Mr. Suresha R | Computer Vision Awards | Excellence in Research Award

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Mr. Suresha R | Computer Vision Awards | Excellence in Research Award 

Mr. Suresha R | Computer Vision Awards | Amrita Vishwa Vidyapeetham | India

Mr. Suresha R. is a results-driven educator and technologist with over six years of combined experience in teaching computer science and academic leadership. He holds an M.Sc. in Computer Science and has qualified in UGC-NET and K-SET, while currently pursuing a Ph.D. Mr. Suresha R. has demonstrated expertise in curriculum design and research, particularly focusing on AI in autonomous solutions and computer vision applications. In his professional career, Mr. Suresha R. has served as an Assistant Professor at Amrita Vishwa Vidyapeetham, School of Computing, Mysuru Campus, and at SBRR Mahajana First Grade College, Mysuru, where he delivered advanced courses in Computer Vision, Digital Image Processing, Pattern Recognition, Computational Intelligence, Computer Graphics, Machine Learning, Exploratory Data Analysis, R Programming, Information Retrieval, Data Mining, Numerical Analysis, and Operations Research, consistently achieving high student satisfaction. His research interests encompass small traffic sign detection and recognition in challenging scenarios using computer vision and LiDAR-based techniques with ROS2 framework, deep learning-based vehicle detection and distance estimation for autonomous systems, motion blur image restoration, wild animal recognition through vocal analysis, and SVM-based medical image classification. Mr. Suresha . possesses strong research skills in Python, MATLAB, ROS2, machine learning, deep learning, image processing, and data analysis. He has successfully guided Bachelor’s and Master’s students in research projects, fostering innovation and academic growth. His academic contributions are recognized through multiple publications in prestigious journals and conferences, including IEEE Access, Procedia Computer Science, ICCCNT, CCEM, ICECAA, and INDIACom. Mr. Suresha . has a proven record of collaborating in interdisciplinary teams, effectively communicating complex technical concepts, and mentoring students to achieve excellence in research and practical applications. His dedication to lifelong learning and active engagement in both teaching and research demonstrates his commitment to advancing knowledge in computer science and autonomous systems. Throughout his career, Suresha  has received awards and recognitions for research excellence, contributing to the development of sustainable and intelligent solutions in the field of computer vision and AI. Overall, Mr. Suresha exemplifies a passionate and innovative professional, bridging theoretical foundations with applied research, and continues to make significant contributions to academia and technology

Professional Profiles: ORCID

Selected Publications 

  1. Suresha, R., Manohar, N., Ajay Kumar, G., & Singh, R. (2024). Recent advancement in small traffic sign detection: Approaches and dataset.

  2. Suresha, R., Manohar, N., & Jipeng, T. (2024). Two-stage traffic sign classification system.

  3. Sudharshan Duth, P., Manohar, N., Suresha, R., Priyanka, M., & Jipeng, T. (2024). Wild animal recognition: A vocal analysis.

  4. Suresha, R., Jayanth, R., & Shriharikoushik, M. A. (2023). Computer vision approach for motion blur image restoration system.

  5. Srinivasa, C., Suresha, R., Manohar, N., Dharun, G. K., Sheela, T., & Jipeng, T. (2023). Deep learning-based techniques for precise vehicle detection and distance estimation in autonomous systems.

  6. Suresha, R., Devika, K. M., & Prabhu, A. (2022). Support vector machine classifier based lung cancer recognition: A fusion approach.

Ms. Priyanka Manchegowda | Computer Vision | Women Researcher Award

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Ms. Priyanka Manchegowda | Computer Vision | Women Researcher Award

Ms. Priyanka Manchegowda | Computer Vision | Amrita Vishwa Vidyapeetham | India

Ms. Priyanka Manchegowda is a results-driven Assistant Professor and researcher, currently pursuing her Ph.D., with over 12 years of combined experience in teaching computer science, academic leadership, and curriculum development. She holds an M.Sc. in Computer Science from Pooja Bhagavat Memorial Mahajana Post Graduate Centre, affiliated with the University of Mysore, Mysuru, India, and has actively contributed to higher education by delivering advanced courses in Exploratory Data Analysis using Python, Digital Image Processing, Design and Analysis of Algorithms, Data Structures, Problem Solving and Programming, Operations Research, Numerical Analysis, Statistical Techniques, Programming in C/C++, and Database Management Systems, consistently achieving strong student satisfaction. Professionally, she has served as an Assistant Professor at SBRR Mahajana First Grade College, Mysuru, from 2013 to 2020, and currently at Amrita Vishwa Vidyapeetham, School of Computing, Mysuru Campus since 2020, where she also contributes as a member of the Board of Studies and has developed curricula in alignment with university standards. In addition to teaching, she has guided Bachelor’s and Master’s students on research projects, focusing her research on computer vision-based human age estimation tailored for Indian medico-legal scenarios, demonstrating expertise in analytical methods, quantitative aptitude, image processing, and programming with Python, C, and C++, alongside database management using MS SQL Server and tools such as MATLAB and Anaconda. Ms. Manchegowda has actively contributed to institutional initiatives and student development, serving as the SWAYAM MOOC Nodal Officer, and as convener for the Rotaract Club and SARANTHA, while also engaging in faculty evaluations for the Internal Quality Assurance Cell (IQAC). She brings strong leadership, teamwork, administrative, and communication skills, alongside a commitment to lifelong learning and academic engagement. Her professional recognition includes citations in Scopus with an h-index reflecting the impact of her scholarly contributions.

Professional Profiles: ORCID | Scopus

Selected Publications

  • Priyanka, M., Divyashree, M., & Madhu, V. (2022). Computer Vision-Based Approach for Estimating Age and Gender using Wrist X-Ray Images.

  • Priyanka, M., Sreekumar, S., & Arsh, S. (2022). Detection of Covid-19 from the Chest X-Ray Images: A Comparison Study between CNN and Resnet-50.

Prof. Zhang Wenli | Computer Vision | Excellence in Research Award

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Prof. Zhang Wenli | Computer Vision | Excellence in Research Award 

Prof. Zhang Wenli | Computer Vision | Beijing University of Technology | China

Dr. Wenli Zhang is a distinguished scholar and innovative technology leader currently serving as a Professor in the Faculty of Information Technology at Beijing University of Technology, recognized for impactful contributions in signal and information processing, artificial intelligence, computer vision, 3D point cloud processing, unmanned aerial vehicle inspection technology, and brain-computer interfaces, positioning Dr. Wenli Zhang as a key figure advancing intelligent sensing and human-machine interaction research in China and globally. Building a strong academic foundation through advanced studies in computer science and informatics in both China and Japan, Dr. Wenli Zhang earned a Ph.D. in Engineering from the University of Tokyo, where a passion for applied research and innovation in intelligent systems was further strengthened. Prior to joining academia in China, Dr. Wenli Zhang developed extensive industrial innovation experience as Chief Researcher at Panasonic Corporation’s Tokyo Research Institute, driving real-world AI and vision-based solutions for next-generation automated applications. In her current role, Dr. Wenli Zhang leads interdisciplinary research that spans multiple sectors including smart agriculture, UAV-based intelligent inspection, and medical rehabilitation, effectively bridging fundamental theories with emerging societal needs and technological transformation. With strong collaboration networks and a commitment to promoting scientific excellence, Dr. Wenli Zhang serves actively in influential professional roles, including council member of the Beijing Interdisciplinary Science Society and committee member of the Innovation Engineering Branch of China Creative Studies Institute, contributing leadership within China’s innovation and engineering communities. Skilled in advanced algorithm development, intelligent visual perception, sensor network data fusion, and neural signal decoding, Dr. Wenli Zhang empowers her research team to develop practical systems that enhance automation, sustainability, and accessibility across industries. Her exceptional commitment to teaching and mentorship has earned her the prestigious “Distinguished Teacher” recognition at Beijing University of Technology, reflecting her dual dedication to academic excellence and student success.

Professional Profiles: ORCID  

Selected Publications:

  • Jiang, K., Guo, W., & Zhang, W. (2025). Amodal Segmentation and Trait Extraction of On-Branch Soybean Pods with a Synthetic Dual-Mask Dataset. Sensors.

  • Zhang, W., Peng, X., Bai, T., Wang, H., Takata, D., & Guo, W. (2024). A UAV-Based Single-Lens Stereoscopic Photography Method for Phenotyping the Architecture Traits of Orchard Trees. Remote Sensing.

  • Zhang, W., Peng, X., Cui, G., Wang, H., Takata, D., & Guo, W. (2023). Tree Branch Skeleton Extraction from Drone-Based Photogrammetric Point Cloud. Drones.

  • Li, Y., Liu, B., & Zhang, W. (2024). Driving-Related Cognitive Abilities Prediction Based on Transformer’s Multimodal Fusion Framework. Sensors.

  • Pang, G., Liu, B., & Zhang, W. (2025). Cloud Rehabilitation System Based on Automatic sEMG Signal Processing. Book Chapter.

  • Zhai, R., Gao, Y., Li, G., Ding, Q., Zhang, Y., & Zhang, W. (2025). Control System for Rehabilitation Bionic Hand Based on Precise Control Algorithms.

  • Wang, Y., Pang, G., Liu, B., Li, Y., & Zhang, W. (2025). Gesture Recognition Method Based on Hybrid Classifier Under Non-ideal Conditions.

Dr. Meir Marmor | Image Analysis Awards | Best Researcher Award

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Dr. Meir Marmor | Image Analysis Awards | Best Researcher Award

Dr. Meir Marmor , UCSF, United States

Dr. Meir Tibrin Marmor is a Professor of Clinical Orthopaedic Surgery at the University of California, San Francisco (UCSF), specializing in orthopaedic trauma and joint replacement. He earned his M.D. from the Israel Institute of Technology with cum laude distinction and completed his orthopaedic residency in Israel before advancing his training through AO and clinical fellowships in trauma and joint replacement surgery in Germany and the U.S. Since 2010, he has served as a trauma surgeon across several Level I and II centers in Northern California, with a primary clinical role at Zuckerberg San Francisco General Hospital (ZSFG), where he leads the Orthopaedic “Blue” Service, the Geriatric Orthopaedic Trauma Service, and the OTI Digital Science Laboratory. Dr. Marmor’s research focuses on musculoskeletal trauma in vulnerable and geriatric populations, as well as surgical education, data science, and digital health technology. He has received numerous awards, including the OTA’s Kathy Cramer Young Clinicians Research Award and multiple best paper and poster recognitions. An active member of global orthopedic societies, he also chairs the OTA Artificial Intelligence Task Force and contributes extensively to academic publishing and international presentations.

Professional Profile:

SCOPUS

Summary of Suitability – Dr. Meir Tibrin Marmor for Best Researcher Award

Dr. Meir Tibrin Marmor is a distinguished clinician-scientist in orthopaedic trauma surgery with over two decades of training, research, and clinical practice in high-impact academic and clinical environments. Currently a Professor of Clinical Orthopaedic Surgery at the University of California, San Francisco (UCSF), he combines surgical excellence with robust contributions to medical research and technology.

🎓 Education

  • 📘 B.Sc. in Medical Sciences – Israel Institute of Technology, Haifa (1988–1992) cum laude

  • 🩺 M.D. in Medicine – Ruth and Bruce Rappaport Faculty of Medicine, Israel Institute of Technology (1992–1996) cum laude

  • 🏥 Orthopaedic Surgery Residency – Tel-Aviv Medical Center & Barzilai Medical Center, Israel (2000–2008)

  • 🌍 AO Fellowship in Orthopaedic Trauma – Saarland University Hospital, Germany (2008)

  • 🔬 Research Fellowship – UCSF, Orthopaedic Trauma (2008–2009)

  • 🩻 Clinical Fellowship – UCSF, Orthopaedic Trauma Surgery (2009–2010)

  • 🦴 Joint Replacement Fellowship – Joint Replacement Institute, Los Angeles (2017–2018)

  • 💻 Master’s in Information and Data Science (MIDS) – UC Berkeley (2022–2024)

🧑‍⚕️ Work Experience

  • 👨‍🏫 Professor of Clinical Orthopaedic Surgery – UCSF, Step 1 (Current)

  • 🏥 Orthopaedic Trauma Surgeon at:

    • Zuckerberg San Francisco General Hospital (ZSFG)

    • Enloe Medical Center, Chico, CA (2012–2014)

    • Regional Medical Center of San Jose (2013–2022)

  • 👨‍🔬 Research and Medical Director Roles:

    • Clinical Research Director – UCSF @ Regional Medical Center

    • Medical Director – Biomechanics Testing Facility @ UCSF

    • Director – Geriatric Orthopaedic Trauma Service & OTI Digital Science Lab @ ZSFG

    • Chief – Orthopaedic “Blue” Service @ ZSFG

🏆 Honors and Awards

  • 🎖️ B.Sc. Medical Sciences – cum laude (1992)

  • 🎖️ M.D. – cum laude (1997)

  • 🪖 Operational Performance Citation – Lebanon Front, IDF (1999)

  • 💰 Fellowship Scholarships – American Physicians Fellowship & Israeli Medical Association (2008)

  • 🖼️ “Best Poster” Award – OTA 25th Annual Meeting, San Diego (2009)

  • 📜 Best Paper Nomination – CAINE Conference (2014)

  • 💡 Kathy Cramer Young Clinicians Research Development Award – OTA (2015)

  • 🏅 Howard Rosen Table Instructor Award – AO Trauma North America (2018)

Publication Top Notes:

Revisiting the OTA-OFC: a systematic review of open fracture classification studies since 2010

Artificial intelligence: international perspectives on critical issues

The Impact of National Orthopaedic Fracture Registries: A Systematic Review

Patient Recruitment Characteristics for Wearable-Sensor-Based Outcome Assessment in Trauma Surgery

A scoping review and critical appraisal of orthopaedic trauma research using the American College of Surgeons National Trauma Data Bank

Worldwide research trends concerning operative competence in orthopedics: A bibliometric and visualization study

Does the CDC Surgical Wound Classification adequately predict postoperative infection in lower extremity fracture surgery?

Mortality, perioperative complications and surgical timelines in hip fracture patients: Comparison of the Spanish with the non-Spanish Cohort of the HIP ATTACK-1 trial

Prof. Zuofeng Zhou | Optical Imaging | Best Researcher Award

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Prof. Zuofeng Zhou | Optical Imaging | Best Researcher Award 

Prof. Zuofeng Zhou, Xi’an Institute of Optics and Precision Mechanics of CAS, China

Dr. Zuofeng Zhou is a Professor at the Xi’an Institute of Optics and Precision Mechanics (XIOPM), Chinese Academy of Sciences, and the Chief Engineer of XIOPM Holdings Co., Ltd. He is recognized as an Outstanding Young Scholar in Shaanxi Province, China. His research interests span image denoising, computer vision, machine learning, hyperspectral remote sensing image processing, and scientific and technological achievements industrialization. Over the past decade, he has published more than 80 research papers in esteemed journals and conferences and holds 14 technology and product patents. Dr. Zhou is an IEEE Member and serves as a reviewer for multiple international journals, including IEEE Transactions on Image Processing and Neurocomputing. He is actively involved in the industrialization of scientific and technological innovations, leading efforts in technology commercialization, startup incubation, and investment in high-tech enterprises, particularly in optoelectronics and military-civilian integration.

Professional Profile:

ORCID

SCOPUS

Summary of Suitability for Best Researcher Award

Dr. Zuofeng Zhou is a highly accomplished researcher with extensive contributions in the fields of image processing, computer vision, and machine learning. His expertise spans both theoretical research and practical industrial applications, particularly in hyper-spectral remote sensing image processing and image/video analysis.

🎓 Education

  • Ph.D. in a relevant field (Details not specified)

💼 Work Experience

  • Full Professor – XIOPM, Chinese Academy of Sciences
  • Chief Engineer – XIOPM Holdings Co., LTD
  • Referee – Reviewer for top journals including:
    • IEEE Transactions on Image Processing
    • Neurocomputing (Elsevier)
    • IET Image Processing
    • Signal Processing (Elsevier)
    • Conferences: CVPR, ICIP, ECCV

🏆 Achievements & Contributions

  • 📜 Research Contributions:
    • Published 80+ research papers in renowned journals and conferences (e.g., Signal Processing, ICIP, IET Image Processing)
    • Authored book chapter in Wavelet Transform and Some of Its Real-World Applications (ISBN: 978-953-51-2230-2)
  • 🔬 Research Interests:
    • Image denoising & computer vision
    • Machine learning & hyperspectral remote sensing
    • Image/video analysis
    • Industrialization of scientific and technological achievements
  • 📌 Patents:
    • Obtained 14 technology and product patent authorizations
  • 🚀 Industrialization Initiatives:
    • Led the commercialization of S&T achievements at XIOPM
    • Established 280+ hi-tech enterprises
    • Created 7,000+ jobs
    • Developed industry clusters in laser equipment, optoelectronic integrated circuits, and healthcare
  • 💰 Investment & Entrepreneurship:
    • Co-founded CAS Star Incubator Co., Ltd.
    • Managed funds totaling ~5 billion CNY
    • Invested in 150+ projects, attracting over 630 million CNY in social investment

🏅 Awards & Honors

  • 🌟 Outstanding Young Scholar – Shaanxi Province, China
  • 🎖 IEEE Member
  • 🏆 Recognitions:
    • “CAS Pilot Unit for S&T Achievement Transformation”
    • “Shaanxi Pilot Unit for Building an Innovative Province”
    • “State-level S&T Enterprise Incubator”

Publication Top Notes:

Satellite Pose Measurement Using an Improving SIFT Algorithm

ViBe algorithm based on background fusion and channel calculation

The Application of a Pavement Distress Detection Method Based on FS-Net

Image Enhancement Technology in Pavement Disease Detection System

High-Precision Volume Measurement of Potholes in Pavement Maintenance

 

Assoc. Prof. Dr. Linchang Zhao | Graphics Processing Unit | Best Researcher Award

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Assoc. Prof. Dr. Linchang Zhao | Graphics Processing Unit | Best Researcher Award

Assoc. Prof. Dr. Linchang Zhao, School of Computer Science, China

Dr. Linchang Zhao is an Associate Professor and graduate tutor at Guiyang University, China, specializing in machine learning, deep learning, few-shot learning, optimization algorithms, and meta-learning. He earned his Ph.D. in Computer Science from Chongqing University and holds an M.E. in Mathematics and Statistics from Qiannan Normal College for Nationalities, as well as a B.S. in Computer Science from Northeast Petroleum University. His research focuses on data mining, imbalanced learning, and developing novel learning models for small data scenarios. Dr. Zhao has authored numerous high-impact publications in top-tier journals and conferences, particularly in cost-sensitive meta-learning and software defect prediction. He has also contributed to several national and provincial research projects and holds patents related to small sample learning and software defect prediction. His expertise in artificial intelligence and deep learning continues to drive innovation in intelligent computing and data-driven decision-making.

Professional Profile:

SCOPUS

ORCID

Summary of Suitability for the Best Researcher Award

Linchang Zhao is a highly deserving candidate for the Best Researcher Award, given his significant contributions to machine learning, deep learning, few-shot learning, and optimization algorithms. His research has pushed the boundaries of artificial intelligence (AI) and computational intelligence, particularly in the areas of data mining, imbalanced learning, and meta-learning.

Education 🎓

  • Ph.D. in Computer Science – Chongqing University, China (2017.9 – 2021.7)
  • M.E. in Mathematics and Statistics – Qiannan Normal College for Nationalities, China (2015.9 – 2017.7)
  • B.S. in Computer Science – Northeast Petroleum University, China (2009.9 – 2013.7)

Work Experience 🏫

  • Associate Professor & Graduate Tutor – Guiyang University, China (Present)

Achievements 🏆

  • Published numerous research papers in prestigious journals such as IEEE Transactions on Cybernetics, Future Generation Computer Systems, and Neurocomputing.
  • Contributed to multiple national and international research projects on deep learning, machine learning, and data mining.
  • Developed advanced models for software defect prediction, cost-sensitive learning, and imbalanced data classification.

Awards & Honors 🎖️

  • Patent Holder for innovative methods in software defect prediction and small-sample learning classifiers.
  • Principal Investigator of a National Natural Science Foundation of China project on Deep Learning (2018–2020).
  • Contributor to significant projects in military intelligence, education big data, and oil exploration risk assessment.
  • Recognized Researcher in Few-Shot Learning, Meta-Learning, and Optimization Algorithms.

Publication Top Notes:

Design and Implementation of GPU Pass-Through System Based on OpenStack

RFAConv-CBM-ViT: enhanced vision transformer for metal surface defect detection

Siamese Dense Neural Network for Software Defect Prediction With Small Data

A cost-sensitive meta-learning classifier: SPFCNN-Miner

Software defect prediction via cost-sensitive Siamese parallel fully-connected neural networks