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

Posted on by Global Sensor Awards

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.

Mr. Ahmet Serhat Yildiz | Computer Vision Awards | Best Researcher Award

Posted on by Global Sensor Awards

Mr. Ahmet Serhat Yildiz | Computer Vision Awards | Best Researcher Award

Mr. Ahmet Serhat Yildiz | Computer Vision Awards | Brunel University of London | United Kingdom

Mr. Ahmet Serhat Yildiz is an emerging researcher in sensing technology with growing expertise in machine learning, deep learning, embedded systems, and multi-sensor fusion, demonstrating strong potential for advanced research roles and academic leadership. He is currently pursuing his PhD in Electronic and Computer Engineering at Brunel University London, where he focuses on real-time object detection, semantic 3D depth sensing, LiDAR–camera fusion, and intelligent autonomous perception systems, aligning closely with sensing applications in robotics, transportation, surveillance, and industrial automation. His academic foundation includes degrees in electronics, electrical engineering, business management, and extensive English language training, providing a multidisciplinary perspective that strengthens his analytical and communication abilities. His professional experience includes roles as a Graduate Teaching Assistant in digital design, embedded systems, and computer architecture, as well as serving as an IoT facilitator, where he mentored learners and contributed to community-oriented technology initiatives. Mr. AHMET SERHAT YILDIZ has developed notable research projects, including FPGA-based embedded game systems, PLC-controlled industrial automation setups, and biomedical sensing circuits for pulse wave velocity measurement, demonstrating strong hands-on engineering skills. His research portfolio includes Scopus-indexed publications on YOLO-based detection models, sensor fusion for autonomous vehicles, and real-time navigation using LiDAR and deep learning frameworks, reflecting his ability to integrate theory with practical sensing applications. His technical skills include Python, PyTorch, embedded C, FPGA development, digital circuit design, PLC programming, and multi-sensor signal processing, enabling him to contribute to both algorithmic and hardware-oriented research environments. His achievements include scholarly publications, increasing citation impact, and recognition through participation in international conferences and multidisciplinary research projects.

Professional Profiles: ORCID | Google Scholar

Featured Publications 

  1. Alkandary, K., Yildiz, A. S., & Meng, H. (2025). A comparative study of YOLO series (v3–v10) with DeepSORT and StrongSORT: A real-time tracking performance study. Electronics.

  2. Tunali, M. M., Yildiz, A., & Çakar, T. (2022). Steel surface defect classification via deep learning. International Conference on Computer Science and Engineering (UBMK).

  3. Yildiz, A. S., Meng, H., & Swash, M. R. (2025). Real-time object detection and distance measurement enhanced with semantic 3D depth sensing using camera–LiDAR fusion. Applied Sciences.

  4. Tunali, M. M., Sayar, A., Aslan, Y., Mutlu, İ., & Çakar, T., including Yildiz, A. (2023). Enhancing quality control in plastic injection production: Deep learning-based detection and classification of defects. International Conference on Computer Science and Engineering (UBMK).

  5. Yıldız, A., Mişe, P., Çakar, T., Terzibaşıoğlu, A. M., & Öke, D. (2023). Spine posture detection for office workers with hybrid machine learning. International Conference on Computer Science and Engineering (UBMK).

  6. Yildiz, A. S., Meng, H., & Swash, M. R. (2025). YOLOv8–LiDAR fusion: Increasing range resolution based on image-guided sparse depth fusion in self-driving vehicles. Lecture Notes in Networks and Systems.

  7. Yildiz, A. S., Meng, H., & Swash, M. R. (2024). A multi-sensor fusion approach to real-time bird’s-eye view navigation: YOLOv8 and LiDAR integration for autonomous systems. Korkut Ata Scientific Research Conference Proceedings.

Dr. Yongho Jeong | Computer vision | Best Researcher Award

Posted on by Global Sensor Awards

Dr. Yongho Jeong | Computer vision | Best Researcher Award 

Dr. Yongho Jeong, Konkuk University, South Korea

Dr. Yongho Jeong is a physicist specializing in experimental particle physics, high-energy physics, and AI-driven data analysis. He earned his Ph.D. in Physics from Sungkyunkwan University, Korea, in 2022 under the supervision of Prof. YongIl Choi, focusing on the search for R-parity violating supersymmetry in proton-proton collisions at √s = 13 TeV using the CMS detector. He completed his B.S. in Physics from Soonchunhyang University in 2013. Dr. Jeong has held multiple postdoctoral positions, including at the University of Seoul, where he worked on Gas Electron Multiplier (GEM) detector aging tests, and at the Korea Astronomy and Space Science Institute (KASI), where he contributed to quantum noise reduction for future gravitational wave detectors. He has also been involved in AI software development at Mustree Company and is set to join Konkuk University as a postdoctoral researcher in 2024, focusing on 3D point cloud data analysis. His extensive research experience includes collaborations with CERN on the GEM Detector Upgrade Project for the CMS experiment, where he worked on quality control, chamber assembly, and detector performance studies. His expertise spans detector development, high-energy physics simulations, data analysis for supersymmetry searches, and advanced AI applications in physics.

Professional Profile:

ORCID

Summary of Suitability for Community Impact Award 

Dr. Yongho Jeong is a highly deserving candidate for the Community Impact Award, given his significant contributions to experimental particle physics, AI-driven technological advancements, and quantum noise reduction for future scientific applications. His extensive research collaborations, contributions to international projects, and involvement in technology-driven community advancements make him a strong nominee for this award.

📚 Education

  • Ph.D. in Physics (2014.09 – 2022.02) – Sungkyunkwan University, Suwon, Korea
    • Supervisor: YongIl Choi
    • Thesis: Search for R-parity violating supersymmetry in pp collisions at √s = 13 TeV in the CMS detector
  • B.S. in Physics (2007.03 – 2013.02) – Soonchunhyang University, Asan, Korea
    • Thesis: The Age of the Universe

💼 Work Experience

  • Postdoctoral Researcher – KonKuk University (KU), Seoul, Korea (2024.09 – Present)

    • Integrated Analytical Models and Advanced Strategies for 3D Point Cloud Data Analysis

  • Postdoctoral Researcher – University of Seoul (UOS), Seoul, Korea (2023.11 – 2024.08)

    • Gas Electron Multiplier (GEM) Detector Aging Test
    • Production of GEM Detector Foil for the Rare Isotope Accelerator Complex (RAON) Laboratory

  • Technology Team – AI Software Development – Mustree Company, Seoul, Korea (2023.07 – 2023.10)

    • Developed AI Software for Size Measurement

  • Postdoctoral Researcher – Korea Astronomy and Space Science Institute (KASI), Daejeon, Korea (2022.05 – 2023.07)

    • Quantum Noise Reduction Technology for Future Gravitational Wave Detectors
    • Development of a 2 µm Laser Squeeze System

  • Ph.D. Researcher – High Energy Physics – Korea University, Seoul, Korea (2020.01 – 2022.04)

    • Data Analysis for Supersymmetric Particles
    • Search for R-parity Violating Supersymmetry in Proton-Proton Collisions at √s = 13 TeV

  • Ph.D. Researcher – GEM Detector Upgrade Project (Phase II) – CERN, Geneva, Switzerland (2018.01 – 2019.12)

    • Quality Control (QC) of GEM Chambers in the CMS Experiment
    • QC2: Leakage Current Test
    • QC3: Gas Leak Test
    • QC4: High Voltage Test
    • GEM Chamber Assembly, Aging Tests & Discharge Probability Studies

  • Ph.D. Researcher – Experimental Particle Physics – Sungkyunkwan University, Suwon, Korea (2017.06 – 2018.02)

    • Data Analysis for tt̄ Inclusive Decay
    • Measurement of the Inclusive Top Quark Cross Section in Di-lepton Channels at √s = 13 TeV

  • Ph.D. Researcher – Experimental Particle Physics – University of Seoul, Seoul, Korea (2016.01 – 2017.06)

    • CMS Detector Simulation for Phase II Upgrade
    • Muon Isolation Optimization Simulation

🏆 Achievements & Contributions

✅ Authored numerous research papers in High-Energy Physics & Detector Technology
✅ Significant contributions to CMS Detector R&D at CERN
✅ Advanced AI-based measurement software for industry applications
✅ Developed quantum noise reduction techniques for future gravitational wave detectors

🎖️ Awards & Honors

🏅 Recognized Researcher in Particle Physics for contributions to Supersymmetry & CMS Experiments
🏅 Recipient of CERN Research Fellowships for GEM Detector Upgrade & Testing
🏅 Awarded Postdoctoral Research Positions in Multiple Leading Korean Institutions
🏅 Contributor to the CMS Collaboration at the European Organization for Nuclear Research (CERN)

Publication Top Notes:

A Mobile LiDAR-Based Deep Learning Approach for Real-Time 3D Body Measurement

A Multi-View Integrated Ensemble for the Background Discrimination of Semi-Supervised Semantic Segmentation