Joseph Forson | Public Sector | Best Researcher Award

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Dr. Joseph Forson | Public Sector | Best Researcher Award

Senior Lecturer atUNIVERSITY OF EDUCATION, WINNEBA, Ghana

Dr. Joseph Forson is a distinguished academic and consultant specializing in development finance and policy management. He currently serves as a lecturer at the University of Education, Winneba (UEW), Ghana, where he has been instrumental in shaping the curriculum and guiding students in various finance and policy courses since 2018. In addition to his teaching responsibilities, Dr. Forson holds several key positions, including Patron of the UEW Association of Business Students and Senior Finance & Policy Consultant at Dataking Consulting Firm in Accra. He has a rich background in higher education administration, having served as Vice-Dean and Graduate Coordinator at UEW, and has been actively involved in editorial roles for academic journals. Dr. Forson earned his Ph.D. in Development Administration from the National Institute of Development Administration (NIDA) in Bangkok, Thailand, and his research interests include the economics of corruption, public policy, and transportation planning. With numerous publications in peer-reviewed journals, he is dedicated to advancing knowledge in his field and fostering a sustainable development agenda.

Profile:

Education:

Dr. Joseph Forson holds a Ph.D. in Development Administration (Policy and Management), which he obtained in 2016 from the National Institute of Development Administration (NIDA) in Bangkok, Thailand. He also earned a Master of Economics (Applied Finance) from Xiamen University in China in 2011. His academic journey began with a Bachelor of Science degree in Development Planning (Policy) from Kwame Nkrumah University of Science and Technology (KNUST) in Kumasi, Ghana, where he graduated in 2007. To enhance his teaching skills, he completed a Postgraduate Diploma in Teaching and Learning in Higher Education at the University of Education, Winneba, Ghana, in 2019. Additionally, he has a certificate in Project Planning and Structuring, acquired from the Project Management Bureau of the City of Amsterdam and Metro Planning Unit in Accra, Ghana, in 2005. This comprehensive educational background equips Dr. Forson with a robust foundation in development studies and economics, significantly contributing to his expertise in finance and policy management.

Professional Experience:

Dr. Joseph Forson has an extensive professional background in academia and consultancy, contributing significantly to the fields of finance and policy management. He currently serves as a lecturer at the University of Education, Winneba (UEW), Ghana, where he has been a pivotal figure since 2018, teaching various finance and policy courses at the postgraduate and undergraduate levels. Dr. Forson has also held key administrative roles, including Vice-Dean and Graduate Coordinator, enhancing the academic experience and governance within the School of Business at UEW. His consultancy work as a Senior Finance & Policy Consultant at Dataking Consulting Firm has allowed him to apply his expertise in real-world scenarios. In addition, he has been an active member of editorial teams for several academic journals, furthering research dissemination in his areas of interest. His prior experience includes roles such as Ag. Head of Department at UEW and a Research Fellow at the Graduate School of Public Administration (NIDA) in Thailand, showcasing his commitment to education and research excellence.

Research Interests:

Dr. Joseph Forson’s research interests encompass a diverse range of topics within the fields of development finance and public policy. He is particularly focused on the interplay between economic factors and governance, exploring the economics of corruption and its implications for development outcomes. His work delves into the intricacies of public policy and management, emphasizing strategies that enhance efficiency and accountability in governance. Additionally, Dr. Forson has a keen interest in transportation planning, investigating how effective transport policies can drive economic growth and sustainability. Through his research, he aims to contribute to the discourse on development strategies that promote equitable economic progress and enhance public sector performance.

Skills:

Dr. Joseph Forson possesses a robust set of skills that complement his extensive academic and professional background. As a Senior Finance and Policy Consultant, he has honed his analytical abilities, particularly in evaluating financial strategies and their impact on public policy. His experience in academia as a lecturer and course module editor has equipped him with strong communication skills, enabling him to convey complex concepts effectively to diverse audiences. Dr. Forson is adept in research methodologies, with expertise in quantitative and qualitative analysis, which allows him to conduct rigorous investigations into development finance and public policy issues. Additionally, his leadership roles, including Vice-Dean and Graduate Coordinator, showcase his ability to manage teams and drive collaborative efforts in educational settings. His editorial experience further underscores his commitment to advancing knowledge in his field through peer-reviewed publications.

Conclusion:

Dr. Joseph Forson exemplifies the qualities of an outstanding researcher through his extensive academic background, diverse research interests, and leadership roles in academia and consultancy. His commitment to advancing knowledge in finance and public policy, along with his impactful publications, make him a worthy candidate for the Research for Best Researcher Award.

Publication Top Noted:

  • Employee Motivation and Job Performance: A Study of Basic School Teachers in Ghana
    • Authors: JA Forson, E Ofosu-Dwamena, RA Opoku, SE Adjavon
    • Journal: Future Business Journal
    • Volume: 7 (30), Pages 1-22
    • Cited by: 146
    • Year: 2021
  • Selected Macroeconomic Variables and Stock Market Movements: Empirical Evidence from Thailand
    • Authors: JA Forson, J Janrattanagul
    • Journal: Contemporary Economics
    • Volume: 8 (2), Pages 154-174
    • Cited by: 105
    • Year: 2014
  • Genuine Wealth Per Capita as a Measure of Sustainability and the Negative Impact of Corruption on Sustainable Growth in Sub-Sahara Africa
    • Authors: JA Forson, P Buracom, G Chen, TY Baah-Ennumh
    • Journal: South African Journal of Economics
    • Volume: 85 (2), Pages 178–195
    • Cited by: 65
    • Year: 2017
  • Impact of Income Diversification Strategy on Credit Risk and Market Risk Among Microfinance Institutions
    • Authors: KCT Duho, DM Duho, JA Forson
    • Journal: Journal of Economic and Administrative Sciences
    • Volume: 39 (2), Pages 523-546
    • Cited by: 45
    • Year: 2023
  • Corruption, EU Aid Inflows and Economic Growth in Ghana: Cointegration and Causality Analysis
    • Authors: JA Forson, P Buracom, TY Baah-Ennumh, G Chen, E Carsamer
    • Journal: Contemporary Economics
    • Volume: 9 (3), Pages 299-318
    • Cited by: 43
    • Year: 2015
  • Causes of Corruption: Evidence from Sub-Saharan Africa
    • Authors: JA Forson, TY Baah-Ennumh, P Buracom, G Chen, Z Peng
    • Journal: South African Journal of Economic and Management Sciences
    • Volume: 19 (4), Pages 562-578
    • Cited by: 42
    • Year: 2016
  • Peer Effects in R&D Investment Policy: Evidence from China
    • Authors: Z Peng, Y Lian, JA Forson
    • Journal: International Journal of Finance and Economics
    • Volume: 26 (3), Pages 4516-4533
    • Cited by: 39
    • Year: 2021
  • The Impact of Artisanal Small-Scale Mining on Sustainable Livelihoods: A Case Study of Mining Communities in the Tarkwa-Nsuaem Municipality of Ghana
    • Authors: TY Baah-Ennumh, JA Forson
    • Journal: World Journal of Entrepreneurship, Management and Sustainable Development
    • Cited by: 35
    • Year: 2017
  • Innovation Financing and Public Policy Dilemmas in the Economic Community of West African States (ECOWAS)
    • Authors: JA Forson
    • Journal: African Journal of Science, Technology, Innovation and Development
    • Volume: 12 (1), Pages 1-11
    • Cited by: 34
    • Year: 2020

Boquan Li | Cyber Threat | Best Researcher Award

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Dr. Boquan Li | Cyber Threat | Best Researcher Award

Assistant Professor at College of Computer Science and Technology, Harbin Engineering University, China

Dr. Boquan Li is a Tenure Track Associate Professor at the College of Computer Science and Technology, Harbin Engineering University, where he has served since January 2024. Prior to this, he was a Research Scientist at the School of Computing and Information Systems, Singapore Management University, from April 2022 to December 2023. Dr. Li holds a Ph.D. in Information Engineering from the University of Chinese Academy of Sciences and a Bachelor of Engineering from Harbin Engineering University. His research interests focus on artificial intelligence, cybersecurity, deepfake detection, and speaker recognition, with numerous publications in leading international conferences and journals. Dr. Li is also an active peer reviewer for prestigious journals like IEEE Transactions on Software Engineering.

Profile:

Education:

Dr. Boquan Li holds a Doctor of Philosophy (Ph.D.) from the University of Chinese Academy of Sciences, where he specialized in Information Engineering at the Institute of Information Engineering. He completed his Ph.D. in January 2022, building a strong foundation in artificial intelligence, cybersecurity, and data science. Prior to his doctoral studies, Dr. Li earned a Bachelor of Engineering degree from the School of Software at Harbin Engineering University in June 2016. His comprehensive academic background has equipped him with expertise in cutting-edge technologies, enabling him to contribute significantly to research in AI and cybersecurity.

Professional Experience:

Dr. Boquan Li has a diverse professional background in both academia and research. Since January 2024, he has been serving as a Tenure Track Associate Professor at the College of Computer Science and Technology, Harbin Engineering University, where he contributes to teaching and research in artificial intelligence and cybersecurity. Prior to this role, Dr. Li worked as a Research Scientist at the School of Computing and Information Systems, Singapore Management University, from April 2022 to December 2023. In this capacity, he was involved in cutting-edge research on deepfake detection, speaker recognition, and digital forensics. His professional experience highlights his expertise in developing innovative solutions to cybersecurity challenges and advancing research in AI-driven technologies.

Research Interests:

Dr. Boquan Li’s research interests focus on cutting-edge areas of artificial intelligence, cybersecurity, and multimedia forensics. He is particularly interested in deepfake detection, where he explores the vulnerabilities and robustness of detection systems across various domains. His work also covers speaker recognition, digital forensics, and adversarial attacks, aiming to develop defense mechanisms against cyber threats. Additionally, Dr. Li has a strong interest in cross-modal fusion techniques, particularly in audio-visual speech recognition, and domain adaptation methods for enhancing the accuracy of AI models across diverse datasets. His research contributes to advancing secure and reliable AI systems.

Skills:

Dr. Boquan Li possesses a diverse skill set that encompasses advanced computational techniques and a robust understanding of artificial intelligence and machine learning algorithms. He is proficient in developing and implementing deep learning models, particularly for applications in image and audio processing. His expertise extends to cybersecurity measures, with a focus on identifying vulnerabilities in AI systems and creating effective defense strategies against adversarial attacks. Additionally, Dr. Li is skilled in data analysis and statistical methods, enabling him to interpret complex datasets and derive meaningful insights. His strong programming skills in languages such as Python and proficiency with machine learning frameworks like TensorFlow and PyTorch further enhance his research capabilities in the field of computer science and technology.

Conclusion:

Dr. Boquan Li’s research addresses critical issues in AI security, deepfake detection, and adversarial defenses, areas of increasing importance in today’s technological landscape. His innovative work, combined with his academic and research experience, positions him as a strong candidate for the Best Researcher Award. His contributions have practical applications in cybersecurity and AI ethics, demonstrating both academic excellence and real-world impact.

Publication Top Noted:

  • How Generalizable are Deepfake Image Detectors? An Empirical Study
  • Two-stage Semi-supervised Speaker Recognition with Gated Label Learning
    • Authors: Xingmei Wang, Jiaxiang Meng, Kong Aik Lee, Boquan Li, Jinghan Liu
    • Year: 2024
    • Conference: International Joint Conference on Artificial Intelligence
    • Type: Conference paper
  • Assessing Backdoor Risk in Deepfake Detectors
    • Authors: Jiawen Wang, Boquan Li, Min Yu, Kam-Pui Chow, Jianguo Jiang, Fuqiang Du, Xiang Meng, Weiqing Huang
    • Year: 2024
    • Conference: IFIP WG 11.9 International Conference on Digital Forensics
    • Type: Conference paper
  • CATNet: Cross-Modal Fusion for Audio–Visual Speech Recognition
    • Authors: Xingmei Wang, Jiachen Mi, Boquan Li, Yixu Zhao, Jiaxiang Meng
    • Year: 2024
    • Journal: Pattern Recognition Letters
    • DOI: 10.1016/j.patrec.2024.01.002
  • A Residual Fingerprint-Based Defense Against Adversarial Deepfakes
  • FakeFilter: A Cross-Distribution Deepfake Detection System with Domain Adaptation
    • Authors: Jianguo Jiang, Boquan Li, Baole Wei, Gang Li, Chao Liu, Weiqing Huang, Meimei Li, Min Yu
    • Year: 2021
    • Journal: Journal of Computer Security
    • DOI: 10.3233/jcs-200124
  • Restoration as a Defense Against Adversarial Perturbations for Spam Image Detection
    • Authors: Jianguo Jiang, Boquan Li, Min Yu, Chao Liu, Weiqing Huang, Lejun Fan, Jianfeng Xia
    • Year: 2019
    • Conference: International Conference on Artificial Neural Networks
    • DOI: 10.1007/978-3-030-30508-6_56

Yikai Zhang | Digital Economy | Best Researcher Award

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Mr. Yikai Zhang | Digital Economy | Best Researcher Award

Student at ShenzheNanyang Technological University, China

Mr. Yikai Zhang is a dedicated researcher and scholar currently pursuing a Master of Science in Knowledge Management at Nanyang Technological University, Singapore. He holds a Bachelor of Management in Human Resource Management from Nankai University, China, where he graduated with a strong academic record. Mr. Zhang’s research interests lie at the intersection of knowledge management and human resource strategies, with a particular focus on knowledge sharing, remote work dynamics, and corporate governance. He has contributed to several high-impact publications, including papers on the digital economy and team collaboration. In addition to his academic achievements, he has gained valuable professional experience through internships at JD.com and Anyang Iron & Steel Group, where he applied his skills in operations and human resource management. His expertise in these areas, combined with his research experience, positions him as a promising talent in his field.

Profile:

Education:

Mr. Yikai Zhang is currently pursuing a Master of Science in Knowledge Management at Nanyang Technological University, Singapore, from August 2023 to January 2025. His studies focus on essential areas such as Knowledge Management Technology, Foundations of Knowledge Management, Knowledge Management Strategies and Policies, and Organizational Leadership. Prior to this, he earned a Bachelor of Management in Human Resource Management from Nankai University, Tianjin, China, where he graduated in June 2023 with an impressive GPA of 87.37/100. His undergraduate coursework included key subjects like Human Resource Management, Organizational Behavior, Labor Economics, Strategic Management, and Probability and Statistics. This solid academic background has equipped him with a comprehensive understanding of both knowledge management and human resource management, positioning him well for further success in these fields.

Professional Experience:

Mr. Yikai Zhang has accumulated valuable professional experience through internships that have enhanced his practical skills in both operations and human resource management. In 2022, he worked as an Operations Department intern at Jingdong (JD.com), where he analyzed procurement processes for small and medium-sized enterprises and developed strategic operational solutions. He also conducted market research on competitive products and assisted in implementing brand promotion plans. Additionally, in 2021, he interned in the Labor and Human Resource Department at Anyang Iron & Steel Group Co., Ltd., where he was involved in skills training for workshop managers, analyzing training outcomes, and drafting training reports. His hands-on experience in both corporate environments has provided him with a well-rounded understanding of operational efficiency and workforce management, complementing his academic background in human resource and knowledge management.

Research Interests:

Mr. Yikai Zhang’s research interests are centered around the fields of knowledge management, human resource management, and organizational behavior. He is particularly focused on exploring knowledge sharing and knowledge hiding behaviors within remote work environments, examining how social presence and electronic monitoring influence these dynamics. Additionally, he is interested in team collaboration, especially in diverse teams, where he investigates the role of leadership and team reflection in overcoming knowledge sharing barriers. His research also extends to corporate governance, analyzing issues related to board governance, ESG, and stakeholder management. Mr. Zhang is passionate about understanding the impact of digital transformations on organizational strategies, labor control, and employee behavior, making his research highly relevant to modern workplace challenges.

Skills:

Mr. Yikai Zhang possesses a strong set of skills that complement his academic and research background. He is proficient in various IT tools, including MS Office, SPSS, and Mplus, which he uses for data analysis and research purposes. His language skills are demonstrated by an IELTS score of 7.0 and a GRE score of 333, highlighting his excellent command of English in both verbal and written communication. These technical and analytical skills, combined with his language proficiency, enable him to effectively conduct research, analyze data, and present his findings in both academic and professional settings.

Conclusion:

Mr. Yikai Zhang’s strong academic foundation, impactful research contributions, and practical experience make him a highly deserving candidate for the Research for Best Researcher Award. His work spans critical areas such as knowledge management, human resource strategies, and corporate governance, positioning him as a promising researcher with potential for significant future contributions to these fields.

 

Shoujun Zhou | Digital Signatures | Best Scholar Award

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Prof. Shoujun Zhou | Digital Signatures | Best Scholar Award

Research professor at Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China

Prof. Shoujun Zhou is a distinguished researcher at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, and a double researcher at the National High Performance Medical Device Research Institute. He received his Ph.D. in Biomedical Engineering from Southern Medical University in 2004. With extensive experience in interventional surgical robotics and medical imaging, Prof. Zhou has led numerous significant research projects, including four National Natural Science Foundation projects and a major instrument project. He has been recognized for his contributions to science and technology, receiving awards such as the first prize for Science and Technology Progress from the Ministry of Education and the Silver Award at the Global Medical Robot Innovation Design Competition. A prolific author, he has published over 100 scientific papers and holds more than 60 patents. Prof. Zhou is also actively involved in various professional committees and organizations related to medical technology and innovation.

Profile:

Education:

Prof. Shoujun Zhou obtained his Ph.D. in Biomedical Engineering from Southern Medical University in July 2004. Prior to that, he earned his Master’s degree in Communication and Information Systems from Lanzhou University in July 2000. His academic journey began with a Bachelor’s degree in Test and Control, which he completed at the Air Force Engineering University in July 1993. This strong educational foundation has equipped him with a deep understanding of biomedical engineering, communication systems, and control technologies, paving the way for his distinguished research career.

Professional Experience:

Prof. Shoujun Zhou has had a distinguished career in biomedical engineering and medical device research. Since October 2010, he has served as a Distinguished Researcher at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, where he focuses on interventional surgical robotics and image-guided therapy. Prior to this role, he worked as a Senior Engineer in the Information Department of the 458th Hospital of the People’s Liberation Army from May 2008 to August 2010. He also completed a postdoctoral fellowship at the School of Information Engineering, Beijing Institute of Technology, from August 2004 to March 2007. Additionally, he held a postdoctoral position at Shenzhen Haibo Technology Co., Ltd., from May 2007 to August 2008 and served as an engineer in the PLA 94921 Unit from July 1993 to August 2001. Throughout his career, Prof. Zhou has contributed to numerous high-impact research projects, demonstrating his expertise in advanced medical technologies.

Research Interests:

Prof. Shoujun Zhou specializes in the fields of interventional surgical robotics and medical imaging. His primary research interests include the development of advanced image-guided therapy techniques, focusing on improving the precision and effectiveness of surgical interventions. He is particularly dedicated to the design and application of intelligent interventional robotic systems, integrating artificial intelligence to enhance decision-making and operational efficiency in surgical procedures. Additionally, Prof. Zhou explores medical image processing methodologies, aiming to innovate techniques that optimize the visualization and analysis of complex medical data. His work significantly contributes to the advancement of minimally invasive surgical approaches and the integration of robotics in healthcare.

Skills:

Prof. Shoujun Zhou possesses a robust skill set in biomedical engineering, specializing in interventional surgical robotics and medical imaging. He has expertise in designing and implementing advanced robotic systems for surgical applications, with a focus on image-guided therapy. Prof. Zhou is proficient in artificial intelligence algorithms and their integration into medical devices, enhancing surgical precision and patient outcomes. His technical skills include medical image processing, algorithm development, and system optimization, complemented by a strong background in project management and leadership. Additionally, he is experienced in conducting multidisciplinary research, collaborating with healthcare professionals and engineers to drive innovations in medical technology.

Conclusion:

Prof. Shoujun Zhou’s extensive research background, numerous awards, and significant contributions to the fields of surgical robotics and medical imaging make him an exceptional candidate for the Research for Best Scholar Award. His work not only advances technology in medicine but also improves patient outcomes through innovative solutions. His leadership in various high-impact projects and dedication to research excellence underscore his suitability for this prestigious recognition.

Publication Top Noted:

  • Verdiff-Net: A Conditional Diffusion Framework for Spinal Medical Image Segmentation
    • Journal: Bioengineering
    • Publication Date: 2024-10-15
    • DOI: 10.3390/bioengineering11101031
    • Contributors: Zhiqing Zhang, Tianyong Liu, Guojia Fan, Yao Pu, Bin Li, Xingyu Chen, Qianjin Feng, Shoujun Zhou
  • Automatic Delineation of the 3D Left Atrium From LGE-MRI: Actor-Critic Based Detection and Semi-Supervised Segmentation
    • Journal: IEEE Journal of Biomedical and Health Informatics
    • Publication Date: 2024-06
    • DOI: 10.1109/JBHI.2024.3373127
    • Contributors: Shun Xiang, Nana Li, Yuanquan Wang, Shoujun Zhou, Jin Wei, Shuo Li
  • SBCNet: Scale and Boundary Context Attention Dual-Branch Network for Liver Tumor Segmentation
    • Journal: IEEE Journal of Biomedical and Health Informatics
    • Publication Date: 2024-05
    • DOI: 10.1109/JBHI.2024.3370864
    • Contributors: Kai-Ni Wang, Sheng-Xiao Li, Zhenyu Bu, Fu-Xing Zhao, Guang-Quan Zhou, Shou-Jun Zhou, Yang Chen
  • SC-SSL: Self-Correcting Collaborative and Contrastive Co-Training Model for Semi-Supervised Medical Image Segmentation
    • Journal: IEEE Transactions on Medical Imaging
    • Publication Date: 2024-04
    • DOI: 10.1109/TMI.2023.3336534
    • Contributors: Juzheng Miao, Si-Ping Zhou, Guang-Quan Zhou, Kai-Ni Wang, Meng Yang, Shoujun Zhou, Yang Chen
  • A Fast Actuated Soft Gripper Based on Shape Memory Alloy Wires
    • Journal: Smart Materials and Structures
    • Publication Date: 2024-04-01
    • DOI: 10.1088/1361-665X/ad2f0c
    • Contributors: Xiaozheng Li, Yongxian Ma, Chuang Wu, Youzhan Wang, Shoujun Zhou, Xing Gao, Chongjing Cao
  • An Adaptive Control Method and Learning Strategy for Ultrasound-Guided Puncture Robot
    • Journal: Electronics
    • Publication Date: 2024-01-31
    • DOI: 10.3390/electronics13030580
    • Contributors: Tao Li, Quan Zeng, Jinbiao Li, Cheng Qian, Hanmei Yu, Jian Lu, Yi Zhang, Shoujun Zhou
  • A Precise Calibration Method for the Robot-Assisted Percutaneous Puncture System
    • Journal: Electronics
    • Publication Date: 2023-12-01
    • DOI: 10.3390/electronics12234857
    • Contributors: Jinbiao Li, Minghui Li, Quan Zeng, Cheng Qian, Tao Li, Shoujun Zhou
  • Online Hard Patch Mining Using Shape Models and Bandit Algorithm for Multi-Organ Segmentation
    • Journal: IEEE Journal of Biomedical and Health Informatics
    • Publication Date: 2022-06
    • DOI: 10.1109/JBHI.2021.3136597
    • Contributors: Jianan He, Guangquan Zhou, Shoujun Zhou, Yang Chen
  • To Align Multimodal Lumbar Spine Images via Bending Energy Constrained Normalized Mutual Information
    • Journal: BioMed Research International
    • Publication Date: 2020-07-11
    • DOI: 10.1155/2020/5615371
    • Contributors: Shibin Wu, Pin He, Shaode Yu, Shoujun Zhou, Jun Xia, Yaoqin Xie
  • Cerebrovascular Segmentation from TOF-MRA Using Model- and Data-Driven Method via Sparse Labels
    • Journal: Neurocomputing
    • Publication Date: 2020-03
    • DOI: 10.1016/j.neucom.2019.10.092
    • Contributors: Baochang Zhang, Shuting Liu, Shoujun Zhou, Jian Yang, Cheng Wang, Na Li, Zonghan Wu, Jun Xia

Ammar Alsheghri | Artificial Intelligence | Best Researcher Award

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Assist Prof Dr. Ammar Alsheghri | Artificial Intelligence | Best Researcher Award

Assistant Professor at king fahd university of petroleum and minerals, Saudi Arabia

Assist. Prof. Dr. Ammar Alsheghri is a distinguished academic and researcher specializing in materials and mechanical engineering. He currently serves as an Assistant Professor in the Department of Mechanical Engineering at King Fahd University of Petroleum and Minerals (KFUPM) in Dhahran, Saudi Arabia. Dr. Alsheghri earned his Ph.D. in Materials Engineering from McGill University, Canada, in 2020, following his Master’s in Mechanical Engineering from Khalifa University in collaboration with MIT, and a Bachelor’s degree from Khalifa University, UAE. His research spans bioinspired materials design, geometric deep learning, and the optimization of materials for prosthetics and medical applications. He has extensive experience in academia and industry, contributing to innovative projects and holding patents in dental restoration technologies. Dr. Alsheghri’s work is highly recognized through numerous fellowships, scholarships, and awards for research excellence.

Profile:

Education:

Assist. Prof. Dr. Ammar Alsheghri holds a Ph.D. in Materials Engineering from McGill University, Canada, which he completed in May 2020 with a perfect GPA of 4.0/4.0. During his Ph.D., he was awarded the prestigious Graduate Excellence Fellowship. He earned his Master of Science in Mechanical Engineering from the Masdar Institute of Science and Technology, Khalifa University, UAE, in collaboration with the Massachusetts Institute of Technology (MIT), USA, in May 2015, also achieving a GPA of 4.0/4.0. Dr. Alsheghri obtained his Bachelor of Science in Mechanical Engineering from Khalifa University, UAE, in June 2013, graduating with the highest honors and an impressive GPA of 3.98/4.0.

Professional Experience:

Assist. Prof. Dr. Ammar Alsheghri has an extensive professional background in both academia and industry. Currently, he is an Assistant Professor in the Department of Mechanical Engineering at King Fahd University of Petroleum and Minerals (KFUPM) in Dhahran, Saudi Arabia, a position he has held since August 2023. Prior to this, he served as a Postdoctoral Fellow at Polytechnique Montreal from 2020 to 2022, where he worked on geometric deep learning for dental applications, collaborating with industrial partners to develop customized dental crowns. Dr. Alsheghri also contributed as a Research Assistant at McGill University from 2015 to 2020, where his thesis focused on bioinspired design and optimization of materials for dentures and cellular structures. He has previous experience as a Research Assistant at Masdar Institute of Khalifa University, working on self-healing materials using finite element analysis. In addition to his academic roles, Dr. Alsheghri has substantial industrial experience. He was a Technology Developer at Dragonfly, part of the Comet Group, from 2022 to 2023, focusing on AI-driven scientific imaging and software development. He also worked as a Research & Development Consultant and Intern at Dragonfly, leading projects involving artificial intelligence for material image processing and mechanical properties analysis. His industry roles also include an internship at Diehl Aircabin GmbH in Germany, where he performed stress analysis for the Airbus A380 ceiling and assisted with composite material testing.

Research Interests:

Assist. Prof. Dr. Ammar Alsheghri’s research interests are deeply rooted in the intersection of materials engineering, mechanical engineering, and cutting-edge technologies such as artificial intelligence. His work focuses on bioinspired design and optimization of materials, particularly for dental applications, including the development of dentures and customized prosthetic structures. Dr. Alsheghri is also highly engaged in the field of geometric deep learning, specifically 3D deep learning for applications in dental segmentation and the generation of dental crowns from scanned dental arches. His expertise extends to self-healing materials, mechanics modeling, and finite element analysis (FEA), which he has applied to enhance the structural properties of materials. Additionally, he is interested in AI-driven image processing and computational mechanics, applying these techniques to scientific imaging and material analysis, with the aim of optimizing mechanical properties and structures for various engineering applications.

Skills:

Assist. Prof. Dr. Ammar Alsheghri possesses a diverse and advanced skill set that spans both academia and industry. He is highly proficient in materials engineering, with expertise in bioinspired design and optimization of materials, specifically for dental and prosthetic applications. Dr. Alsheghri excels in finite element analysis (FEA) and computational mechanics, which he has applied to projects involving self-healing materials and lightweight structures. He is also skilled in computer-aided design (CAD) and 3D modeling, having worked on the design and development of dental prostheses and optimized cellular structures. In addition, Dr. Alsheghri has strong capabilities in artificial intelligence, particularly in geometric deep learning and 3D deep learning, which he has applied to the segmentation of dental structures and the design of customized dental crowns. He is experienced in data analysis, image processing, and the use of AI for scientific imaging. His skills in laboratory testing and materials characterization complement his technical expertise, allowing him to contribute to multidisciplinary research and development efforts.

Conclusion:

With an outstanding academic record, a strong research portfolio, multiple patents, and a track record of successful collaborations in both academia and industry, Dr. Ammar Alsheghri stands out as a highly qualified candidate for the Best Researcher Award. His interdisciplinary expertise, particularly in materials engineering, AI, and bioinspired design, positions him as a leader in advancing research and technology in both mechanical and biomedical engineering fields.

Publication Top Noted:

  • Removable partial denture alloys processed by laser‐sintering technique
    • Authors: O Alageel, MN Abdallah, A Alsheghri, J Song, E Caron, F Tamimi
    • Journal: Journal of Biomedical Materials Research Part B: Applied Biomaterials
    • Volume/Issue: 106(3)
    • Pages: 1174-1185
    • Year: 2018
    • DOI: 10.1002/jbm.b.33910
  • Design and cost analysis of a solar photovoltaic powered reverse osmosis plant for Masdar Institute
    • Authors: A Alsheghri, SA Sharief, S Rabbani, NZ Aitzhan
    • Journal: Energy Procedia
    • Volume: 75
    • Pages: 319-324
    • Year: 2015
    • DOI: 10.1016/j.egypro.2015.07.439
  • Finite element implementation and application of a cohesive zone damage-healing model for self-healing materials
    • Authors: AA Alsheghri, RKA Al-Rub
    • Journal: Engineering Fracture Mechanics
    • Volume: 163
    • Pages: 1-22
    • Year: 2016
    • DOI: 10.1016/j.engfracmech.2016.05.020
  • High strength brushite bioceramics obtained by selective regulation of crystal growth with chiral biomolecules
    • Authors: H Moussa, W Jiang, A Alsheghri, A Mansour, A El Hadad, H Pan, R Tang, …
    • Journal: Acta Biomaterialia
    • Volume: 106
    • Pages: 351-359
    • Year: 2020
    • DOI: 10.1016/j.actbio.2020.01.004
  • Composition and characteristics of trabecular bone in osteoporosis and osteoarthritis
    • Authors: I Tamimi, ARG Cortes, JM Sánchez-Siles, JL Ackerman, …
    • Journal: Bone
    • Volume: 140
    • Pages: 115558
    • Year: 2020
    • DOI: 10.1016/j.bone.2020.115558
  • Thermodynamic-based cohesive zone healing model for self-healing materials
    • Authors: AA Alsheghri, RKA Al-Rub
    • Journal: Mechanics Research Communications
    • Volume: 70
    • Pages: 102-113
    • Year: 2015
    • DOI: 10.1016/j.mechrescom.2015.09.007
  • Determining the retention of removable partial dentures
    • Authors: O Alageel, AA Alsheghri, S Algezani, E Caron, F Tamimi
    • Journal: Journal of Prosthetic Dentistry

Kiran Ravulakollu | Machine Learning | Best Researcher Award

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Prof Dr. Kiran Ravulakollu | Machine Learning | Best Researcher Award

Dean at Woxsen University, India.

Prof. Dr. Kiran Ravulakollu is currently the Dean and Professor at the School of Technology at Woxsen University, Kamkole, Telangana, where he has played a pivotal role in establishing the school since 2021. He also serves as the Director of Research and Development at the same institution. With a strong academic background, Dr. Ravulakollu holds a Ph.D. in Computer Science from the University of Sunderland, UK, and has extensive teaching and research experience in areas such as artificial intelligence, image processing, and hybrid intelligent systems. Throughout his career, he has held various academic positions, including Assistant Dean of Research at the University of Petroleum and Energy Studies and has been instrumental in developing research ecosystems that foster collaboration and innovation. His contributions to the field are evident in his impressive publication record, with over 879 publications and numerous patents. An active participant in research advisory committees and academic councils, Dr. Ravulakollu is dedicated to advancing technology and education through strategic leadership and innovative research initiatives.

Profile:

Education:

Prof. Dr. Kiran Ravulakollu has a solid academic foundation, beginning with a Bachelor’s degree in Computer Science and Engineering from Jawaharlal Nehru Technological University, Hyderabad, India, awarded in 2004. He further advanced his expertise by earning a Postgraduate Certificate in Artificial Intelligence from City, University of London, United Kingdom, in 2006. Dr. Ravulakollu’s academic journey culminated in a Ph.D. in Computer Science from the University of Sunderland, United Kingdom, in 2012. His Ph.D. research focused on developing a computational architecture inspired by the Superior Colliculus of the mid-brain, utilizing neural networks for the efficient integration of audio and visual stimuli. Additionally, he completed a Post-Graduate Certificate in Academic Practices from the University of Petroleum and Energy Studies, Dehradun, India, in 2019, further enhancing his teaching and research credentials.

Professional Experience:

Prof. Dr. Kiran Ravulakollu has an extensive professional experience in academia and research, currently serving as the Dean and Professor at the School of Technology at Woxsen University, Kamkole, Telangana, since August 2021. In this role, he successfully established the school, significantly increasing student enrollment from 31 to 1,500, faculty and staff from 2 to 75, and generating revenue of ₹80 lakhs. He has also served as the Director of Research and Development at Woxsen University since August 2022, where he developed a robust R&D ecosystem, resulting in a remarkable rise in publications from 10 to 879, citations from 428 to over 7,400, and the acquisition of 36 patents. Prior to his current roles, Dr. Ravulakollu held various positions at the University of Petroleum and Energy Studies, Dehradun, including Assistant Dean of Research and Senior Associate Professor. His academic journey began as an Assistant Professor at Sharda University, where he contributed to curriculum development and student mentoring. His research background includes a tenure as a Research Associate at the HIS Research Group at the University of Sunderland, UK, where he focused on sensory data integration for artificial agents. Throughout his career, Dr. Ravulakollu has demonstrated exceptional leadership, strategic thinking, and a commitment to fostering research excellence in technology and engineering.

Research Interests:

Prof. Dr. Kiran Ravulakollu’s research interests lie at the intersection of artificial intelligence, computer science, and intelligent systems. His Ph.D. research focused on creating computational architectures inspired by the mid-brain’s Superior Colliculus, utilizing artificial neural networks to integrate audio and visual stimuli for enhanced localization capabilities. This foundational work has propelled his ongoing investigations into various advanced topics, including image processing methodologies, artificial agents, ambient intelligence, and hybrid intelligent systems. Additionally, Dr. Ravulakollu is keenly interested in the Internet of Things (IoT) and its applications, exploring how interconnected devices can contribute to smarter solutions in urban environments. His dedication to innovation is reflected in his ability to translate complex theoretical concepts into practical applications, fostering knowledge transfer that shapes products and enhances research outcomes. Overall, his diverse research portfolio showcases a commitment to pushing the boundaries of technology and developing cutting-edge solutions for real-world challenges.

Skills:

Prof. Dr. Kiran Ravulakollu possesses a robust skill set that encompasses analytical expertise, strong research methodologies, and innovative development capabilities. His analytical skills enable him to design and implement significant projects, effectively identifying problems and conducting feasibility studies to ensure research viability. With a solid foundation in project management, he excels at coordinating research and development activities, fostering collaboration among diverse teams. Dr. Ravulakollu is adept at data analysis, utilizing advanced techniques to derive meaningful insights and inform decision-making processes. His proficiency in knowledge transfer allows him to bridge the gap between theoretical research and practical application, shaping products that meet industry demands. Additionally, his experience in developing policies and frameworks for effective administration reflects his strategic thinking ability and commitment to continuous improvement within academic and research environments. Overall, Dr. Ravulakollu’s diverse skill set positions him as a leader in his field, driving impactful research initiatives and fostering innovation.

Conclusion:

Prof. Dr. Kiran Ravulakollu’s exceptional track record in academia, research, and administration make him a highly suitable candidate for the Best Researcher Award. His ability to blend innovative research with practical applications, along with his leadership in establishing a robust R&D environment, highlights his suitability for this prestigious recognition. His career demonstrates a consistent commitment to advancing knowledge and technology in the fields of artificial intelligence, machine learning, and hybrid intelligent systems, positioning him as a leader in contemporary research.

Publication Top Noted:

SIGN LANGUAGE RECOGNITION: STATE OF THE ART

  • Authors: AK Sahoo, GS Mishra, KK Ravulakollu
  • Year: 2013
  • Cited by: 105

Improving automated latent fingerprint detection and segmentation using deep convolutional neural network

  • Authors: M Chhabra, KK Ravulakollu, M Kumar, A Sharma, A Nayyar
  • Journal: Neural Computing and Applications
  • Year: 2023
  • Cited by: 33

Naïve Bayes Classifier with LU Factorization for Recognition of Handwritten Odia Numerals

  • Authors: KKR, Pradeepta K. Sarangi, P. Ahmed
  • Journal: Indian Journal of Science and Technology
  • Year: 2014
  • Cited by: 32

HANDWRITTEN DEVNAGARI DIGIT RECOGNITION: BENCHMARKING ON NEW DATASET

  • Authors: R Kumar, KK Ravulakollu
  • Journal: Journal of Theoretical & Applied Information Technology
  • Year: 2014
  • Cited by: 27

A Hybrid Intrusion Detection System: Integrating Hybrid Feature Selection Approach with Heterogeneous Ensemble of Intelligent Classifiers

  • Authors: KKR, Amrita
  • Journal: International Journal of Network Security
  • Year: 2018
  • Cited by: 25

Fuzzy-membership based writer identification from handwritten devnagari script

  • Authors: R Kumar, KK Ravulakollu, R Bhat
  • Journal: Journal of Information Processing Systems
  • Year: 2017
  • Cited by: 23

Indian sign language recognition using skin color detection

  • Authors: AK Sahoo, KK Ravulakollu
  • Journal: International Journal of Applied Engineering Research
  • Year: 2014
  • Cited by: 19

VISION BASED INDIAN SIGN LANGUAGE CHARACTER RECOGNITION

  • Authors: AK Sahoo, KK Ravulakollu
  • Journal: Journal of Theoretical & Applied Information Technology
  • Year: 2014
  • Cited by: 18

A review on artificial intelligence in orthopaedics

  • Authors: T Hamid, M Chhabra, K Ravulakollu, P Singh, S Dalal, R Dewan
  • Conference: 2022 9th International Conference on Computing for Sustainable Global Development
  • Year: 2022
  • Cited by: 17

WORD BASED STATISTICAL MACHINE TRANSLATION FROM ENGLISH TEXT TO INDIAN SIGN LANGUAGE

  • Authors: GS Mishra, AK Sahoo, KK Ravulakollu
  • Journal: ARPN Journal of Engineering & Applied Sciences
  • Year: 2017
  • Cited by: 17

State-of-the-Art: A Systematic Literature Review of Image Segmentation in Latent Fingerprint Forensics

  • Authors: KKR, Megha Chhabra, Manoj Kumar Shukla
  • Journal: Recent Patents on Computer Science
  • Year: 2019
  • Cited by: 16

Surface Corrosion Grade Classification using Convolution Neural Network

  • Authors: KKR, Sanjay Kumar Ahuja, Manoj Kumar Shukla
  • Journal: International Journal of Recent Technology and Engineering
  • Year: 2019
  • Cited by: 15

Abraham Ogofure | Biotechnology | Excellence in Research

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Dr. Abraham Ogofure | Biotechnology | Excellence in Research

Biotechnology at University of Johannesburg, South Africa.

Dr. Abraham Ogofure is a microbiologist specializing in plant-microbiome interactions, bioenergy, molecular microbiology, and public health. He holds a Ph.D. in Plant Pathogenic Microbiology from the University of Benin, Nigeria, where his research focused on biological control of bacterial soft rot in tomatoes. With expertise in microbial analysis, DNA extraction, and bioinformatics, Dr. Ogofure’s work spans key areas such as food security, sustainable fertilizer production, and antibiotic resistance. Currently a Lecturer II at the University of Benin, he has co-supervised several research projects and mentored students, making significant contributions to both academia and applied research. He is also a member of professional bodies like the American Society for Microbiology (ASM) and Nigerian Society for Microbiology (NSM).

Profile:

Education:

Dr. Abraham Ogofure holds a Ph.D. in Plant Pathogenic Microbiology from the University of Benin, Benin City, Nigeria, which he completed in 2021. His doctoral thesis, titled “In vitro and In Planta Biological Control Efficacy of Bacillus subtilis against Bacterial Soft Rot Disease of Tomato (Lycopersicum esculentum L.),” involved advanced microbiological research focused on biocontrol methods for agricultural pathogens. Prior to his Ph.D., Dr. Ogofure earned an M.Sc. in Plant Pathogenic Microbiology from the same institution in 2016, graduating with an outstanding CGPA of 4.8/5.0. His master’s research investigated the antibacterial, phytochemical, and proximate properties of plantain (Musa paradisiaca). He began his academic journey with a B.Sc. in Microbiology from the University of Benin in 2010, achieving a CGPA of 3.75/5.0. His undergraduate project examined the antimicrobial activity of crab shell extract on Escherichia coli strains, showcasing his early interest in microbial research. Throughout his education, Dr. Ogofure gained practical experience in various microbiological techniques, including bacterial isolation, DNA extraction, and bioinformatics, which have significantly contributed to his expertise in the field.

Professional Experience:

Dr. Abraham Ogofure has a robust professional background in both academia and research. He is currently a Lecturer II at the University of Benin, where he has been teaching since 2012. His experience includes supervising undergraduate and postgraduate research projects, conducting microbiological analyses, and co-supervising master’s and doctoral research. Dr. Ogofure has also contributed to the Recirculate Project, a collaboration between Lancaster University and CSIR, where he worked on microbiological assays and data management. Additionally, he has volunteered as a science teacher and served on university committees, demonstrating his commitment to education and research development.

Research Interests:

Dr. Abraham Ogofure’s research interests span a wide range of critical topics in microbiology and public health. He is particularly focused on plant-microbiome interactions and the role of beneficial and pathogenic bacteria in promoting plant growth and impacting public health. His work on bioenergy and the production of sustainable fertilizers aims to support agricultural sustainability, while his research on food security and safety explores biological control of pathogens to protect crops and human health. Dr. Ogofure is also deeply involved in molecular microbiology, particularly in understanding antibiotic resistance mechanisms and developing novel antimicrobial agents using nanotechnology. Additionally, he has a strong interest in data management and visualization, particularly in the context of public health. His interdisciplinary approach combines microbiology, molecular techniques, and bioinformatics to address key challenges in agriculture, health, and the environment.

Skills:

Dr. Abraham Ogofure possesses a diverse set of skills rooted in microbiology, molecular biology, and data analysis. He is proficient in microbial isolation and cultivation techniques, DNA extraction, and polymerase chain reaction (PCR), along with bioinformatics tools such as Mega 10 and Bioedit for sequence analysis. His practical expertise extends to biocontrol methods, antibacterial susceptibility testing, and pathogenicity testing, with a strong background in the use of Bacillus subtilis for biological control of plant diseases. Dr. Ogofure is also skilled in data management and statistical analysis, utilizing software such as SPSS, Excel, and R-programming for data curation and visualization. Additionally, his knowledge of nanotechnology for the development of novel antimicrobial agents and his experience in supervising research projects further enhance his research and academic capabilities. His multidisciplinary skill set enables him to contribute to both scientific research and public health initiatives.

Conclusion:

Dr. Abraham Ogofure’s extensive research background, academic achievements, and commitment to education make him an exemplary candidate for the Excellence in Research Award. His contributions to microbiology and public health significantly advance our understanding of critical issues, positioning him as a leader in the field.

Publication Top Noted:

  • Detection of methicillin-resistant staphylococci isolated from food producing animals: A public health implication
    • Authors: EO Igbinosa, A Beshiru, LU Akporehe, AG Ogofure
    • Journal: Veterinary Sciences
    • Year: 2016
    • Cited by: 55
  • Multi-antibiotic resistant and putative virulence gene signatures in Enterococcus species isolated from pig farms environment
    • Authors: A Beshiru, IH Igbinosa, FI Omeje, AG Ogofure, MM Eyong, EO Igbinosa
    • Journal: Microbial Pathogenesis
    • Year: 2017
    • Cited by: 32
  • Prevalence and Characterization of Food-Borne Vibrio parahaemolyticus From African Salad in Southern Nigeria
    • Authors: EO Igbinosa, A Beshiru, IH Igbinosa, AG Ogofure, KE Uwhuba
    • Journal: Frontiers in Microbiology
    • Year: 2021
    • Cited by: 27
  • Assessment of fungal pathogens associated with orange spoilage
    • Authors: FE Oviasogie, AG Ogofure, A Beshiru, JN Ode, FI Omeje
    • Journal: African Journal of Microbiology Research
    • Year: 2015
    • Cited by: 26
  • Physico-chemical and microbiological profile of bacterial and fungal isolates of Ikpoba River in Benin City: Public health implications
    • Authors: OA Ologbosere, HSA Aluyi, AG Ogofure, A Beshiru, FI Omeje
    • Journal: African Journal of Environmental Science and Technology
    • Year: 2016
    • Cited by: 22
  • Anaerobic co-digestion of cattle rumen content and food waste for biogas production: Establishment of co-digestion ratios and kinetic studies
    • Authors: NA Ihoeghian, AN Amenaghawon, MU Ajieh, CE Oshoma, A Ogofure
    • Journal: Bioresource Technology Reports
    • Year: 2022
    • Cited by: 21
  • Prevalence, multiple antibiotic resistance and virulence profile of methicillin-resistant Staphylococcus aureus (MRSA) in retail poultry meat from Edo, Nigeria
    • Authors: EO Igbinosa, A Beshiru, IH Igbinosa, AG Ogofure, TC Ekundayo, AI Okoh
    • Journal: Frontiers in Cellular and Infection Microbiology
    • Year: 2023
    • Cited by: 19

Muthukrishnan A | Neural Network | Best Researcher Award

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Dr. Muthukrishnan A | Neural Network | Best Researcher Award

Associate Professor at Vel Tech Rangarajan Dr Sagunthala R and D Institute of Science and Technology, India.

Dr. A. Muthukrishnan is an accomplished Associate Professor in the Department of Electronics and Communication Engineering at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology in Chennai. He earned his Ph.D. in Information and Communication Engineering from Anna University in 2016, following a Master’s degree in VLSI Design in 2009 and a Bachelor’s degree in Electrical and Electronics Engineering in 2005. With a robust academic and professional background, Dr. Muthukrishnan has held various positions, including Research Director at The Silicon Harvest and Visiting Faculty at Anna University. His research interests encompass VLSI Design, Wireless Sensor Networks, and IoT systems, and he has published numerous papers across reputable journals and platforms. A recognized research supervisor, he has guided multiple M.E./M.Tech and B.E./B.Tech projects. Dr. Muthukrishnan is also actively involved in professional development, having conducted various faculty training programs and received several awards, including the Best Achiever Award from Anna University. His dedication to research and education makes him a prominent figure in his field.

Profile:

Education:

Dr. A. Muthukrishnan holds a Ph.D. in Information and Communication Engineering from Anna University, Chennai, awarded in 2016. He also earned a Master’s degree in VLSI Design in 2009 and a Bachelor’s degree in Electrical and Electronics Engineering in 2005, both from institutions affiliated with Anna University. His strong academic foundation demonstrates a commitment to excellence in engineering education.

Professional Experience:

Dr. A. Muthukrishnan has extensive professional experience in academia and industry. Currently, he serves as an Associate Professor in the Department of Electronics and Communication Engineering at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, a position he has held since August 2022. Before this role, he worked as a Research Director at The Silicon Harvest in Madurai from 2020 to 2022 and as an Associate Professor at Sethu Institute of Technology from 2018 to 2020. Additionally, Dr. Muthukrishnan has significant teaching experience as a Visiting Faculty at Anna University, Madurai, from 2011 to 2017, and as an Assistant Professor at Dr. NGP Institute of Technology, Coimbatore, from 2009 to 2011. His early career included a role as a Member of the Technical Staff at Izone Solutions Private Limited in Chennai from 2005 to 2007. Throughout his career, Dr. Muthukrishnan has also contributed to the industry as a Technical Adviser for various companies, leveraging his expertise in VLSI Design, Wireless Sensor Networks, and IoT systems.

Research Interests:

Dr. A. Muthukrishnan’s research interests primarily focus on VLSI Design, Wireless Sensor Networks (WSN), and sensor-interfaced Internet of Things (IoT) applications. He is particularly passionate about developing energy-efficient algorithms and methodologies for data gathering in wireless sensor networks. His ongoing research includes the design of a hybrid data gathering protocol aimed at optimizing accuracy while significantly conserving energy. Additionally, he has explored innovative signal reconstruction techniques and data gathering strategies utilizing graph theory to minimize redundancy. Dr. Muthukrishnan is also engaged in fault modeling and test pattern generation, contributing to advancements in testing VLSI circuits. His work aims to bridge the gap between theoretical research and practical applications, with an emphasis on enhancing the performance and sustainability of modern electronic systems.

Skills:

Dr. A. Muthukrishnan possesses a diverse skill set that encompasses various aspects of information and communication engineering, particularly in VLSI design, wireless sensor networks, and IoT applications. He is adept at developing energy-efficient algorithms and methodologies for data gathering and signal reconstruction, utilizing advanced concepts in graph theory and matrix-based approaches. Dr. Muthukrishnan’s technical expertise extends to fault modeling and test pattern generation for VLSI circuits, where he applies innovative techniques to enhance circuit testing and reliability. Additionally, he has strong project management and research supervision skills, having guided numerous M.E./M.Tech and B.E./B.Tech projects. His active involvement in consultancy projects and collaborations further demonstrates his ability to translate research into practical solutions, making significant contributions to the field of electronics and communication.

Conclusion:

Dr. A. Muthukrishnan’s exceptional academic background, combined with his extensive experience in teaching, research, and industry, makes him a strong candidate for the Best Researcher Award. His innovative research contributions, dedication to student mentorship, and active involvement in professional development showcase his commitment to advancing the fields of VLSI Design and Wireless Sensor Networks.

Publication Top Noted:

  • Deep learning-based energy prediction and tangent search remora optimization-based secure multi-path data communication mechanism in WSN
    • Journal: Network: Computation in Neural Systems
    • Year: 2024
    • DOI: 10.1080/0954898X.2024.2393750
    • WOSUID: WOS:001309984000001
    • Contributors: Athinarayanasamy, M.; Selvakumar, K.; Sivasubbu, V.; Kanakam, M. Mahesh
  • IOT device type identification using magnetized Hopfield neural network with tuna swarm optimization algorithm
    • Journal: Swarm and Evolutionary Computation
    • Year: 2024
    • DOI: 10.1016/J.SWEVO.2024.101653
    • WOSUID: WOS:001309823300001
    • Contributors: Muthukrishnan, A.; Kamalesh, S.
  • A secure quantum technology for smart cities using Travelling Salesman Problem (TSP): Application perspectives
    • Source: Handbook of Research on Quantum Computing for Smart Environments
    • Year: 2023
    • DOI: 10.4018/978-1-6684-6697-1.ch009
    • EID: 2-s2.0-85151874035
    • Contributors: Pavitra, A.R.R.; Lawrence, I.D.; Muthukrishnan, A.
  • Design of Circular Ring Shaped UWB Antenna for BANs and MI Applications
    • Conference: 2023 9th International Conference on Advanced Computing and Communication Systems (ICACCS)
    • Year: 2023
    • DOI: 10.1109/ICACCS57279.2023.10113090
    • EID: 2-s2.0-85159765433
    • Contributors: Premkumar, M.; Muthukrishnan, A.; Ashokkumar, S.R.; Nagakumararaj, S.; Sathesh Raaj, R.; Srinivasan, D.
  • HY-LSTM: A new time series deep learning architecture for estimation of pedestrian time to cross in advanced driver assistance system
    • Journal: Journal of Visual Communication and Image Representation
    • Year: 2023
    • DOI: 10.1016/J.JVCIR.2023.103982
    • WOSUID: WOS:001126041400001
    • Contributors: Veluchamy, S.; Mahesh, K. Michael; Muthukrishnan, R.; Karthi, S.
  • Optimized Dictionary-based Sparse Regression Learning for Health Care Monitoring in IoT-based Context-Aware Architecture
    • Journal: IETE Journal of Research
    • Year: 2023
    • DOI: 10.1080/03772063.2023.2255567
    • WOSUID: WOS:001072165600001
    • Contributors: Kamalesh, S.; Muthukrishnan, A.
  • Internet of image things-discrete wavelet transform and Gabor wavelet transform based image enhancement resolution technique for IoT satellite applications
    • Journal: Cognitive Systems Research
    • Year: 2019
    • DOI: 10.1016/j.cogsys.2018.10.010
    • EID: 2-s2.0-85056850190
    • Part of ISSN: 13890417

DP Sharma Mainali | Material Engineering | Best Researcher Award

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Assist Prof Dr. DP Sharma Mainali | Material Engineering | Best Researcher Award

Research at The Hague University of Applied Sciences, Netherlands.

Assist. Prof. Dr. DP Sharma Mainali is a dedicated educator and researcher with over 27 years of experience in the education sector. Currently, he serves as an Assistant Professor at The Hague University of Applied Sciences and as a Materials Scientist at Delft University of Technology in the Netherlands. A Dutch citizen of Nepali origin, Dr. Mainali is renowned for his commitment to leveraging education as a means of social transformation. His research focuses on materials science, including carbon capture technologies and advanced materials for engineering applications. In addition to his academic pursuits, he is an active human rights activist, passionately addressing global issues and advocating for social justice. Dr. Mainali’s extensive background in engineering and his dedication to education and advocacy make him a prominent figure in both academic and humanitarian circles.

Profile:

Education:

Assist. Prof. Dr. DP Sharma Mainali has a strong academic background in chemical engineering and material science. He earned his degree in Chemical Engineering (ir) from Delft University of Technology in the Netherlands, one of the most prestigious institutions in the field. His education equipped him with advanced knowledge and technical expertise, which he has applied extensively in his research on materials science, particularly in the areas of carbon capture technologies and shape memory alloys. His academic foundation has been instrumental in shaping his contributions to both academia and innovative scientific research.

Professional Experience:

Assist. Prof. Dr. DP Sharma Mainali has extensive professional experience spanning over 27 years in the education and research sectors. Currently, he serves as an Assistant Professor in Chemical Engineering at The Hague University of Applied Sciences, where he is responsible for delivering high-quality education and mentoring students in engineering principles. In parallel, he works as a Materials Scientist at Delft University of Technology, where he engages in cutting-edge research focused on materials science and engineering. His roles at these esteemed institutions have allowed him to contribute significantly to innovative research projects, particularly in carbon capture technologies and advanced materials for engineering applications. Throughout his career, Dr. Mainali has actively participated in various academic and professional initiatives, advocating for the role of education in driving social change and addressing pressing global challenges. His dedication to both teaching and research exemplifies his commitment to advancing knowledge and fostering a positive impact on society.

Research Interests:

Assist. Prof. Dr. DP Sharma Mainali has a diverse range of research interests primarily centered around materials science and engineering. His work focuses on the synthesis and characterization of advanced materials, particularly covalent organic frameworks for carbon capture technologies, aiming to develop sustainable solutions to combat climate change. Additionally, Dr. Mainali is deeply engaged in exploring the microstructural and functional properties of shape memory alloys, investigating how heat treatment can enhance their performance for various engineering applications. His research also extends to the field of renewable energy, where he conducts techno-economic analyses of green hydrogen production and storage, particularly in the context of developing countries like Nepal. Moreover, he is interested in integrating advanced technologies, such as deep learning and the Internet of Things (IoT), into energy management systems to improve efficiency and sustainability. Through his multidisciplinary approach, Dr. Mainali aims to contribute to innovative solutions that address critical challenges in both engineering and environmental sustainability.

Skills:

Assist. Prof. Dr. DP Sharma Mainali possesses a robust skill set that complements his extensive background in materials science and engineering. His technical expertise includes advanced materials synthesis and characterization, particularly in the development of covalent organic frameworks for carbon capture applications. Dr. Mainali is proficient in various research methodologies, allowing him to effectively analyze microstructural and functional properties of materials, such as shape memory alloys. Additionally, he has strong analytical skills, enabling him to conduct comprehensive techno-economic analyses related to renewable energy systems, particularly in green hydrogen production and storage. His knowledge of integrating cutting-edge technologies, including deep learning and the Internet of Things (IoT), into energy management solutions highlights his innovative approach to problem-solving. Furthermore, Dr. Mainali’s experience in teaching and mentoring enhances his communication and leadership abilities, making him a valuable asset in academic and collaborative research environments.

Conclusion:

With his extensive background in materials science, renewable energy, and education, combined with a strong dedication to human rights activism, Assist. Prof. Dr. DP Sharma Mainali stands out as a deserving candidate for the Best Researcher Award. His innovative work in both academic and societal contexts highlights his commitment to driving positive change through research and education.

Publication Top Noted:

  • Synthesis, characterization, and CO₂ uptake of mellitic triimide-based covalent organic frameworks
    • Journal: J. Polym. Sci., Part A: Polym. Chem
    • Volume: 57 (24)
    • Pages: 2373-2377
    • Year: 2019
    • Cited by: 15
    • Contributors: H. Veldhuizen, A. Vasileiadis, M. Wagemaker, T. Mahon, D.P. Mainali, L. Zong, et al.
  • Effect of heat treatment on microstructure and functional properties of additively manufactured NiTi shape memory alloys
    • Journal: Journal of Alloys and Compounds
    • Volume: 967
    • Article Number: 171740
    • Year: 2023
    • Cited by: 13
    • Contributors: J.N. Zhu, W. Zhu, E. Borisov, X. Yao, T. Riemslag, C. Goulas, A. Popovich, et al.
  • Techno-economic analysis of green hydrogen production, storage, and waste heat recovery plant in the context of Nepal
    • Journal: International Journal of Hydrogen Energy
    • Volume: 77
    • Pages: 892-905
    • Year: 2024
    • Cited by: 2
    • Contributors: B. Paneru, A. Paudel, B. Paneru, V. Alexander, D.P. Mainali, S. Karki, S. Karki, et al.
  • Intelligent Energy Management: Remaining Useful Life Prediction and Charging Automation System Comprised of Deep Learning and the Internet of Things
    • Journal: arXiv preprint
    • Year: 2024
    • Cited by: Not yet cited
    • Contributors: B. Paneru, B. Paneru, D.P. Mainali
  • Hydrogen production from surplus hydropower: Techno-economic assessment with alkaline electrolysis in Nepal’s perspective
    • Journal: International Journal of Hydrogen Energy
    • Volume: 74
    • Pages: 89-100
    • Year: 2024
    • Cited by: Not yet cited
    • Contributors: A. Paudel, B. Paneru, D.P. Mainali, S. Karki, Y. Pochareddy, S.R. Shakya, et al.

Mohammad Reza Eesazadeh | Dynamic State Estimation | Best Researcher Award

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Mr. Mohammad Reza Eesazadeh | Dynamic State Estimation | Best Researcher Award

Mohammad Reza Eesazadeh at Sharif university of technology, Iran

Mr. Mohammad Reza Eesazadeh is a Ph.D. candidate in Electrical Engineering – Power at Sharif University of Technology (SUT), Tehran, specializing in synchro design for electric vehicles and machine learning applications in power systems. He holds an M.Sc. in Electrical Engineering from Shahid Beheshti University, where he focused on dynamic state estimation with non-Gaussian noises, and a B.Sc. in Electrical Engineering from University of Mohaghegh Ardabili. His work experience includes roles as an R&D expert and software developer in energy management systems and power system simulations. He has published research in prestigious journals like the IEEE Sensors Journal, and his research interests include power system modeling, wide-area measurement, and electrical machines.

Profile:

Education:

Mr. Eesazadeh is currently pursuing a Ph.D. in Electrical Engineering – Power at Sharif University of Technology (SUT), Tehran, Iran, where he is developing advanced synchro designs for electric vehicles (EVs) and exploring machine learning topics. He previously earned his M.Sc. in Electrical Engineering – Power Systems from Shahid Beheshti University (SBU), Tehran, graduating with a GPA of 16.28. His Bachelor’s degree in Electrical Engineering was obtained from University of Mohaghegh Ardabili, where he focused on fault current limiters. Mr. Eesazadeh has consistently ranked among the top students, including placing 2nd in the National University Entrance Exam for Ph.D. in 2021 and being in the top 3% for M.Sc. entrance exams.

Professional Experience:

Mr. Eesazadeh has diverse work experience as a software developer and R&D expert, particularly in the power systems sector. He has worked with Modje Niroo Company, Tehran, developing advanced state estimation and power flow modules for energy management systems. At the Research and Technology Deputy of SBU, he led a team to develop a power system simulator for Iran’s Electric Transmission Grid, combining MATLAB, C++, and DIgSILENT for real-time data estimation. His early work includes an internship at Ardabil Province Electricity Distribution Company, focusing on power system expansion planning.

Research Interests:

Mr. Mohammad Reza Eesazadeh’s research interests encompass a broad range of topics within electrical engineering, particularly in power systems and advanced technologies. His work focuses on power system modeling and analysis, with a special emphasis on developing dynamic state estimation techniques. He is also deeply engaged in wide-area measurement systems and system identification, applying data analytics and machine learning to enhance these processes. Additionally, Mr. Eesazadeh is interested in the development of electrical machines, especially for electric vehicles, and electromagnetic sensors such as resolvers and synchros. His innovative contributions to these fields are reflected in his research on improving power system operations and advancing sensor technologies.

Skills:

Mr. Mohammad Reza Eesazadeh possesses a diverse set of skills that span technical, analytical, and personal development areas. His technical expertise includes proficiency in specialized software such as MATLAB (Simulink and Script), DIgSILENT, Ansys Electrical, ePLAN, AutoCAD, and LabVIEW, as well as electrical design tools like ETAP and PSIM. He is also adept in programming languages, including C++, Python, C#, and SQL, leveraging these for tasks like power system analysis, state estimation, and data analytics. Additionally, Mr. Eesazadeh is skilled in various instrumentation and engineering design principles, and his experience in developing Energy Management Systems and SCADA modules further highlights his depth in the field. On the personal side, he is an effective communicator with strong teamwork, leadership, and problem-solving abilities, demonstrated through his roles in R&D teams and his supervision of graduate students. His commitment to self-learning and continuous improvement, combined with his ability to prioritize tasks and make informed decisions, further strengthens his professional profile.

Conclusion:

With his strong educational background, significant work experience, advanced technical skills, and impactful research contributions, Mr. Mohammad Reza Eesazadeh presents a compelling case for the Research for Best Researcher Award. His work in power systems, machine learning applications, and energy management systems positions him as a leader in his field.

Publication Top Noted:

  • Developed square-root cubature Kalman filter-based solution for improving power system state estimation with unknown inputs and non-Gaussian noise
    • Journal: Sustainable Energy, Grids and Networks
    • Volume: 40
    • Year: 2024
    • Article Number: 101523
    • Contributors: M.R. Eesazadeh, M.T. Ameli
    • Citations: 0
  • Development of a Multi-Turn Linear Variable Reluctance Resolver with Integrated Ferromagnetic Core
    • Journal: IEEE Sensors Journal
    • Year: 2024
    • Contributors: S.A. Seyed-Bouzari, M. Eesazadeh, F. Tootoonchian, Z. Nasiri-Gheidari
    • Citations: 0
  • Winding Selection for Wound-Rotor Synchro
    • Journal: IEEE Sensors Journal
    • Volume: 24(1)
    • Pages: 215-222
    • Year: 2024
    • Contributors: M.R. Eesazadeh, Z. Nasiri-Gheidari
    • Citations: 0