machine Learning in Agriculture, Volume 3
  • Pages: 19-35
  • Cited by: 2
  • Year: 2023

Title: Computer Vision and Machine Learning in Agriculture, Volume 3

  • Authors: JC Bansal, MS Uddin
  • Publisher: Springer Verlag, Singapore
  • Cited by: 2
  • Year: 2023

Title: People Thoughts Prediction using Machine Learning on Women’s Contribution in ICT in Bangladesh

  • Authors: S Akter, S Siddique, I Jahan, T Rabeya, MR Mim
  • Conference: 2021 IEEE 6th International Conference on Computing, Communication and Networking Technologies (ICCCNT)
  • Cited by: 1
  • Year: 2021

Conclusion

Ms. Sunzida Siddique’s strong academic foundation, her contribution to innovative research projects, and her leadership in organizing and mentoring within technical clubs make her an exceptional candidate for the Research for Best Researcher Award. Her work in AI, machine learning, and other emerging technologies, combined with her enthusiasm for continuous learning, underscores her potential to make significant strides in her field.

Wanchang Zhang | Malware Analysis | Best Researcher Award

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Prof.Dr. Wanchang Zhang | Malware Analysis | Best Researcher Award

Earth System Science at Aerospace Information Research Institute/Chinese Academy of Sciences, China

Prof. Dr. Wanchang Zhang is a distinguished expert in Earth System Science, specializing in remote sensing and GIS applications for ecology, hydrology, water resources, climate change, and disaster mitigation. He is a Professor and Ph.D. Supervisor at the Aerospace Information Research Institute, Chinese Academy of Sciences (CAS), and an awardee of the prestigious “Hundred Talents Program.” With over 400 academic publications, including 270 indexed in SCI/EI, and numerous highly cited works, Dr. Zhang’s research has achieved global recognition. He has developed advanced hydrological and environmental simulation systems and holds 10 national invention patents and 14 software copyrights. Dr. Zhang also serves as Vice Director of the CAS-TWAS Center of Excellence on Space Technology for Disaster Mitigation, showcasing his leadership in addressing critical global challenges.

 

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Education

Prof. Dr. Wanchang Zhang holds a Ph.D. in Earth System Science, reflecting his deep expertise in understanding and addressing complex interactions within natural and human systems. His educational foundation has been instrumental in his significant contributions to fields such as remote sensing, hydrology, and global climate studies. Through rigorous academic training and extensive research, Dr. Zhang has developed innovative approaches and technologies that have propelled advancements in disaster mitigation, environmental monitoring, and water resource management.

Experience

Prof. Dr. Wanchang Zhang is a distinguished Professor and Ph.D. Supervisor at the Aerospace Information Research Institute, Chinese Academy of Sciences (CAS), and Vice Director of the CAS-TWAS Center of Excellence on Space Technology for Disaster Mitigation. With extensive academic positions at Nagoya University, Nanjing University, and the Institute of Atmospheric Physics at CAS, he has pioneered research in hydrology, water resources, climate change, and disaster risk mitigation. Dr. Zhang has developed advanced simulation systems and software for monitoring and managing environmental and geological disasters, solidifying his reputation as a leader in Earth System Science and GIS applications.

Research Interests

Prof. Dr. Wanchang Zhang’s research interests lie at the intersection of Earth System Science and advanced remote sensing technologies. His work spans diverse domains, including the study of hydrological processes, water resource management, and water environment simulation systems. He is deeply involved in understanding global climate change and its impacts, as well as developing methodologies for disaster risk assessment and mitigation. Dr. Zhang’s expertise extends to creating innovative models for monitoring and early warning of geological hazards, droughts, and floods, leveraging GIS and remote sensing tools. His research also addresses pressing global challenges in ecology and environmental sustainability, showcasing a commitment to using science and technology to mitigate disasters and enhance resilience.

Skills

Prof. Dr. Wanchang Zhang possesses a comprehensive skill set in advanced Earth System Science research, with a strong emphasis on remote sensing and GIS applications. He is adept at developing and implementing distributed hydrology and water resource simulation systems, including the ESSI-I, II, and III models. His expertise extends to designing practical tools and software for risk assessment, environmental monitoring, and disaster early warning systems. Dr. Zhang is skilled in conducting interdisciplinary research that integrates hydrology, ecology, and climate change studies. Additionally, his proficiency in academic writing and publishing is reflected in his extensive record of SCI/EI-indexed papers, patents, and highly cited research. His technical and managerial capabilities also include leading collaborative projects, supervising Ph.D. candidates, and contributing to global academic and professional communities.

Awards

Prof. Dr. Wanchang Zhang has received numerous accolades in recognition of his exceptional contributions to Earth System Science and remote sensing applications. He was honored as an awardee of the prestigious “Hundred Talents Program” by the Chinese Academy of Sciences (CAS), highlighting his status as a leading expert in his field. His groundbreaking research has earned him five awards for papers published in esteemed international and domestic journals or presented at conferences. Additionally, several of his publications are acknowledged as highly cited works in the ESI database and domestic journals, underscoring their significant impact on the scientific community. Dr. Zhang’s innovative contributions are further evidenced by 10 national invention patents and 14 software copyrights, showcasing his pivotal role in advancing technology and scientific knowledge.

 

Publication Top Noted

Title: Semantic segmentation of urban buildings from VHR remote sensing imagery using a deep convolutional neural network

  • Authors: Y Yi, Z Zhang, W Zhang, C Zhang, W Li, T Zhao
  • Journal: Remote Sensing
  • Volume: 11
  • Issue: 15
  • Article Number: 1774
  • Cited by: 227
  • Year: 2019

Title: Landslide susceptibility mapping using multiscale sampling strategy and convolutional neural network: A case study in Jiuzhaigou region

  • Authors: Y Yi, Z Zhang, W Zhang, H Jia, J Zhang
  • Journal: Catena
  • Volume: 195
  • Article Number: 104851
  • Cited by: 181
  • Year: 2020

Title: Assessment of water quality and identification of polluted risky regions based on field observations & GIS in the Honghe River Watershed, China

  • Authors: CA Yan, W Zhang, Z Zhang, Y Liu, C Deng, N Nie
  • Journal: PloS One
  • Volume: 10
  • Issue: 3
  • Article Number: e0119130
  • Cited by: 178
  • Year: 2015

Title: Mapping favorable groundwater potential recharge zones using a GIS-based analytical hierarchical process and probability frequency ratio model: A case study from an agro-urban area

  • Authors: A Arshad, Z Zhang, W Zhang, A Dilawar
  • Journal: Geoscience Frontiers
  • Volume: 11
  • Issue: 5
  • Pages: 1805-1819
  • Cited by: 161
  • Year: 2020

Title: 基于 GIS 的空间插值方法研究 (Spatial interpolation method based on GIS)

  • Authors: 朱求安 (Zhu Qiunan), 张万昌 (Zhang Wanchang), 余钧辉 (Yu Junhui)
  • Journal: 江西师范大学学报: 自然科学版 (Journal of Jiangxi Normal University: Natural Science Edition)
  • Volume: 28
  • Issue: 2
  • Pages: 183-188
  • Cited by: 144
  • Year: 2004

Title: A simple empirical topographic correction method for ETM+ imagery

  • Authors: Y Gao, W Zhang
  • Journal: International Journal of Remote Sensing
  • Volume: 30
  • Issue: 9
  • Pages: 2259-2275
  • Cited by: 143
  • Year: 2009

Conclusion

Dr. Wanchang Zhang’s groundbreaking research, prolific publication record, and technological innovations make him a strong contender for the Best Researcher Award. His contributions to Earth System Science and disaster mitigation have not only enriched academic understanding but also provided practical solutions to pressing global challenges.

Jacob Kwaku Nkrumah | Detection and Prevention | Best Researcher Award

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Dr. Jacob Kwaku Nkrumah | Detection and Prevention | Best Researcher Award

Ph.D student at Jiangsu University, Zhenjiang, China

Dr. Jacob Kwaku Nkrumah is a dedicated academic and researcher specializing in automotive and mechanical engineering. He is currently pursuing a Ph.D. in Vehicle Engineering at Jiangsu University, China, with anticipated completion in December 2024. Dr. Nkrumah holds advanced degrees, including an MPhil in Automotive Engineering and Technology and an M-Tech in Mechanical Engineering Education, complemented by a robust background in teaching and curriculum development. His research focuses on automotive safety systems, innovative engineering solutions, and materials science, with multiple publications in esteemed journals. Dr. Nkrumah’s professional experience includes roles as a lecturer at Tamale Technical University and as a teacher in Ghana’s education system, showcasing his passion for knowledge dissemination and academic excellence.

 

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Education

Dr. Jacob Kwaku Nkrumah has an impressive educational background that highlights his dedication to advancing his expertise in mechanical and automotive engineering. He is currently pursuing a Ph.D. in Vehicle Engineering at Jiangsu University, Zhenjiang, China, with completion expected in December 2024. He holds an MPhil in Automotive Engineering and Technology (2021) and an M-Tech in Mechanical Engineering Education (2014), both from the University of Education, Winneba, Ghana. In addition, he earned a Diploma in Education from the same institution in 2016. Dr. Nkrumah further strengthened his technical foundation with a B-Tech in Automobile Engineering (2011) from Kwame Nkrumah University of Science and Technology, Kumasi, Ghana, and an HND in Mechanical Engineering (2003) from Tamale Technical University, Ghana. His academic achievements underscore a strong commitment to research and education in engineering disciplines.

Experience

Dr. Jacob Kwaku Nkrumah has extensive teaching and academic experience that spans nearly two decades, showcasing his dedication to education and engineering. From 2017 to 2021, he served as a lecturer in the Automotive Engineering Department at Tamale Technical University, Ghana, where he taught courses such as Engineering Mathematics, Engineering Science, and Engineering Physics. Prior to this, he worked with the Ghana Education Service, first as a teacher at Krachi Senior High School (2012–2017), where he taught Mathematics and Physics, and earlier at Kogni Junior High School (2004–2016), where he was responsible for teaching Science and Mathematics. Dr. Nkrumah began his professional journey as a National Service Personnel at Debokpa Vocational Institute, Tamale, from 2003 to 2004. His diverse roles have equipped him with strong classroom management, conflict resolution, and curriculum development skills, which reflect his commitment to academic excellence and the advancement of engineering education.

Research Interests

Dr. Jacob Kwaku Nkrumah’s research interests are primarily focused on automotive engineering, vehicle safety systems, and mechanical engineering innovations. His work explores the development and enhancement of automotive technologies, particularly in the areas of intelligent lighting systems, headlight beam intensity control, and sensor-based automatic systems for improved driving safety and efficiency. Dr. Nkrumah is also deeply involved in material science, with research on the modal and thermal analysis of components like the internal combustion engine’s connecting rod. His studies aim to contribute to the advancement of vehicle performance, safety, and energy efficiency, as well as the broader field of mechanical engineering through the application of finite element methods and other engineering simulation techniques.

Skills

Dr. Jacob Kwaku Nkrumah possesses a diverse set of skills that enhance his effectiveness as both an educator and a researcher. He is adept at preparing comprehensive lesson notes and has strong classroom management abilities, ensuring a productive and focused learning environment. His skills in conflict management within the classroom have been key in maintaining harmony and fostering effective student engagement. Additionally, Dr. Nkrumah has significant experience in curriculum development, where he has contributed to shaping educational frameworks to meet modern engineering standards. These skills complement his research expertise and his ability to teach complex engineering concepts effectively, making him a well-rounded academic professional.

Awards

Dr. Jacob Kwaku Nkrumah has earned recognition for his outstanding contributions to the field of automotive and mechanical engineering. His dedication to research and education has led to multiple publications in prestigious journals, highlighting his innovative work in automotive safety systems and mechanical engineering. While specific awards are not listed, Dr. Nkrumah’s academic achievements, including his Ph.D. candidacy and successful research projects, reflect his commitment to advancing knowledge and excellence in engineering. His work continues to garner attention and contributes significantly to the academic community, particularly in the realm of vehicle engineering and safety technologies.

 

Publication Top Noted

Title: Assessing the Skills of Roadside Mechanics in Diagnosing and Fixing Problems of Modern Electronic Managed Vehicles in Ghana (Tamale Metropolis)

  • Authors: B Ziblim, J Nkrumah, I Imoro
  • Journal: American Scientific Research Journal for Engineering, Technology, and …
  • Cited by: 7
  • Year: 2018

Title: The evolution of vehicle pneumatic vibration isolation: A systematic review

  • Authors: VA Atindana, X Xu, AN Nyedeb, JK Quaisie, JK Nkrumah, SP Assam
  • Journal: Shock and Vibration
  • Volume: 2023(1)
  • Article Number: 1716615
  • Cited by: 6
  • Year: 2023

Title: A novel semi-active control of an integrated chassis and seat quasi-zero stiffness suspension system for off-road vehicles

  • Authors: VA Atindana, X Xu, NJ Kwaku, A Akayeti, X Jiang
  • Journal: Journal of Vibration and Control
  • Article Number: 10775463231224835
  • Cited by: 5
  • Year: 2024

Title: Analysis of the material properties of vehicle suspension coil spring

  • Authors: I Imoro, JK Nkrumah, B Ziblim, AH Mohammed
  • Journal: World Journal of Engineering and Technology
  • Volume: 11
  • Issue: 4
  • Pages: 827-858
  • Cited by: 4
  • Year: 2023

Title: Experimental design and optimization of pneumatic low-frequency driver seat for off-road vehicles: quasi-zero negative stiffness and gray wolf optimization algorithm

  • Authors: VA Atindana, X Xu, L Huan, A Nirere, AN Nyedeb, JK Quaisie, NJ Kwaku, …
  • Journal: Journal of the Brazilian Society of Mechanical Sciences and Engineering
  • Volume: 45
  • Cited by: 4
  • Year: 2023

Title: Review of Suspension Control and Simulation of Passive, Semi-Active and Active Suspension Systems Using Quarter Vehicle Model

  • Authors: DIO Jacob Kwaku Nkrumah, Kwabla Sherry Amedorme, Baba Ziblim
  • Journal: American Academic Scientific Research Journal for Engineering, Technology …
  • Cited by: 2
  • Year: 2022

Title: A review of automotive intelligent and adaptive headlight beams intensity control approaches

  • Authors: JK Nkrumah, Y Cai, A Jafaripournimchahi
  • Journal: Advances in Mechanical Engineering
  • Volume: 16
  • Issue: 4
  • Article Number: 16878132231220355
  • Cited by: 1
  • Year: 2024

Conclusion

Dr. Jacob Kwaku Nkrumah exemplifies the qualities of an outstanding researcher. His dedication to advancing automotive safety and efficiency, combined with his academic contributions and educational impact, make him a strong contender for the Best Researcher Award. His work addresses critical challenges in engineering, offering innovative solutions with practical applications, which aligns with the award’s mission to recognize excellence in research.

Jinshuo Liu | Data Mining | Top Researcher Award

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Prof. Jinshuo Liu | Data Mining | Top Researcher Award

Professor at Wuhan University, China

Prof. Jinshuo Liu is a distinguished researcher and educator with over 27 years of experience at Wuhan University, one of China’s top universities. He currently serves as a Professor in the School of Cyber Science and Engineering, where he leads a research group specializing in web mining and data mining. Prof. Liu has supervised numerous students, guiding six Ph.D. and 101 Master’s students in their research. His leadership extends to being the head of the collaboration lab between Wuhan University and the University of Edinburgh, UK. Prof. Liu’s extensive research contributions include over 50 published papers and more than 30 Chinese invention patents. He has led 41 projects, including major initiatives funded by the National Natural Science Foundation of China and the National Key Research and Development Program of China. His research interests are rooted in data mining, high-performance computing, and advancing technological solutions in cybersecurity.

 

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Education

Prof. Jinshuo Liu holds an impressive academic background in computer science, which has been instrumental in shaping his research career. He earned his Ph.D. in Computer Software and Theory from Wuhan University, China, in 2006, building on his foundational knowledge and research skills. Prior to that, he completed a Master’s degree in Computer Science from Leiden University, Netherlands, in 2003, where he further honed his expertise in computing theories and applications. Prof. Liu began his academic journey at Wuhan University, where he obtained his Bachelor’s degree in Computer Science in 1997. His academic pursuits also include international experience as a Visiting Associate Professor at the University of Virginia, USA, in 2017, and as a Visiting Scholar at Konkuk University, Korea, in 2012. These experiences have enriched his global perspective and contributed to his leadership in data mining and high-performance computing.

Experience

Prof. Jinshuo Liu has an extensive professional background, with over 27 years at Wuhan University, one of China’s top universities. Currently, he is a Professor in the School of Cyber Science and Engineering, where he leads a specialized research group in web mining. His leadership extends to an international collaboration lab between Wuhan University and the University of Edinburgh, UK, highlighting his role in fostering global research initiatives. Throughout his career, Prof. Liu has led 41 major projects, including three funded by the National Natural Science Foundation of China and three from the National Key Research and Development Program of China. He has also supervised the academic progress of six Ph.D. students and 101 master’s students. His contributions to the field are further underscored by his impressive record of over 50 publications and more than 30 invention patents, which reflect his commitment to advancing research in data mining and high-performance computing.

Research Interests

Prof. Jinshuo Liu’s research interests are centered on data mining and high-performance computing, with a focus on cutting-edge challenges in web mining and information processing. His work involves developing advanced techniques to address complex issues in identity disambiguation, network security, and critical information dissemination within cyberspace. Leading research at the intersection of computing theory and practical application, Prof. Liu also collaborates internationally to explore topics such as entity identification, public opinion monitoring, and efficient parallel computation for large-scale Earth system models. His research aims to innovate solutions for high-impact applications in both cybersecurity and the analysis of large data sets.

Skills

Prof. Jinshuo Liu possesses a robust skill set in advanced data mining, high-performance computing, and cybersecurity. His expertise includes web mining, identity disambiguation, and malicious information tracing, utilizing cutting-edge algorithms and frameworks for efficient data processing. He is highly skilled in developing and applying high-efficiency identification and recovery methods, particularly in areas involving network supervision and public opinion analysis. With significant experience leading national projects, Prof. Liu is adept at managing complex research collaborations, including his leadership role in a collaborative lab between Wuhan University and the University of Edinburgh. His skills extend to fostering innovation in computational methods for large-scale Earth system models, making significant contributions to both national and international projects.

Awards

Prof. Jinshuo Liu has received several prestigious awards in recognition of his contributions to research and technology. Notably, he was honored with the China Earthquake Administration Scientific and Technological Achievement Award for Earthquake Prevention and Disaster Reduction, receiving the 2nd Class Award in 2017. In the same year, he was awarded the China State Grid Science and Technology Progress Award, earning the 3rd Prize. These accolades highlight his significant contributions to both the advancement of scientific knowledge and practical applications in critical fields, including cybersecurity and disaster management. Prof. Liu’s recognition underscores his leadership and innovative contributions to technology and research.

 

Publication Top Noted

Title: Collaborate SLM and LLM with latent answers for event detection

  • Authors: Yan, Y., Liu, J., Ji, D., Wang, X., Pan, J.Z.
  • Journal: Knowledge-Based Systems
  • Volume: 305
  • Article Number: 112684
  • Year: 2024
  • Citations: 0

Title: Construction of Disaster Event Evolutionary Graph Based on Spatiotemporal Relationship

  • Authors: Ning, H., Sui, H., Wang, J., Liu, J.
  • Journal: Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University
  • Volume: 49
  • Issue: 5
  • Pages: 831–843
  • Year: 2024
  • Citations: 1

Title: Knowledge-Enhanced Prompt Learning for Few-Shot Text Classification

  • Authors: Liu, J., Yang, L.
  • Journal: Big Data and Cognitive Computing
  • Volume: 8
  • Issue: 4
  • Article Number: 43
  • Year: 2024
  • Citations: 0

Title: Intelligent load balancing in data center software-defined networks

  • Authors: Gilliard, E., Liu, J., Aliyu, A.A., Jing, H., Wang, M.
  • Journal: Transactions on Emerging Telecommunications Technologies
  • Volume: 35
  • Issue: 4
  • Article Number: e4967
  • Year: 2024
  • Citations: 0

Title: Knowledge graph reasoning for cyber attack detection

  • Authors: Gilliard, E., Liu, J., Aliyu, A.A.
  • Journal: IET Communications
  • Volume: 18
  • Issue: 4
  • Pages: 297–308
  • Year: 2024
  • Citations: 2

Title: Inhomogeneous Interest Modeling via Hypergraph Convolutional Networks for Social Recommendation

  • Authors: Luo, L., Wang, M., Liu, J., Huang, J.
  • Conference: Proceedings of the International Joint Conference on Neural Networks
  • Year: 2024
  • Citations: 0
  • Title: Content-Biased and Style-Assisted Transfer Network for Cross-Scene Hyperspectral Image Classification
  • Authors: Shi, Z., Lai, X., Deng, J., Liu, J.

Title: An efficient blockchain-based approach to improve the accuracy of intrusion detection systems

  • Authors: Abubakar, A.A., Liu, J., Gilliard, E.
  • Journal: Electronics Letters
  • Volume: 59
  • Issue: 18
  • Article Number: e12888
  • Year: 2023
  • Citations: 2

Conclusion

Prof. Jinshuo Liu’s career reflects a commitment to pioneering research, impactful mentorship, and substantial contributions to technology and society. His leadership in national and collaborative projects, international research ties, numerous publications, and innovation patents underscore his status as a top researcher. Prof. Liu is well-suited for the Top Researcher Award, given his groundbreaking achievements in data mining, high-performance computing, and digital security advancements.

Syed Aziz Shah | Privacy-Preserving | Top Researcher Award

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Dr. Syed Aziz Shah | Privacy-Preserving | Top Researcher Award

Associate Professor at Coventry University UK, United Kingdom

Dr. Syed Aziz Shah is a Reader (Associate Professor) at the Research Centre for Intelligent Healthcare at Coventry University, UK, where he specializes in AI-based RF sensing technologies. He also serves as the Post Graduate Research Lead at the same institution. Dr. Shah earned his PhD in Electrical and Electronics Engineering from Xidian University, China, in 2018. His research focuses on advanced sensing techniques, remote patient monitoring, and machine learning applications in healthcare. He has received several prestigious awards, including the UK’s ESPRC New Investigator Award and the Royal Academy of Engineering’s Emerging Leader endorsement for his pioneering work in RF sensing. Dr. Shah has published extensively in high-impact journals and is actively involved in various academic and professional affiliations, including IEEE and the Pakistan Engineering Council.

 

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Education

Dr. Syed Aziz Shah completed his PhD in Electrical and Electronics Engineering at Xidian University, China, from 2015 to 2018. His doctoral research focused on advanced RF sensing technologies, and he gained recognition for his significant contributions to the field. Dr. Shah’s academic journey also includes extensive research and publications in esteemed journals such as IEEE, IET, and MDPI, which earned him several awards, including the Research Excellence Award from Xidian University for achieving the highest number of publications during his PhD studies. His strong educational foundation has been instrumental in his current work at the Research Centre for Intelligent Healthcare at Coventry University, UK, where he leads cutting-edge research in AI-based RF sensing technologies.

Experience

Dr. Syed Aziz Shah currently holds the position of Reader (Associate Professor) in AI-based RF Sensing Technologies at the Research Centre for Intelligent Healthcare, Coventry University, UK, where he has been serving since 2020. In addition, he is the Post Graduate Research Lead at the same institution, overseeing research initiatives and guiding postgraduate research projects. Dr. Shah leads the Healthcare Sensing Technology Group, managing a team of researchers including one Assistant Professor, two Research Fellows, and eight PhD students. He has made significant contributions to the field of intelligent healthcare through his research on AI-based RF sensing technologies, particularly in applications such as remote patient monitoring and fall detection. His leadership extends beyond research, as he also serves as the Outreach Programme Manager at the Institute of Health and Wellbeing at Coventry University, where he works to enhance the institute’s visibility through strategic initiatives. Throughout his career, Dr. Shah has been invited to deliver keynote talks and courses at prestigious institutions such as Imperial College London, University of Bristol, University of Manchester, and University of Leeds, further cementing his position as an expert in the field. He has also supervised several PhD students and served as an external examiner for doctoral theses at various international institutions.

Research Interests

Dr. Syed Aziz Shah’s research interests lie at the intersection of AI-based technologies and RF (Radio Frequency) sensing, with a particular focus on their applications in healthcare. His work explores innovative solutions for remote patient monitoring, human activity recognition, and disease detection through advanced RF sensing techniques. Dr. Shah has contributed extensively to the development of intelligent healthcare systems, using machine learning algorithms to enhance the accuracy and efficiency of RF sensing technologies. His research also delves into the use of intelligent reflecting surfaces in communication systems, aiming to improve the quality and reliability of wireless communications for healthcare applications. Additionally, he is involved in developing AI-driven methodologies to support medical diagnostics, such as contactless respiratory waveform extraction for COVID-19 patients. Dr. Shah is particularly interested in the integration of RF sensing and AI to create cutting-edge solutions for healthcare monitoring and intervention, advancing the field of intelligent healthcare technology.

Skills

Dr. Syed Aziz Shah possesses a robust set of skills in advanced technologies, particularly in the realms of AI-based RF Sensing, Machine Learning, and Signal Processing. His expertise spans RF System Design and the application of Artificial Intelligence in healthcare sensing technologies. He is adept at developing and managing RF sensing solutions for real-time healthcare monitoring, including fall detection and respiratory waveform extraction for remote patient care. Dr. Shah has substantial skills in project management, exemplified through leading large research projects and managing research teams at Coventry University’s Research Centre for Intelligent Healthcare, where he oversees a team comprising Assistant Professors, Research Fellows, and Ph.D. students. Additionally, Dr. Shah is experienced in outreach and pastoral care, having managed outreach initiatives and welfare programs to enhance institutional visibility and student support. His skills in supervision and mentorship are demonstrated by his involvement in Ph.D. supervision and training programs, alongside his role as an external examiner for doctoral research. His technical and leadership skills are further underscored by his active participation as a keynote speaker, course leader, and organizer of academic conferences and workshops, establishing him as a leader in the field of intelligent healthcare and RF sensing technology.

Awards

Dr. Syed Aziz Shah has received several prestigious awards and honors throughout his academic and research career. Notably, he was honored with the UK’s Most Prestigious ESPRC New Investigator Award, a recognition granted to individuals holding academic lectureship positions, which includes a substantial grant of GBP 410,000. This award highlights his pioneering work in RF sensing for remote patient monitoring. Additionally, Dr. Shah was endorsed as an Exceptional Talent: ‘Emerging Leader’ by the Royal Academy of Engineering, UK, in acknowledgment of his groundbreaking contributions to the field of RF sensing technology. This prestigious recognition is given to early-career innovators and scientists who demonstrate exceptional potential and leadership in their field. Furthermore, he received the Research Excellence Award from Xidian University, China, for achieving the highest number of publications in esteemed journals such as IEEE, IET, and MDPI during his Ph.D. studies. As part of this honor, he was also awarded a USD 5,000 reward for his academic achievements. These awards reflect Dr. Shah’s significant impact on the research community, particularly in the area of intelligent healthcare technology and RF sensing.

Publication Top Noted

Title: RF sensing technologies for assisted daily living in healthcare: A comprehensive review

  • Authors: SA Shah, F Fioranelli
  • Journal: IEEE Aerospace and Electronic Systems Magazine
  • Volume: 34
  • Issue: 11
  • Pages: 26-44
  • Cited by: 170
  • Year: 2019

Title: An intelligent non-invasive real-time human activity recognition system for next-generation healthcare

  • Authors: W Taylor, SA Shah, K Dashtipour, A Zahid, QH Abbasi, MA Imran
  • Journal: Sensors
  • Volume: 20
  • Issue: 9
  • Article Number: 2653
  • Cited by: 162
  • Year: 2020

Title: A novel hybrid secure image encryption based on julia set of fractals and 3D Lorenz chaotic map

  • Authors: F Masood, J Ahmad, SA Shah, SS Jamal, I Hussain
  • Journal: Entropy
  • Volume: 22
  • Issue: 3
  • Article Number: 274
  • Cited by: 130
  • Year: 2020

Title: A Review of the State of the Art in Non-Contact Sensing for COVID-19

  • Authors: W Taylor, QH Abbasi, K Dashtipour, S Ansari, SA Shah, A Khalid, et al.
  • Journal: Sensors
  • Volume: 20
  • Issue: 19
  • Article Number: 5665
  • Cited by: 108
  • Year: 2020

Title: Radar sensing for healthcare: The applications of radar in monitoring vital signs and recognizing human activity patterns

  • Authors: DF Fioranelli, DSA Shah, H Li, A Shrestha, DS Yang, DJL Kernec
  • Journal: Electronics Letters
  • Volume: 55
  • Issue: 19
  • Pages: 1022-1024
  • Cited by: 108*
  • Year: 2019

Title: Radar for health care: Recognizing human activities and monitoring vital signs

  • Authors: F Fioranelli, J Le Kernec, SA Shah
  • Journal: IEEE Potentials
  • Volume: 38
  • Issue: 4
  • Pages: 16-23
  • Cited by: 94
  • Year: 2019

Title: Machine learning driven approach towards the quality assessment of fresh fruits using non-invasive sensing

  • Authors: A Ren, A Zahid, A Zoha, SA Shah, MA Imran, A Alomainy, QH Abbasi
  • Journal: IEEE Sensors Journal
  • Volume: 20
  • Issue: 4
  • Pages: 2075-2083
  • Cited by: 89
  • Year: 2019

Title: Human activity recognition: Preliminary results for dataset portability using FMCW radar

  • Authors: SA Shah, F Fioranelli
  • Conference: 2019 International Radar Conference (RADAR)
  • Pages: 1-4
  • Cited by: 73
  • Year: 2019

Title: Freezing of gait detection considering leaky wave cable

  • Authors: X Yang, SA Shah, A Ren, N Zhao, Z Zhang, D Fan, J Zhao, W Wang, et al.
  • Journal: IEEE Transactions on Antennas and Propagation
  • Volume: 67
  • Issue: 1
  • Pages: 554-561
  • Cited by: 64
  • Year: 2018

Conclusion

Dr. Syed Aziz Shah’s exceptional contributions to AI, RF sensing, and intelligent healthcare systems make him a fitting nominee for the Top Researcher Award. His leadership in research, innovative projects, and outstanding academic achievements reflect his dedication to advancing technology for the betterment of society. His accolades, teaching roles, and continued research excellence position him as a trailblazer in his field, deserving of this prestigious recognition.

Liliana Aguilar-Marcelino | Cybersecurity | Best Innovation Award

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Dr. Liliana Aguilar-Marcelino | Cybersecurity | Best Innovation Award

Senior researcher at Instituto Nacional de Investigaciones Forestales Agricolas y Pecuarias, Mexico

Dr. Liliana Aguilar-Marcelino is a senior researcher at the Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad (CENID-SAI) at INIFAP, Mexico. With a focus on microbial consortia, biocontrol, biotechnology, and natural product pharmacology, she investigates the bioactivity of fungi, bacteria, insects, mites, and nematodes. Her work includes exploring sustainable pest control strategies through biocontrol agents and metabolomic studies. Dr. Aguilar-Marcelino has contributed extensively to research on the insecticidal properties of metabolites from edible mushrooms and the development of nematocidal compounds. Her innovative research aims to advance agricultural sustainability and environmental health.

 

Profile

Scopus Profile

Google Scholar Profile

ORCID Profile

Education

Dr. Liliana Aguilar-Marcelino holds a distinguished academic background in the field of biological sciences. She completed her undergraduate studies in biology and later pursued advanced education, specializing in microbiology and biotechnology. Dr. Aguilar-Marcelino obtained her graduate degree (Master’s and/or Ph.D.) from a renowned institution, where she honed her expertise in microbial consortia, biocontrol, biotechnology, and the bioactivity of natural products. Her education has been instrumental in shaping her research focus, which spans a wide array of topics including natural product pharmacology, metabolomics, and the development of sustainable pest management solutions. With her strong academic foundation, Dr. Aguilar-Marcelino has become a leading researcher in her field, contributing significantly to the advancement of agricultural science and sustainable biocontrol technologies.

Experience

Dr. Liliana Aguilar-Marcelino has been a senior researcher at the Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad (CENID-SAI) at INIFAP, Mexico, since 2008. During her tenure, she has focused on pioneering research in microbial consortia, biocontrol, biotechnology, and metabolomics. She has led multiple studies exploring the bioactivity of fungi, bacteria, insects, mites, and nematodes, contributing to the development of sustainable solutions for pest control and agricultural health. Dr. Aguilar-Marcelino has published numerous research papers on topics such as the insecticidal effects of metabolites from edible mushrooms and the nematocidal properties of natural extracts, further establishing her expertise in the field of biocontrol and natural product pharmacology.

Research Interests

Dr. Liliana Aguilar-Marcelino’s research interests are centered on microbial consortia, biocontrol, and biotechnology, with a particular focus on the bioactivity of natural products. She specializes in metabolomics and the pharmacological potential of fungi, bacteria, insects, mites, and nematodes. Her work explores the development of natural pest control methods and sustainable agricultural practices through the study of bioactive compounds derived from edible mushrooms, fungi, and other microorganisms. Additionally, Dr. Aguilar-Marcelino investigates the potential of natural products for managing plant-parasitic nematodes and other agricultural pests, aiming to provide eco-friendly alternatives to traditional chemical controls.

 

Publication Top Noted

Title: New and future developments in microbial biotechnology and bioengineering: Trends of microbial biotechnology for sustainable agriculture and biomedicine systems: Diversity and applications

  • Authors: AA Rastegari, AN Yadav, N Yadav
  • Publisher: Elsevier
  • Cited by: 136
  • Year: 2020

Title: Micro (nano) plastics in wastewater: A critical review on toxicity risk assessment, behaviour, environmental impact, and challenges

  • Authors: S Singh, TSSK Naik, AG Anil, J Dhiman, V Kumar, DS Dhanjal, et al.
  • Journal: Chemosphere
  • Volume: 290
  • Article Number: 133169
  • Cited by: 71
  • Year: 2022

Title: Plasmodium berghei ookinetes induce nitric oxide production in Anopheles pseudopunctipennis midguts cultured in vitro

  • Authors: A Herrera-Ortíz, H Lanz-Mendoza, J Martínez-Barnetche, et al.
  • Journal: Insect Biochemistry and Molecular Biology
  • Volume: 34
  • Issue: 9
  • Pages: 893-901
  • Cited by: 65
  • Year: 2004

Title: The nematophagous fungus Duddingtonia flagrans reduces the gastrointestinal parasitic nematode larvae population in faeces of orally treated calves maintained under tropical conditions

  • Authors: P Mendoza-de-Gives, ME López-Arellano, L Aguilar-Marcelino, et al.
  • Journal: Veterinary Parasitology
  • Volume: 263
  • Pages: 66-72
  • Cited by: 52
  • Year: 2018

Title: Recent Trends in Mycological Research: Volume 1: Agricultural and Medical Perspective

  • Author: AN Yadav
  • Publisher: Springer International Publishing
  • Cited by: 49
  • Year: 2021

Title: Using molecular techniques applied to beneficial microorganisms as biotechnological tools for controlling agricultural plant pathogens and pests

  • Authors: L Aguilar-Marcelino, P Mendoza-de-Gives, LKT Al-Ani, et al.
  • Book: Molecular Aspects of Plant Beneficial Microbes in Agriculture
  • Pages: 333-349
  • Cited by: 47
  • Year: 2020

Title: Jesús Antonio Pineda-Alegría, José Ernesto Sánchez-Vázquez, Manases González-Cortazar, Alejandro Zamilpa, María Eugenia López-Arellano, Edgar Josué Cuevas-Padilla

  • Authors: P Mendoza-de-Gives, L Aguilar-Marcelino
  • Cited by: 69
  • Year: 2018

Conclusion

Dr. Liliana Aguilar-Marcelino’s innovative research in the areas of biocontrol, biotechnology, and natural product pharmacology has led to the development of several novel approaches for sustainable agricultural pest management. By focusing on natural alternatives to chemical pesticides, her work not only advances scientific understanding but also promotes environmentally friendly practices. Through her groundbreaking studies, Dr. Aguilar-Marcelino has significantly contributed to the field of sustainable agriculture, making her an outstanding candidate for the Research for Best Innovation Award.

Zhijiao Chen | Cryptographic Hardware | Best Researcher Award

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Prof. Zhijiao Chen | Cryptographic Hardware | Best Researcher Award

Associate Professor at Beijing University of Post and Telecommunications, China

Prof. Zhijiao Chen is an Associate Professor at Beijing University of Posts and Telecommunications, specializing in millimeter-wave antenna design and wireless communication technologies. He holds a Ph.D. in Antennas from Queen Mary University of London and has a strong background in dielectric resonator antennas, 3D printed antennas, and shaped beam synthesis. Prof. Chen has collaborated with leading institutions worldwide, including the National Physical Laboratory and City University of Hong Kong. His research focuses on high-efficiency antenna arrays for 5G and beyond, as well as innovative materials for antenna design. He is an active member of IEEE and has received multiple awards for his contributions to research and teaching.

 

Profile

Scopus Profile

ORCID Profile

Education

Prof. Zhijiao Chen obtained his PhD from the Antennas Research Group at Queen Mary University of London (2010–2014), under the supervision of Prof. Clive G. Parini, a Fellow of the Royal Academy of Engineering. His doctoral research, awarded in November 2014, laid a strong foundation in advanced antenna design. Prior to his PhD, he completed a BSc in a joint program between Beijing University of Posts and Telecommunications and Queen Mary University of London, graduating with First Class Honors in 2010.

Experience

Currently, Prof. Chen serves as an Associate Professor at the Beijing University of Posts and Telecommunications (2020-present). He previously held a lecturer position there from 2014 to 2020. He has extensive international exposure, having been a Visiting Scholar at institutions like the National Physical Laboratory in the UK (2019), City University of Hong Kong (2018–2019), and Northeastern University in the USA (2013). His collaborations with leading researchers in the field, such as Professors Tian Hong Loh, Chi Hou Chan, and Nian-Xiang Sun, underscore his expertise and contribution to global antenna research.

Research Interests

Prof. Chen’s research interests span critical areas in antenna technology, including millimeter-wave and dielectric resonator antennas, base station antennas, 3D printed antennas, shaped beam synthesis, and bandpass filters. His innovative work in these areas has significant implications for advancing 5G, satellite communication, and vehicular connectivity.

Awards 

Prof. Chen has received multiple accolades throughout his career, reflecting his scholarly impact. Notable awards include the Young Scientists Award at the ACES-China 2021 symposium and the Best Oral Presentation Award at IEEE ICET 2021. His contributions to antenna technology have also earned him first place in the 2020 Ceyear Electronic Measurement Competition and Best Paper Award at IEEE iWAT2013, underscoring his role as a leader in antenna research.

Skills

Prof. Zhijiao Chen specializes in millimeter-wave antennas, dielectric resonator antennas, 3D printed antennas, and beam synthesis for advanced communication systems. His expertise includes high-efficiency antenna arrays, satellite communications, and IoT applications. He is skilled in materials science, particularly in the use of ceramics and dielectric structures for antenna design. Prof. Chen has extensive experience in collaborative research with leading institutions and plays an active role in the academic community as a reviewer, editor, and conference session chair. His work bridges theory and practice, contributing to advancements in wireless communication technologies like 5G and beyond.

Publication Top Noted

  • Great Adventures and Experiences: The IEEE Antennas and Propagation Society Young Professional Ambassador Program [Young Professionals]
    • Author(s): Chen, Z.
    • Journal: IEEE Antennas and Propagation Magazine
    • Year: 2024
    • Volume: 66
    • Issue: 2
    • Pages: 80–83
    • Type: Article, Open Access
    • Abstract & Related Documents: Not available
  • Compact Multibeam Antenna Using Miniaturized Slow-Wave Substrate-Integrated Waveguide Rotman Lens for Satellite-Assisted Internet of Vehicles
    • Author(s): Deng, J.-Y., Liu, Y.-B., Chen, Z., Lin, W.
    • Journal: IEEE Internet of Things Journal
    • Year: 2024
    • Volume: 11
    • Issue: 4
    • Pages: 6848–6856
    • Type: Article
    • Citations: 3
  • FDM 3D-Printed DRA Array for 5G Millimeter Wave and 6G Applications
    • Author(s): Li, S., Izquierdo, B.S., Gao, S., Chen, Z.
    • Conference: IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)
    • Year: 2024
    • Pages: 417–418
    • Type: Conference Paper
    • Citations: 0
  • A Dental Dielectric Resonator Antenna
    • Author(s): Chen, Z., Zhang, J., Jing, Y., Jiang, X., Sanz-Izquierdo, B.
    • Conference: IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)
    • Year: 2024
    • Pages: 1391–1392
    • Type: Conference Paper
    • Citations: 0
  • IWS 2024 Women in Microwaves: Challenge Yourself and Be Proud [Women in Microwaves]
    • Author(s): Li, Z., Chen, Z., Han, Y., Yang, W., Che, W.
    • Journal: IEEE Microwave Magazine
    • Year: 2024
    • Volume: 25
    • Issue: 10
    • Pages: 87–90
    • Type: Conference Paper
    • Citations: 0
  • A W-Band High-Gain Low-Sidelobe Circular-Shaped Monopulse Antenna Array Based on Dielectric Loaded Waveguide
    • Author(s): Zhang, X., Chen, Z., Ye, X.
    • Journal: IEEE Access
    • Year: 2024
    • Volume: 12
    • Pages: 64997–65006
    • Type: Article, Open Access
    • Citations: 2
  • A Wearable Open-Ring Dielectric Resonator Antenna with Frequency Reconfiguration
    • Author(s): Jiang, X., Chen, Z., Sanz-Izquierdo, B.
    • Conference: 18th European Conference on Antennas and Propagation, EuCAP 2024
    • Year: 2024
    • Type: Conference Paper
    • Citations: 0
  • Dielectric Resonator Antennas: Materials, Designs and Applications
    • Author(s): Chen, Z., Deng, J., Liu, H.
    • Book Title: Dielectric Resonator Antennas: Materials, Designs and Applications
    • Year: 2024
    • Pages: 1–301
    • Type: Book
    • Citations: 1
  • Wideband Millimeter-Wave MIMO Antenna with a Loaded Dielectric Cover for High-Gain Broadside Radiation
    • Author(s): Chen, Z., Song, W., Wang, W.
    • Journal: Electronics (Switzerland)
    • Year: 2023
    • Volume: 12
    • Issue: 21
    • Article ID: 4384
    • Type: Article, Open Access
    • Citations: 2
  • Novel B-site Scheelite Structure Ceramic Bi(Ge0.5Mo0.5)O4 and its Dielectric Properties
    • Author(s): Xu, D., Zhang, H., Pang, L., Chen, Z., Zhou, D.
    • Journal: Journal of the American Ceramic Society
    • Year: 2023
    • Volume: 106
    • Issue: 11
    • Pages: 6675–6683
    • Type: Article
    • Citations: 7

Conclusion

Prof. Zhijiao Chen’s extensive academic and research experience, along with his significant contributions to the field of antenna technology and communication systems, make him an outstanding candidate for the Research for Best Researcher Award. His expertise, leadership in research projects, collaboration with international institutions, and recognition within the scientific community underscore his qualifications for this honor.

Adla Padma | Blockchain | Women Researcher Award

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Ms. Adla Padma | Blockchain | Women Researcher Award

Research Scholar at Vellore Institute of Technology, India

Ms. Adla Padma is an Assistant Professor (On Contract) at the School of Computer Science Engineering and Information Systems (SCORE) at Vellore Institute of Technology (VIT), Vellore, Tamil Nadu. With over six years of academic experience, her research focuses on blockchain technology and privacy preservation in IoT environments. Currently pursuing a Ph.D. in Computer Science and Engineering at VIT, Ms. Padma’s thesis explores efficient blockchain frameworks for IoT smart environments. She has published several journal articles and conference papers, including works on scalable blockchain solutions and secure information sharing in smart cities. Ms. Padma has received multiple recognitions, including the Raman Research Award for her significant contributions to blockchain research. She has also actively participated in technical workshops and courses related to blockchain, IoT, and cybersecurity.

Profile:

Education:

Ms. Adla Padma is currently pursuing a Ph.D. in Computer Science and Engineering at Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, with her thesis focusing on “An Efficient Blockchain Enabled Privacy Preservation Framework for IoT Smart Environment.” She holds a Master’s degree in Computer Science and Engineering (M.Tech) from Sri Indu Institute of Engineering and Technology, Rangareddy, Telangana, where she graduated in 2016 with a commendable 82.75%. Prior to that, Ms. Padma completed her Bachelor of Technology (B.Tech) in Computer Science and Engineering from KBR Engineering College, Yadadri Bhuvanagiri, Telangana, in 2012, with a notable percentage of 79.94%. Her educational background also includes an Intermediate from Nalanda Junior College, Nalgonda, Telangana, where she scored an impressive 90%. Ms. Padma’s strong academic foundation has laid the groundwork for her successful career in research and teaching.

Professional Experience:

Ms. Adla Padma has over six years of professional experience in the field of academia, specializing in computer science and engineering. She is currently serving as an Assistant Professor (On Contract) at the School of Computer Science Engineering and Information Systems (SCORE) at Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, where she has been involved in teaching and research since 2022. Prior to this, Ms. Padma worked as an Assistant Professor at Sri Indu Institute of Engineering and Technology, Rangareddy, Telangana, from 2016 to 2020. Throughout her career, she has been dedicated to advancing research in blockchain technology, privacy preservation in IoT environments, and related fields. Ms. Padma has also contributed significantly to academic projects, technical talks, and workshops, further enhancing her expertise in areas like machine learning, web technologies, and programming languages. Her academic journey has been marked by a strong focus on both teaching and research, with an emphasis on integrating cutting-edge technologies into real-world applications.

Research Interests:

Ms. Adla Padma’s research interests primarily revolve around the intersection of blockchain technology, privacy preservation, and the Internet of Things (IoT). She is particularly focused on developing efficient frameworks for privacy protection in smart environments using blockchain, aiming to enhance the security and scalability of IoT applications. Her research also explores the design and analysis of algorithms, machine learning, and programming languages such as C, C++, Python, and Java. Additionally, Ms. Padma is interested in web technologies and their application in secure information sharing, as well as the integration of blockchain for smart city solutions. Through her work, she seeks to contribute to the development of innovative solutions that address pressing challenges in digital security and privacy across various industries.

Awards and Honors:

Ms. Adla Padma has been recognized with several prestigious awards and honors throughout her academic and research career. She received the Raman Research Award at VIT, Vellore, Tamil Nadu, for her impactful publications, including “GLSBIoT: GWO-based enhancement for lightweight scalable blockchain for IoT with trust-based consensus” and “Blockchain Based an Efficient and Secure Privacy Preserved Framework for Smart Cities”. These awards reflect her significant contributions to blockchain technology and privacy preservation. Additionally, Ms. Padma has been appointed as a reviewer for the American Journal of Information Science and Technology for the period of 2024–2027, further solidifying her standing in the research community.

Skills:

Ms. Adla Padma possesses a diverse skill set that spans various domains within computer science and engineering. She is highly proficient in blockchain technology, with a focus on privacy preservation and security frameworks for IoT environments. Her expertise extends to the design and analysis of algorithms, programming languages including C, C++, Python, and Java, as well as web technologies and machine learning. Additionally, Ms. Padma is skilled in conducting research, academic writing, and publishing in high-impact journals. She is also experienced in guiding and mentoring students on technical projects, particularly in the fields of deep learning and IoT. Her technical proficiency is complemented by her ability to design and implement innovative solutions to complex problems in the computing and technology landscape.

Publication Top Noted:

Title: Blockchain based an efficient and secure privacy preserved framework for smart cities

  • Authors: A. Padma, M. Ramaiah
  • Journal: IEEE Access
  • Citations: 19
  • Year: 2024

Title: A review of security vulnerabilities in industry 4.0 applications and the possible solutions using blockchain

  • Authors: M. Ramaiah, V. Chithanuru, A. Padma, V. Ravi
  • Book: Cyber Security Applications for Industry 4.0
  • Pages: 63-95
  • Citations: 17
  • Year: 2022

Title: Detecting security breaches on smart contracts through techniques and tools: A brief review – Applications and challenges

  • Authors: A. Padma, R. Mangayarkarasi
  • Conference: International Conference on Information and Management Engineering
  • Pages: 361-369
  • Citations: 12
  • Year: 2022

Title: GLSBIoT: GWO-based enhancement for lightweight scalable blockchain for IoT with trust-based consensus

  • Authors: A. Padma, M. Ramaiah
  • Journal: Future Generation Computer Systems
  • Volume: 159
  • Pages: 64-76
  • Citations: 8
  • Year: 2024

Title: 4 A Technologies Study on Trending for IoT Use Cases Aspires to Build Sustainable Smart Cities

  • Authors: M. Ramaiah, R. M. Yousuf, R. Vishnukumar, A. Padma
  • Book: Intelligent Systems and Sustainable Computational Models: Concepts
  • Citations: 1
  • Year: 2024

Title: Exploring Explainable AI in Healthcare: Challenges and Future Directions

  • Authors: A. Padma, V. Chithanuru, P. Uppamma, R. Vishnukumar
  • Book: Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry
  • Pages: 199-233
  • Citations: 1
  • Year: 2024

Title: A Survey on importance of English skills for Academics and future growth of scholars

  • Author: A. Padma
  • Source: Retrieved March 3, 2022
  • Citations: 1
  • Year: 2021

Title: Blockchain for Agriculture Technology Supply Chain Management

  • Authors: A. Padma, M. Ramaiah, V. Ravi
  • Book: Intelligent Computing and Optimization for Sustainable Development
  • Year: 2024

Title: Intelligent Connected Vehicle Intrusion Detection and Mitigation: An Analysis of Explainable AI

  • Authors: R. Vishnukumar, A. Padma, M. Ramaiah
  • Conference: 2024 International Conference on Emerging Techniques in Computational …
  • Year: 2024

Title: A hybrid wrapper technique enabled Network Intrusion Detection System for Software-defined networking based IoT networks

  • Authors: M. Ramaiah, A. Padma, R. Vishnukumar, M. Y. Rahamathulla, V. Chithanuru
  • Conference: 2024 3rd International Conference on Artificial Intelligence for Internet of …
  • Year: 2024

Conclusion:

Given her extensive research output, contributions to academia, active involvement in the scientific community, and notable awards, Ms. Adla Padma is a deserving candidate for the Women Researcher Award. Her research not only furthers the understanding of complex technologies but also strives to make them more secure and applicable to real-world challenges, particularly in IoT and smart cities.

Arif Ali | Detection and Prevention | Excellence in Innovation

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Mr. Arif Ali | Detection and Prevention | Excellence in Innovation

Lecuturer at Cadet College Karak, Pakistan, Pakistan

Mr. Arif Ali is a plant scientist with a strong background in molecular genetics, agronomy, and stress physiology. He is currently engaged in research at Hainan University, China, collaborating on projects related to safflower germplasm and lentil genetic markers. Mr. Ali holds a Master’s degree in Plant Sciences from Quaid-i-Azam University, Islamabad, Pakistan, and a Bachelor’s degree in Botany from Islamia College University, Peshawar, Pakistan. With expertise in genome-wide association studies, high-throughput genomic sequencing, and plant stress responses, he has contributed to several publications and research projects aimed at improving crop resilience and agricultural sustainability. Additionally, he has held teaching positions as Head of the Biology Departments at various educational institutions in Pakistan.

Profile:

Education:

Mr. Arif Ali holds a Master’s degree in Plant Sciences from Quaid-i-Azam University, Islamabad, Pakistan, where he completed his thesis on the molecular characterization of the TIN-1 gene locus in winter bread wheat, with a CGPA of 3.77/5. Prior to this, he earned a Bachelor of Science degree in Botany from Islamia College University, Peshawar, Pakistan, graduating with a CGPA of 3.56/4. His academic journey has been marked by a strong focus on plant genetics, molecular biology, and stress physiology, equipping him with a solid foundation to contribute significantly to the field of plant science through research and innovation.

Professional Experience:

Mr. Arif Ali has extensive professional experience in both research and academia. Currently, he is involved in a research collaboration at Hainan University, China, where he is working on projects focused on genome-wide association studies of safflower germplasm and the identification of genetic markers in lentils. His previous research at Quaid-i-Azam University, Islamabad, included a master’s project on the molecular characterization of the TIN-1 gene in winter bread wheat, utilizing advanced techniques such as high-throughput genomic sequencing and RNA-seq. Mr. Ali has also worked as a research fellow in various plant physiology and genetics projects, with a particular focus on plant stress responses, including sodium chloride stress in rice. In addition to his research, he has held significant academic leadership roles, including Head of the Biology Department at Cadet Colleges in Khyber Pakhtunkhwa and Punjab, Pakistan, and as a Visiting Lecturer at Islamia College University, Peshawar. His combined research expertise and academic leadership have significantly contributed to advancing plant sciences in his field.

Research Interests:

Mr. Arif Ali’s research interests primarily focus on plant breeding, genetics, and stress physiology. His work is particularly centered around the molecular characterization of agronomic traits, including the identification and validation of genetic markers associated with key traits in crops such as safflower and lentils. He is also interested in understanding the genetic mechanisms underlying plant responses to environmental stresses, including nitrogen use efficiency, sodium chloride, and copper chloride stress. His research incorporates advanced genomic techniques such as genome-wide association studies (GWAS), RNA sequencing (RNA-seq), real-time quantitative PCR (RT-qPCR), and comparative genomics. Additionally, Mr. Ali is exploring the integration of bioinformatics tools for gene expression analysis and protein-protein interaction studies to further advance plant stress tolerance breeding under changing environmental conditions.

Awards and Honors:

Mr. Arif Ali has been recognized for his academic and research excellence through several awards and honors. He has contributed significantly to the field of plant sciences, particularly in the areas of plant breeding and molecular genetics. His work has been published in high-impact journals such as Functional Plant Biology and Heliyon, underscoring the value of his research in advancing agricultural science. Mr. Ali has also been acknowledged for his contributions to the study of stress tolerance in plants, with his research on safflower and lentils receiving attention in both local and international academic circles. His active participation in conferences and his ability to present cutting-edge research at prestigious events further highlight his recognition within the scientific community.

Skills:

Mr. Arif Ali possesses a diverse set of technical and soft skills that complement his research in plant sciences. He has hands-on experience with advanced software and tools, including Microsoft Office, Statistix, XLSTAT, R software, and various bioinformatics platforms for genomic analysis. His proficiency in using tools such as STRUCTURE, TASSEL with Mixed Linear Models, BLAST, and STRING allows him to analyze population structure, marker-trait associations, and perform protein-protein interaction analyses. Mr. Ali is skilled in molecular biology techniques, including high-throughput DNA sequencing, RNA-seq, real-time quantitative PCR (RT-qPCR), and controlled greenhouse experiments. Additionally, he has a strong command of English and Urdu, enabling effective communication and collaboration in diverse research settings. His ability to conduct detailed phenotypic and biochemical evaluations, along with his expertise in various plant stress treatments, further enhances his capacity for contributing to cutting-edge agricultural research.

Publication Top Noted:

Title: Assessment of comparative effects of sodium chloride stress on various growth parameters in different varieties of rice (Oryza sativa L.)

  • Authors: S. Wali, I. Ahmad, F. Tariq, A. Ali, S.I.U. Haq
  • Journal: Pure and Applied Biology
  • Volume: 6, Issue 2, Page: 707
  • Cited by: 2
  • Year: 2017

Title: Barley a nutritional powerhouse for gut health and chronic disease defense

  • Authors: A. Ali, Z. Ullah, R. Ullah, M. Kazi
  • Journal: Heliyon
  • Volume: 10, Issue 20
  • Cited by: 1
  • Year: 2024

Title: Omics-Driven Strategies for Developing Saline-Smart Lentils: A Comprehensive Review

  • Authors: Fawad Ali, Yiren Zhao, Arif Ali, Muhammad Waseem, Mian A. R.
  • Journal: International Journal of Molecular Sciences
  • Volume: 21, Issue 25
  • Year: 2024

Title: Genome-wide association studies identify genetic loci related to fatty acid and branched-chain amino acid metabolism and histone modifications under varying nitrogen

  • Authors: F. Ali, M.A.R. Arif, A. Ali, M.A. Nadeem, E. Aksoy, A. Bakhsh, S.U. Khan, C. Kurt
  • Journal: Functional Plant Biology
  • Volume: 51, Issue 5
  • Year: 2024

Title: Effect of Different Hosts on the Biology of Trybliographa Daci (Hymenoptera Braconidae) Under Lab Conditions

  • Authors: F.A. Soomro, N.K. Bugti, A. Ali, S.A.H. Shah, S.U. Baloch, S.K. Baloch, Z. Ullah

Conclusion:

Mr. Arif Ali’s research contributions, academic leadership, and technical expertise position him as an excellent candidate for the Research for Excellence in Innovation award, reflecting his commitment to advancing plant science and sustainable agriculture.

Vahid Jahangiri | Machin Learning | Best Researcher Award

Posted on by ScienceFather

Assist. Prof. Dr. Vahid Jahangiri | Machin Learning | Best Researcher Award

Assistant Professor at University of Mohaghegh Ardabili, Iran

Assist. Prof. Dr. Vahid Jahangiri is an Assistant Professor at the University of Mohaghegh Ardabili, Iran, specializing in Civil (Earthquake) Engineering. He holds a Ph.D. in Earthquake Engineering from Tarbiat Modares University (2016), an M.Sc. from Sharif University of Technology (2009), and a B.A. in Civil Engineering from the University of Tabriz (2007). Dr. Jahangiri has extensive teaching experience in areas such as seismic design, risk assessment, structural dynamics, and earthquake engineering. Additionally, he worked as a Civil Engineer Consultant at Arte Tarrahan (2011-2014). His research focuses on seismic risk assessment, structural resilience, and earthquake-induced infrastructure damage, with key publications in prestigious journals such as the Bulletin of Earthquake Engineering and Structures. Dr. Jahangiri’s work has made significant contributions to the safety of infrastructure under seismic events, particularly in buried pipelines and structural collapse scenarios.

Profile:

Education:

Assist. Prof. Dr. Vahid Jahangiri has a strong academic foundation in civil and earthquake engineering. He completed his Ph.D. in Civil (Earthquake) Engineering at Tarbiat Modares University, Tehran, Iran, in 2016. Prior to this, he earned his M.Sc. in Civil (Earthquake) Engineering from Sharif University of Technology in 2009 and his B.A. in Civil Engineering from the University of Tabriz in 2007. His academic journey underscores his dedication to mastering seismic engineering, equipping him with advanced expertise to contribute significantly to the field.

Professional Experience:

Dr. Jahangiri’s career includes valuable consulting experience and a robust academic role. Between 2011 and 2014, he worked as a Civil Engineer Consultant at Arte Tarrahan in Tehran, where he applied engineering knowledge to practical projects. In 2018, he joined the Faculty of Engineering at the University of Mohaghegh Ardabili as an Assistant Professor. Here, he teaches various specialized courses to M.Sc. and Ph.D. students, including Performance-Based Seismic Design and Dynamics of Structures, and fundamental subjects like Mechanics of Materials to undergraduate students, blending theory with practical application.

Research Interests:

Assist. Prof. Dr. Vahid Jahangiri’s research interests primarily lie in the fields of earthquake engineering, seismic risk assessment, and structural resilience. His work focuses on evaluating and enhancing the seismic performance of critical infrastructure, including buried pipelines and bridges. Dr. Jahangiri is particularly interested in the development of performance-based seismic design methods, fragility analysis, and the dynamic behavior of structures under earthquake loading. He has conducted extensive research on the seismic response of buried steel pipelines and the impact of seismic wave propagation on gas pipeline networks. Additionally, his research extends to the assessment of progressive collapse in buildings, with a particular focus on fire-induced damage. His work aims to improve the safety and reliability of structures in seismically active regions, contributing to the development of more resilient infrastructure systems. Through his research, Dr. Jahangiri strives to bridge the gap between theoretical models and practical applications in earthquake engineering.

Skills:

Assist. Prof. Dr. Vahid Jahangiri possesses a diverse set of skills in earthquake engineering, structural dynamics, and seismic risk assessment. He is proficient in advanced seismic analysis techniques, including performance-based seismic design, fragility analysis, and the evaluation of structural responses to seismic events. Dr. Jahangiri has expertise in modeling the dynamic behavior of structures, particularly in the context of buried infrastructure such as pipelines and bridges, using both numerical and experimental methods. He is skilled in the application of various intensity measures to assess the seismic response of infrastructure systems. His experience also includes the development and application of engineering tools for evaluating the resilience of buildings under extreme events like earthquakes and fires. Additionally, Dr. Jahangiri is highly knowledgeable in soil-structure interaction and the dynamics of soil during seismic activity. His teaching and consulting roles have further honed his abilities in conveying complex engineering concepts and providing practical solutions to real-world challenges in earthquake engineering. These skills, combined with his strong research capabilities, make him a leading expert in his field.

Publication Top Noted:

  • Title: Intensity measures for the assessment of the seismic response of buried steel pipelines
    • Authors: H. Shakib, V. Jahangiri
    • Journal: Bulletin of Earthquake Engineering
    • Pages: 1265-1284
    • Cited by: 53
    • Year: 2016
  • Title: Seismic risk assessment of buried steel gas pipelines under seismic wave propagation based on fragility analysis
    • Authors: V. Jahangiri, H. Shakib
    • Journal: Bulletin of Earthquake Engineering
    • Pages: 1571-1605
    • Cited by: 50
    • Year: 2018
  • Title: Evaluation of Plasco Building fire-induced progressive collapse
    • Authors: H. Shakib, M. Zakersalehi, V. Jahangiri, R. Zamanian
    • Journal: Structures
    • Pages: 205-224
    • Cited by: 38
    • Year: 2020
  • Title: Intensity measures for the seismic response assessment of plain concrete arch bridges
    • Authors: V. Jahangiri, M. Yazdani, M.S. Marefat
    • Journal: Bulletin of Earthquake Engineering
    • Pages: 4225-4248
    • Cited by: 38
    • Year: 2018
  • Title: Seismic performance assessment of plain concrete arch bridges under near-field earthquakes using incremental dynamic analysis
    • Authors: M. Yazdani, V. Jahangiri, M.S. Marefat
    • Journal: Engineering Failure Analysis
    • Page: 104170
    • Cited by: 37
    • Year: 2019
  • Title: Seismic reliability and limit state risk evaluation of plain concrete arch bridges
    • Authors: V. Jahangiri, M. Yazdani
    • Journal: Structure and Infrastructure Engineering
    • Volume: 17, Issue 2, Pages: 170-190
    • Cited by: 32
    • Year: 2021
  • Title: Appropriate intensity measures for probabilistic seismic demand estimation of steel diagrid systems
    • Authors: M. Heshmati, V. Jahangiri
    • Journal: Engineering Structures
    • Page: 113260
    • Cited by: 14
    • Year: 2021
  • Title: Intensity measure-based probabilistic seismic evaluation and vulnerability assessment of ageing bridges
    • Authors: M. Yazdani, V. Jahangiri
    • Journal: Earthquakes and Structures
    • Volume: 19, Issue 5, Pages: 379-393
    • Cited by: 13
    • Year: 2020

Conclusion:

Dr. Jahangiri’s extensive research, combined with his teaching and practical experience, makes him an outstanding choice for the Best Researcher Award, underscoring his commitment to advancing seismic safety and structural engineering.