Sumei Li | Neural Network | Best Researcher Award Posted on 04/10/202404/10/2024 by Best Paper Award Assoc Prof Dr. Sumei Li | Neural Network | Best Researcher Award Associate Professor at Tianjin University, China Summary: Assoc Prof Dr. Sumei Li is a distinguished researcher in the field of communication engineering, with a focus on advancing technologies for image and video processing. With over 37 published papers in prestigious journals and numerous contributions to leading international conferences, Dr. Li is at the forefront of her field. She has also filed 20 invention patents, demonstrating her commitment to innovation and excellence in research. Her collaborations with renowned institutions and experts, such as Wei Xiang, highlight her dedication to fostering interdisciplinary research. Professional Profile: Scopus Profile Orcid Profile 👩🎓Education: Ph.D. in Communication Engineering Nankai University, Tianjin, China 🏢 Professional Experience: Assoc Prof Dr. Sumei Li has been an Associate Professor in the Communication Engineering Department at Tianjin University since 2006. She has successfully chaired a national 863 project, a National Natural Science Foundation project, and a key fund in Tianjin, underscoring her leadership in the field. Her contributions to academia include significant research and innovations in 3D image and video processing, quality evaluation, and stereo image super-resolution reconstruction. Research Interests: Dr. Li’s primary research interests include: 3D image and video processing Quality evaluation Stereo/image super-resolution reconstruction Neural networks Deep learning Author Metrics: Total Published Papers: 37 Citations: 1,791 Patents Published/Under Process: 20 Top Noted Publication: 1. Multi-Scale Visual Perception Based Progressive Feature Interaction Network for Stereo Image Super-Resolution Authors: Liu, A., Li, S., Chang, Y., Hou, Y. Journal: IEEE Transactions on Circuits and Systems for Video Technology Year: 2024 Volume: 34 Issue: 3 Pages: 1615–1626 Citations: 1 2. Bidirectional Feature Aggregation Network for Stereo Image Quality Assessment Considering Parallax Attention-Based Binocular Fusion Authors: Chang, Y., Li, S., Liu, A., Jin, J., Xiang, W. Journal: IEEE Transactions on Broadcasting Year: 2024 Volume: 70 Issue: 1 Pages: 278–289 Citations: 1 3. Coarse-to-Fine Cross-View Interaction Based Accurate Stereo Image Super-Resolution Network Authors: Liu, A., Li, S., Chang, Y., Zhang, W., Hou, Y. Journal: IEEE Transactions on Multimedia Year: 2024 Volume: 26 Pages: 7321–7334 Citations: 2 4. Cross-Resolution Feature Attention Network for Image Super-Resolution Authors: Liu, A., Li, S., Chang, Y. Journal: Visual Computer Year: 2023 Volume: 39 Issue: 9 Pages: 3837–3849 Citations: 3 5. No Reference Stereoscopic Video Quality Assessment Considering Self-Attention and Different Resolution Level Authors: Zhang, X., Li, S. Conference: ACM International Conference Proceeding Series Year: 2023 Pages: 36–41 Conclusion: Assoc Prof Dr. Sumei Li is a highly qualified candidate for the Best Researcher Award, given her extensive publication record, innovative contributions to communication engineering, and leadership in significant research projects. Her dedication to advancing image and video processing technologies, coupled with her emphasis on neural networks and deep learning, showcases her as a pivotal figure in her field. By addressing areas for improvement, such as broadening her research scope and increasing public engagement, Dr. Li can further amplify her impact on both academia and industry. Overall, her commitment to research excellence and innovation makes her a deserving contender for this prestigious award.
Govind Prasad Buddha | Machine Learning | Best Paper Award Posted on 02/04/202402/04/2024 by Best Paper Award Dr. Govind Prasad Buddha, Machine Learning, Best Paper Award Doctorate at Bank of America, United States Summary: Dr. Govind Prasad Buddha is an accomplished software engineer and researcher with extensive experience in the fields of fraud detection, machine learning, and software engineering. He holds a Master’s degree in Computer Science from Andhra University and a Master of Technology (CST) from the University of Mysore. Currently pursuing his Doctor of Philosophy (Ph.D.) in Computer Science from LIUTEBM University, Dr. Buddha has made significant contributions to the development of innovative fraud detection systems during his tenure at Bank of America and Verizon Data Services India Pvt Ltd. With roles ranging from Software Engineer to Feature Lead, Dr. Buddha has demonstrated expertise in leading diverse teams and spearheading projects aimed at enhancing fraud detection mechanisms for credit card and digital platforms. His research interests encompass fraud detection systems, machine learning applications, software engineering practices, data security, and big data analytics. Driven by a passion for innovation and a commitment to excellence, Dr. Buddha continues to advance the field of fraud detection through his research and practical contributions. Professional Profile: Google Scholar Profile 👩🎓Education & Qualification: Master of Computer Science from Andhra University, completed in 1999-2001. Master of Technology (CST) from the University of Mysore, completed in 2002-2004. Doctor of Philosophy (CS) from LIUTEBM University, completed in 2020-2023. Professional Experience: Dr. Govind Prasad Buddha has a diverse professional experience spanning various roles and responsibilities. He has been actively engaged in the field of software engineering and technology management. His career highlights include: Serving as a Software Engineer III at Bank of America in Newark, DE, USA, since September 2022. In this role, he is involved in leading the Venom Detection automation team and overseeing Merchant Fraud Detection, among other responsibilities. Previously, he worked as a Feature Lead at Bank of America in India from October 2018 to June 2022, where he played a pivotal role in crafting merchant fraud rule engines and implementing machine learning models for real-time fraud detection. Before joining Bank of America, Dr. Buddha worked as a Senior Analyst and Team Lead in the same organization in India from September 2010 to December 2015, where he contributed to various projects involving credit card claims resolution, fraud detection, and system enhancements. Prior to his tenure at Bank of America, he gained valuable experience at Verizon Data Services India Pvt Ltd in Hyderabad, IN, serving as an Analyst from June 2007 to September 2010. During his time there, he worked as a lead developer for telecom mediation systems and played a crucial role in developing critical mediation reports. Earlier in his career, Dr. Buddha worked as an Associate Analyst at Convergys in Hyderabad, IN, from June 2005 to June 2007, where he was involved in telecom billing applications and developed background jobs for billing systems, among other responsibilities. Throughout his career, Dr. Govind Prasad Buddha has demonstrated a strong commitment to excellence in software engineering, project management, and technical leadership, contributing significantly to the success of the organizations he has been associated with. Research Interest: Fraud Detection Systems: Dr. Buddha is interested in developing innovative fraud detection systems for financial institutions, particularly focusing on credit card and digital transaction fraud. His research explores the application of machine learning algorithms and real-time data analysis techniques to enhance fraud detection accuracy and efficiency. Machine Learning Applications: He is keen on exploring the practical applications of machine learning in various domains, including fraud detection, customer behavior analysis, and predictive analytics. His research aims to leverage advanced machine learning models to uncover valuable insights from large-scale datasets and improve decision-making processes. Software Engineering Practices: Dr. Buddha investigates software engineering practices and methodologies aimed at improving the quality, reliability, and maintainability of software systems. His research interests include software design patterns, code refactoring techniques, and agile development methodologies. Data Security and Privacy: He is interested in studying data security and privacy concerns in software systems, especially in the context of financial transactions and sensitive personal information. His research focuses on developing robust security measures and privacy-preserving techniques to safeguard user data and prevent unauthorized access. Big Data Analytics: Dr. Buddha explores the challenges and opportunities associated with big data analytics in the context of fraud detection and financial services. His research aims to develop scalable and efficient algorithms for processing and analyzing large volumes of data to extract actionable insights and detect fraudulent activities in real-time. Publication Top Noted: Title: Explore The Application Of Machine Learning Algorithms To Analyze Genetic And Clinical Data To Tailor Treatment Plans For Individual Patients Authors: M Nalluri, SRB Reddy, R Pulimamidi, GP Buddha Journal: Tuijin Jishu/Journal of Propulsion Technology Volume: 44 Issue: 5 Pages: 2505-2513 Year: 2023 Citations: 36 Title: Behaviour based credit card fraud detection design and analysis by using deep stacked autoencoder based Harris grey wolf (HGW) method Authors: GPB GRADXS, N RAO Journal: SJIS-P Volume: 35 Issue: 1 Pages: 1-8 Year: 2023 Citations: 10 Title: AI-Enabled Health Systems: Transforming Personalized Medicine And Wellness Authors: R Pulimamidi, GP Buddha Journal: Tuijin Jishu/Journal of Propulsion Technology Volume: 44 Issue: 3 Pages: 4520-4526 Year: 2023 Citations: 8 Title: The Future of Healthcare: Artificial intelligence’s Role in Smart Hospitals and Wearable Health Devices Authors: DRP Govind Prasad Buddha Journal: Tuijin Jishu/Journal of Propulsion Technology Volume: 44 Issue: 5 Pages: 2498-2504 Year: 2023 Citations: 7 Title: Electronic system for authorization and use of cross-linked resource instruments Authors: GP Buddha, SP Kumar, CMR Reddy Publication: US Patent Application Application Number: 17/203,879 Year: 2022 Citations: 7