Xinran Li | Artificial Intelligence | Editorial Board Member

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Dr. Xinran Li | Artificial Intelligence  | Editorial Board Member

Dr. Xinran Li | University of Shanghai for Science and Technology | China

Dr. Xinran Li is an active researcher specializing in multimedia information security, perceptual image hashing, information hiding, and artificial intelligence security. She has established a strong publication record with more than twenty peer-reviewed papers, including fifteen SCI-indexed works and multiple IEEE Transactions publications. Her contributions span robust perceptual hashing, encrypted-domain image hashing, steganography analysis, secure multimedia processing, and feature-fusion methods for image authentication. She has participated in several funded research projects and maintains interdisciplinary collaborations reflected through co-authored journal and conference papers. Her work has earned over forty citations, demonstrating growing global impact. She serves as a reviewer for high-quality venues and is a member of prominent professional societies, contributing to ongoing advancements in secure multimedia computing.

Profile: Orcid 

Featured Publications: 

Xinran Li, & Zichi Wang. (2024). Vaccine for digital images against steganography. Scientific Reports, 14(1), 21340.

Xinran Li, Zichi Wang, Guorui Feng, Xinpeng Zhang, & Chuan Qin. (2024). Perceptual image hashing using orthogonal moments feature fusion. IEEE Transactions on Multimedia, 26, 10041–10054.

Xinran Li, Chuan Qin, Zichi Wang, Zhenxing Qian, & Xinpeng Zhang. (2022). Unified performance evaluation method for perceptual image hashing. IEEE Transactions on Information Forensics and Security, 17, 1404–1419.

Xinran Li, Mengqi Guo, Zichi Wang, & Chuan Qin. (2024). Robust image hashing in encrypted domain. IEEE Transactions on Emerging Topics in Computational Intelligence, 8(1), 670–683.

Zichi Wang, Xinpeng Zhang, & Xinran Li. (2025). Untraceable steganography: Towards the anonymity of steganographer. IEEE Signal Processing Letters, 32, 956–960.

Amol Bhagat | Big Data Security | Best Researcher Award

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Dr. Amol Bhagat | Big Data Security | Best Researcher Award

Manager Business Incubation at Prof Ram Meghe College of Engineering and Management, Badnera Amravati | India

Dr. Amol Prakash Bhagat is an accomplished academic and innovator serving as Assistant Professor, Manager–Business Incubator, and Programme Coordinator–IEDC at Ram Meghe College of Engineering & Management, Badnera, Amravati. With over 18 years of teaching experience, he has made significant contributions in Data Science, Artificial Intelligence, Machine Learning, Digital Signal Processing, and Medical Image Processing. Dr. Bhagat has authored 100+ publications, filed 38 patents (7 granted), published 10 books, and guided numerous postgraduate and doctoral scholars. He has secured multiple high-value research grants from DST, NITI Aayog, and MSME, and is recognized with prestigious awards such as the Start-Up NIDHI Award (DST EDII) and IETE Higher Technical Proficiency Award. As a mentor for initiatives like Smart India Hackathon and Atal Tinkering Labs, he actively fosters innovation and entrepreneurship.

Professional Profile:

Education: 

Dr. Amol Prakash Bhagat holds a Ph.D. in Information Technology, complemented by an M.Tech in Computer Science & Engineering and a B.E. in Information Technology. His strong academic foundation in computing, engineering, and advanced research underpins his extensive contributions to the fields of data science, artificial intelligence, and digital signal processing.

Experience:

With over 18 years of teaching experience and 8 years dedicated to research, Dr. Bhagat has successfully guided 25 M.E./M.Tech students to completion and serves as a Ph.D. supervisor at Sant Gadge Baba Amravati University. He has also contributed 1.5 years in the industry, bringing practical expertise to his academic work. Beyond teaching and research, he has held key leadership roles, including Coordinator of the Department of Science and Technology-funded Innovation & Entrepreneurship Development Centre (IEDC), Manager of the MSME Business Incubator, and Nodal Officer for the Atal Ranking of Institutions on Innovation Achievements (ARIIA). His professional service includes active participation as a Technical Programme Committee Member in over 30 international conferences, reviewer for leading publishers such as Elsevier, IEEE, and Springer, Chairperson in 15+ conferences, and delivering more than 150 expert lectures as a resource person.

Research Interest:

Data Science, Artificial Intelligence, Machine Learning, Digital Signal Processing, Soft Computing, Data Analytics, Medical Image Processing, Image Segmentation, Content-Based Image Retrieval, Cybersecurity in Wireless Networks, and Innovation-Driven Entrepreneurship.

Publications Top Noted:

  1. Medical Images: Formats, Compression Techniques and DICOM Image Retrieval – A Survey
    Year: 2012 | Citations: 40

  2. Classification and Analysis of Clustering Algorithms for Large Datasets
    Year: 2015 | Citations: 20

  3. A Detection and Prevention of Wormhole Attack in Homogeneous Wireless Sensor Network
    Year: 2016 | Citations: 19

  4. Six Sigma DMAIC Literature Review
    Year: 2015 | Citations: 19

  5. Design and Development of Systems for Image Segmentation and Content-Based Image Retrieval
    Year: 2012 | Citations: 17

Conclusion:

Dr. Amol Bhagat’s exceptional research productivity, innovation-driven mindset, and proven leadership in big data security and AI applications make him a highly deserving candidate for the Best Researcher Award. His strong patent portfolio, grant acquisition record, and dedication to nurturing talent align perfectly with the award’s vision of recognizing transformative contributions. With expanded international collaborations and global outreach, Dr. Bhagat is poised to further advance the frontiers of data-driven security and innovation, cementing his status as a global leader in the field.

Huy Dinh | Artificial Intelligence | Best Researcher Award

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Mr. Huy Dinh | Artificial Intelligence | Best Researcher Award

Huy Dinh at Stanford University Department of Orthopaedic Surgery | United States

Huy G. Dinh, BS is a physician-scientist in training at the Stanford University School of Medicine, combining expertise in bioengineering, computational modeling, and artificial intelligence to advance medical diagnostics and patient care. His research spans AI-assisted motion analysis, computational hemodynamics, and predictive modeling of musculoskeletal and vascular diseases. A recipient of the Cognitive Scientist Best Researcher Award and the MedScholars Discovery Grant, Mr. Dinh has authored multiple peer-reviewed publications and presented at leading conferences, reflecting a deep commitment to translational research at the intersection of engineering and medicine.

Professional Profile:

Education: 

  • Doctor of Medicine (MD) – Stanford University School of Medicine, Stanford, CA

  • Bachelor of Science in Bioengineering – University of California, Los Angeles (UCLA), Los Angeles, CA

Experience:

Mr. Dinh’s professional journey bridges clinical research, teaching, and emergency medical services. At Stanford’s Ladd Lab, he develops novel AI-driven motion analysis tools for assessing hand function and investigates radiographic patterns to predict osteoarthritis progression. His earlier work at UCLA’s Chien Lab focused on fluid simulations of vascular disease and predictive models for aneurysm progression. Beyond research, he has served as a Teaching Assistant in Orthopaedic Surgery, an EMT providing acute care across Southern California, and a campus leader organizing large-scale cultural and academic events.

Research Interest:

  • Artificial Intelligence in Medicine – AI-assisted motion capture, predictive analytics, and interpretable models for clinical decision-making

  • Computational Hemodynamics – Patient-specific simulations of vascular flow and disease progression

  • Musculoskeletal Imaging – Quantitative radiographic analysis and shape modeling in osteoarthritis

  • Medical Device Development – Integrating engineering principles into novel diagnostic tools

Publications Top Noted:

1. Proof of Concept and Validation of Single-Camera AI-Assisted Live Thumb Motion Capture

  • Year: 2025

2. Examining the Utility of 2D DSA for Carotid Stenosis Hemodynamic Pressure Analysis

  • Year: 2023

3. Image-Derived Metrics Quantifying Hemodynamic Instability Predicted Growth of Unruptured Intracranial Aneurysms

  • Year: 2022

4. Reconstruction of Carotid Stenosis Hemodynamics Based on Guidewire Pressure Data and Computational Modeling

  • Year: 2022

5. Patient-Specific Analyses Reveal Differences in Hemodynamic and Morphological Parameters Between Growing and Stable Unruptured Intracranial Aneurysms

  • Year: 2022

Conclusion:

Mr. Huy Dinh’s pioneering contributions in AI-driven medical diagnostics make him an outstanding candidate for the Best Researcher Award in Artificial Intelligence. His ability to integrate engineering innovation with clinical needs positions him as a transformative figure in the future of personalized medicine. With continued focus on expanding collaborations, translating research into clinical practice, and contributing to the ethical evolution of AI in healthcare, he is poised to make lasting global contributions. His record of excellence and innovation strongly supports his recognition with this award.