Sumei Li | Neural Network | Best Researcher 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:

👩‍🎓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.

 

 

ShivaDutt Jangampeta | Machine Learning | Industry Innovation Research Award

Mr. ShivaDutt Jangampeta, Machine Learning, Industry Innovation Research Award

ShivaDutt Jangampeta at JP Morgan Chase, United States

Mr. ShivaDutt Jangampeta appears to be a highly experienced professional with a strong background in cybersecurity, specifically in Security Information and Event Management (SIEM). However, determining his suitability for the “Research for Community Impact Award” requires an assessment of how his work impacts the community.

Relevant Criteria for the Research for Community Impact Award:

Community Impact: The award typically recognizes research that has a significant positive impact on the community, either through direct application or through contributions to knowledge that benefit the community.

Innovation and Advancement: Contributions to advancing the field and introducing innovative solutions or methodologies.

Collaboration and Dissemination: Engagement with stakeholders and dissemination of research findings to a broader audience.

Evaluation of Mr. Jangampeta’s Suitability:

Strengths:

Professional Experience:

  • Extensive experience in managing and optimizing SIEM systems.
  • Leadership roles in cybersecurity teams at major organizations like JPMorgan Chase and PEPSICO.
  • Development and implementation of advanced cybersecurity measures that could indirectly benefit community security by protecting sensitive data and reducing vulnerabilities.

Research Contributions:

  • Authored several publications related to data security, SIEM, and compliance, indicating a contribution to academic knowledge.
  • Research topics like anomaly detection in SIEM and the role of data security in compliance suggest a focus on enhancing cybersecurity frameworks, which can have broad implications for community safety and trust in digital systems.

Innovative Solutions:

  • Implementation of advanced technologies and automation in cybersecurity, contributing to more resilient and efficient security infrastructures.

Areas to Consider:

Direct Community Impact:

  • While Mr. Jangampeta’s work in cybersecurity is crucial, the direct impact on the community might be less apparent compared to other fields such as public health or environmental science.
  • It would be beneficial to highlight specific examples or case studies where his work directly protected community members or contributed to public safety.

Engagement and Dissemination:

  • The extent of his engagement with community stakeholders and efforts to disseminate his research findings to a broader, non-technical audience would strengthen his case for this award.

Conclusion:

Mr. Jangampeta’s extensive experience and contributions to the field of cybersecurity are impressive and certainly valuable. His work indirectly impacts the community by enhancing the security of digital infrastructures, which is increasingly important in today’s interconnected world. To bolster his application for the Research for Community Impact Award, it would be advantageous to emphasize any direct community benefits resulting from his cybersecurity initiatives and any outreach efforts he has made to educate or involve the community in his work.

If his research and professional activities can be framed to clearly demonstrate significant, tangible benefits to the community, Mr. Jangampeta could be a suitable candidate for the award.

 

Amarachi Madu | Automated Intelligence | Best Researcher Award

Mrs. Amarachi Madu, Automated Intelligence, Best Researcher Award

Amarachi Madu at Virginia Tech, United States

Summary:

Mrs. Amarachi Madu is a Ph.D. candidate in Computer Science at Virginia Tech, with a strong background in mathematics and computer science. With a keen interest in artificial intelligence and its applications, she has conducted groundbreaking research in various domains including finance, healthcare, and human-computer interaction. With a Master’s degree from Austin Peay State University and a Bachelor’s degree from Nnamdi Azikiwe University, she brings a diverse skill set encompassing programming, data analytics, machine learning, and statistical analysis. Amarachi is passionate about leveraging cutting-edge technologies to address real-world challenges and improve human lives.

Professional Profile:

👩‍🎓Education:

Ph.D. in Computer Science

  • University: Virginia Tech, Blacksburg, VA
  • Duration: 8/2020 – Present
  • GPA: 3.93/4.0

Master of Science in Computer Science and Quantitative Methods

  • University: Austin Peay State University, Clarksville, TN
  • Duration: 8/2018 – 5/2020
  • GPA: 4.0/4.0

Bachelor of Science in Mathematics

  • University: Nnamdi Azikiwe University, Awka, Nigeria
  • Duration: 9/2010 – 9/2014
  • GPA: 4.72/5.0

Professional Experience:

Mrs. Amarachi Madu has accumulated a wealth of professional experience across various prestigious institutions and organizations:

As an AI Research Summer Associate at JPMorgan Chase & Co from June 2023 to August 2023, she conducted groundbreaking research in financial services, focusing on complex problems in the finance domain in collaboration with the natural language processing team.

Currently, she serves as a Graduate Research Assistant at Virginia Tech, Blacksburg, VA since January 2023, where she contributes to cutting-edge AI research.

Prior to her role at Virginia Tech, she was a Graduate Teaching Assistant at Virginia Tech from August 2020 to December 2022, where she played a key role in teaching information visualization, problem-solving in computer science, introduction to programming in Java, and data analytics and visualization.

Previously, she also worked as an AI Research Summer Associate at JPMorgan Chase & Co from June 2022 to August 2022, focusing on AI research in financial services, particularly collaborating with the natural language processing team on research problems in finance.

During her tenure as a Summer Extern at AT&T from July 2021 to August 2021, she underwent extensive training in various business and technical aspects to enhance personal and professional development.

Her journey in research began as a Graduate Research Assistant at Austin Peay State University, Clarksville, TN from August 2018 to May 2020, where she facilitated structured learning sessions for students and contributed to advancements in research, particularly in the application of linear multi-step methods and statistical analysis.

Through these roles, Mrs. Amarachi Madu has demonstrated her commitment to advancing knowledge in artificial intelligence, natural language processing, and related fields, while also gaining valuable experience in teaching, research, and industry collaboration.

Research Interest:

  • Artificial Intelligence
  • Natural Language Processing
  • Multi-modal Machine Learning
  • Medical Imaging
  • Human-Computer Interaction

Top Noted Publication:

Title: ChatGPT passing USMLE shines a spotlight on the flaws of medical education

  • Authors: AB Mbakwe, I Lourentzou, LA Celi, OJ Mechanic, A Dagan
  • Journal: PLOS Digital Health
  • Volume: 2
  • Issue: 2
  • Page: e0000205
  • Year: 2023

Title: Chexrelnet: An anatomy-aware model for tracking longitudinal relationships between chest x-rays

  • Authors: G Karwande, AB Mbakwe, JT Wu, LA Celi, M Moradi, I Lourentzou
  • Conference: International Conference on Medical Image Computing and Computer-Assisted
  • Year: 2022

Title: Fairness metrics for health AI: we have a long way to go

  • Authors: AB Mbakwe, I Lourentzou, LA Celi, JT Wu
  • Journal: EBioMedicine
  • Volume: 90
  • Page: 9
  • Year: 2023

Title: Enhancing mathematics achievement of introverted and extroverted secondary school students through the use of advance organizers

  • Authors: OE Chinelo, ON Francisca, MA Blessing
  • Journal: Journal of Educational Research and Reviews
  • Volume: 4
  • Issue: 3
  • Page: 27-32
  • Year: 2016

Govind Prasad Buddha | Machine Learning | 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:

  • 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