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.

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

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

Xing LI | Cybersecurity Risk | Best Researcher Award

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Assoc Prof Dr. Xing LI | Cybersecurity Risk | Best Researcher Award

Associate Professor at Xi’an Jiaotong University, China

Associate Professor Dr. Xing Li appears to be a suitable candidate for the Best Researcher Award based on several key considerations:

Profile:

Research Contributions:

Diverse Research Topics: Dr. Xing Li has made significant contributions to various fields within accounting and finance, with a particular focus on cybersecurity risk management and corporate governance. His research addresses critical issues such as the impact of managerial myopia on cybersecurity, employee education levels on corporate investment efficiency, and the relationship between corporate social responsibility and financial fraud.

High-Impact Publications: Dr. Li has an impressive record of publications in highly regarded journals such as the Journal of Banking & Finance, Journal of Accounting Literature, Contemporary Accounting Research, Journal of Business Ethics, and Accounting & Finance. His work has garnered recognition, including a Top Cited Article Award, indicating its impact and relevance in the academic community.

Collaborative Efforts: Many of Dr. Li’s research projects are collaborative, involving co-authors from different institutions. This collaborative approach is essential for producing high-quality, multidisciplinary research that addresses complex issues in innovative ways.

Teaching Excellence:

Outstanding Teaching Evaluations: Dr. Li has received exceptionally high student evaluation scores, including a 99.77 in 2023, and has been awarded the Outstanding Teaching Award at Xi’an Jiaotong University. His commitment to teaching excellence enhances his profile as a well-rounded academic.

Course Development: He has developed and taught courses such as Audit and Assurance (ACCA) and Empirical Accounting Research, contributing to the academic development of both undergraduate and master students.

Professional Recognition and Awards:

Awards and Honors: Dr. Li has received several prestigious awards, including the Shaanxi Provincial Higher School Science and Technology Achievement Award (Grand Prize) and the Outstanding Research Thesis Award at City University of Hong Kong. These accolades highlight his contributions to both research and teaching.

Research Funding: He has secured significant research funding from reputable sources such as the National Natural Science Foundation of China and the China Postdoctoral Science Foundation, underscoring his ability to attract support for his research initiatives.

Contributions to Academic Literature:

Monographs and Textbooks: Dr. Li has contributed as Deputy Editor-in-Chief to influential textbooks like “Blockchain Theory and Practice” and “Advanced Financial Management: Theory and Practice.” These contributions reflect his role in shaping academic literature and providing valuable resources for students and professionals.

Reviewer Roles and Professional Activities:

Editorial and Reviewer Roles: Dr. Li serves as a reviewer for several reputable journals, including the Journal of Business Ethics and the International Journal of Financial and Economics. His involvement in these roles demonstrates his commitment to maintaining high standards in academic publishing.

Conclusion:

Based on his extensive research contributions, outstanding teaching record, significant awards and honors, and active involvement in the academic community, Associate Professor Dr. Xing Li is indeed a strong candidate for the Best Researcher Award. His work not only advances academic knowledge but also addresses practical issues in cybersecurity risk management and corporate governance, making a substantial impact on the field.

Publication Tob Noted:

The Impact of Managerial Myopia on Cybersecurity: Evidence from Data Breaches

  • Authors: Chen, W., Li, X., Wu, H., Zhang, L.
  • Journal: Journal of Banking and Finance
  • Volume: 166
  • Article: 107254
  • Year: 2024
  • Citations: 0

Asymmetric Inefficiency in the Market Response to Non-earnings 8-K Information

  • Authors: Li, X., Tan, Q.
  • Journal: Contemporary Accounting Research
  • Volume: 39, Issue: 2
  • Pages: 1389–1424
  • Year: 2022
  • Citations: 1

MD&A Readability, Auditor Characteristics, and Audit Fees

  • Authors: Wang, L., Chen, X., Li, X., Tian, G.
  • Journal: Accounting and Finance
  • Volume: 61, Issue: 4
  • Pages: 5025–5050
  • Year: 2021
  • Citations: 14

Corporate Social Responsibility and Financial Fraud: The Moderating Effects of Governance and Religiosity

  • Authors: Li, X., Kim, J.-B., Wu, H., Yu, Y.
  • Journal: Journal of Business Ethics
  • Volume: 170, Issue: 3
  • Pages: 557–576
  • Year: 2021
  • Citations: 26

Employee Quality and Audit Fee: Evidence from China

  • Authors: Li, X., Chen, X., Qi, B., Tian, G.
  • Journal: Accounting and Finance
  • Volume: 60, Issue: 5
  • Pages: 4533–4566
  • Year: 2020
  • Citations: 26

 

Sharmila Ghosh | Hiding and Steganography | Best Researcher Award

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Ms. Sharmila Ghosh | Hiding and Steganography | Best Researcher Award 

Student at National Institute of Technology Agartala, India

Summary:

Sharmila Ghosh is a dedicated cyber security professional from Agartala, Tripura, India. She holds a BTech in Information Technology and is currently pursuing an MTech in Cyber Security. Her academic background includes extensive knowledge in Cryptography, Steganography, Ethical Hacking, and Web Development. Sharmila has demonstrated her technical skills through innovative projects such as Image Steganography using Histogram Shifting and Personalized Music Recommendation Systems. Her research interests focus on enhancing data security through chaos theory-based cryptographic algorithms and advanced image security techniques. She has earned several accolades, including multiple prizes in electronic design and national competitions. Sharmila’s commitment to advancing cyber security is evident in her published research and diverse skill set in programming and web development.

Profile:

Education:

Sharmila Ghosh is currently pursuing a Master of Technology (MTech) in Cyber Security at the National Institute Technology Agartala, Tripura, with expected completion in 2024. Prior to this, she earned her Bachelor of Technology (BTech) in Information Technology from Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, where she achieved a CGPA of 8.62. During her undergraduate studies, she gained extensive knowledge in various areas including Cryptography, Steganography, Ethical Hacking, Data Structures, Algorithms, and Computer Networks. Sharmila completed her Higher Secondary education under the CBSE board at Sri Krishna Mission School, Agartala, with a percentage of 65.4%. She also completed her Secondary Examination under CBSE at the same school with a CGPA of 9.0. Her educational background reflects a strong foundation in both theoretical and practical aspects of cyber security and technology.

Professional Experience:

Sharmila Ghosh’s professional experience includes various roles and projects that have honed her skills in cyber security and technology. During her BTech studies, she implemented a cutting-edge Image Steganography project using Histogram Shifting combined with Huffman Encoding and AES Encryption for enhanced data security. She also developed a Personalized Music Recommendation System utilizing Deep Neural Network techniques, aiming to provide a tailored listening experience. Additionally, Sharmila worked on a Semantic Similarity Computation project using Cosine LSTM to analyze textual elements. Her hands-on projects and coursework have provided her with practical experience in ethical hacking, cryptography, web development, and programming, making her well-prepared for challenges in the cyber security field.

Research Interests:

Sharmila Ghosh’s research interests are centered around advancing the field of cyber security through innovative techniques and applications. Her focus includes Cryptography and Steganography, where she explores methods to enhance data security, particularly in medical imaging and digital watermarking. She is also interested in Chaos Theory-based Cryptographic Algorithms, which she investigates to improve cryptographic systems. Her research extends to Social Media Network Security, where she studies attacks and prevention measures. Additionally, Sharmila is engaged in Image Security analysis, employing chaos theory to enhance the robustness of image steganography. Her work aims to integrate and improve security measures using advanced methodologies, contributing to the broader cyber security landscape.

 Skills:

Sharmila Ghosh possesses a diverse skill set essential for a career in cyber security and technology. She is proficient in Cyber Security, with expertise in Ethical Hacking, Cryptography, and Steganography. Her programming skills include Python and C language, which she uses for various security-related applications and development tasks. In Web Development, Sharmila is skilled in HTML and CSS, contributing to her ability to create and secure web interfaces. She has a strong foundation in Data Structures and Algorithms, enhancing her problem-solving capabilities. Additionally, Sharmila has experience with Advanced Steganography Techniques, such as Histogram Shifting and Huffman Encoding, and is adept at using Deep Neural Networks for personalized systems. Her ability to integrate Cryptography with Steganography for enhanced data security reflects her innovative approach and strong analytical skills.

 Awards and Honors:

Sharmila Ghosh has received several awards and honors reflecting her academic and extracurricular achievements. She was awarded the Second Prize in a School-level scholarship competition in October 2023 and the Third Prize in an Enterprise Scholarship in June 2023. She was recognized as an Outstanding Student Cadre and an Outstanding Communist Party Member in September and June 2023, respectively. During her BTech, she earned the Second Prize in the Central University Graduate Electronic Design Competition in August 2022. She also achieved the Third Prize in the National Intelligent Car Competition South China Race in August 2021 and the Second Prize in the Hunan Electronic Design Competition in June 2021. These accolades highlight her excellence in both academic pursuits and competitive projects.

Publication Top Noted:

  1. “A Comparative Analysis of Chaos Theory-Based Medical Image Steganography to Enhance Data Security”
    Authors: Sharmila Ghosh, Ananya Saha, Tanmoy Pal, Arvind Kumar Jha
    Year: 2024
    Journal: Procedia Computer Science, 235, pp. 1024–1033
  2. “An Analysis of Chaos-Based Cryptographic Algorithms”
    Authors: Sharmila Ghosh, Pritam Pal, Nirmal Kar
    Year: 2023
    Conference: 5th International Conference on Electrical, Computer and Communication Technologies (ICECCT 2023)
  3. “Attacks on Social Media Networks and Prevention Measures”
    Authors: Pritam Pal, Sharmila Ghosh, Nirmal Kar
    Year: 2023
    Conference: International Conference for Advancement in Technology (ICONAT 2023)