Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Excellence in Research Award

Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Excellence in Research Award

Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Dong-A University | South Korea

Assist. Prof. Dr Hye-Youn Lim is a distinguished researcher and academic in artificial intelligence, computer vision, and intelligent systems, serving in the Department of Electronics Engineering at Dong-A University, Republic of Korea. Hye-Youn Lim obtained her Ph.D. from a leading research university and has accumulated extensive professional experience, including leading national and international research projects and collaborating with multiple industry partners on AI-based technology applications. Her research interests focus on intelligent video analysis, visual recognition, and smart city applications, demonstrating her expertise in applying computational methods to real-world problems. Hye-Youn Lim possesses a diverse set of research skills, including deep learning model development, attention-driven network design, data preprocessing and augmentation strategies, and applied computer vision for automated systems. Her scholarly output includes more than 30 SCI- and Scopus-indexed journal articles, with verified metrics of 22 Scopus documents, over 100 citations, and a recorded h-index, reflecting both impact and consistency in high-quality research dissemination.

Citation Metrics (Scopus)

120

90

60

30

0

Citations
105

Documents
22

h-index
3

Citations
Documents
h-index

View Scopus Profile
View ORCID Profile

Featured Publications

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

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.

Aljaz Hojski | Vision Sensing | Best Researcher

Dr. Aljaz Hojski | Vision Sensing | Best Researcher

Dr. Aljaz Hojski | Vision Sensing | Cadre doctor at Universitätspital Basel | Switzerland

Dr. Aljaz Hojski is a highly respected thoracic surgeon and clinical researcher, currently affiliated with Universitätspital Basel. With a strong focus on surgical innovation and patient-centered care, his contributions in minimally invasive thoracic procedures and oncological surgery have gained widespread recognition across academic and clinical communities. His medical background is complemented by an extensive portfolio of scientific publications, collaborative research initiatives, and active peer-review responsibilities in high-impact journals. A committed academician and practicing consultant, Dr. Hojski is known for bridging the gap between clinical application and evidence-based research, especially in lung cancer management, thoracic trauma, and postoperative pain optimization.

Academic Profile:

ORCID

Scopus

Education:

Dr. Hojski obtained his foundational medical education at the University of Ljubljana, where he developed a keen interest in thoracic medicine and surgical procedures. His education included comprehensive training in general medicine, with progressive specialization in thoracic surgery during his clinical rotations and postgraduate residency programs. Throughout his academic journey, he emphasized scientific inquiry alongside clinical excellence, engaging in laboratory-based research and hospital-based surgical trials. This dual focus on science and surgery established a strong platform for his later contributions to applied clinical research and international collaborations in minimally invasive thoracic techniques.

Experience:

Dr. Hojski currently serves in a senior consultant role within the Department of Thoracic Surgery at Universitätspital Basel, a leading center for cardiothoracic care and research in Europe. He is actively involved in surgical planning, patient care, and mentoring junior clinicians. In addition to his clinical duties, he contributes to institutional and multicenter research protocols aimed at improving perioperative outcomes and refining surgical strategies. His professional experience spans diverse domains including advanced thoracoscopic resections, surgical pain management, and postoperative complication risk stratification. Dr. Hojski’s extensive collaborations with multidisciplinary teams, including radiologists, anesthesiologists, and oncologists, have enabled the successful translation of academic research into clinical best practices.

Research Interest:

Dr. Hojski’s primary research interests include thoracic oncology surgery, 3D imaging and surgical planning, postoperative pain control strategies, and risk prediction in lung resection patients. He has been an investigator and co-investigator on several funded research projects focused on optimizing pain therapy following minimally invasive lung operations, and the development of advanced imaging tools for segmental lung function assessment. His research also extends into clinical outcome analysis, where he contributes to developing predictive models for surgical complications and evaluating the effectiveness of new procedural technologies. His interdisciplinary approach enables him to align clinical insight with scientific rigor in solving real-world surgical challenges.

Awards:

Dr. Hojski has been nominated for several recognitions in the field of medical science and thoracic surgery, reflecting his continued impact on both clinical advancement and scientific contribution. His research output and leadership have earned him invitations to present at international symposia, while his peer-reviewed publications and service as a reviewer demonstrate his influence in academic publishing. He remains committed to excellence in both operative care and medical scholarship, making him a compelling nominee for awards that celebrate high-impact contributions to science and medicine.

Selected Publications:

  • Estimating Postoperative Lung Function Using Three-Dimensional Segmental HRCT-Reconstruction: A Retrospective Pilot Study on Right Upper Lobe Resections, 2025, 60 citations

  • Perioperative Intravenous Lidocaine in Thoracoscopic Surgery for Improved Postoperative Pain Control: A Randomized, Placebo-Controlled, Double-Blind, Superiority Trial, 2024, 85 citations

  • Planning Thoracoscopic Segmentectomies with 3-Dimensional Reconstruction Software Improves Outcomes, 2025, 45 citations

  • A Risk Score to Predict Postoperative Complications in Patients with Resectable Non-Small Cell Lung Cancer, 2025, 50 citations

Conclusion:

Dr. Aljaz Hojski represents the ideal candidate for prestigious international research recognition, owing to his consistent contributions to thoracic surgery, clinical research, and interdisciplinary innovation. Through a well-balanced integration of surgical expertise, scientific research, and professional leadership, he has advanced both patient care and academic knowledge in thoracic medicine. His published works continue to shape protocols and influence best practices within surgical communities globally. As a forward-looking clinician-scientist, Dr. Hojski is well-positioned to lead future developments in thoracic healthcare and surgical outcomes research, making him a deserving nominee for awards that honor excellence in clinical and academic medical sciences.

 

 

Prof. Zuofeng Zhou | Optical Imaging | Best Researcher Award

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

 

Ms. Maryam Moshrefizadeh | Computer Vision Awards | Best Researcher Award

Ms. Maryam Moshrefizadeh | Computer Vision Awards | Best Researcher Award 

Ms. Maryam Moshrefizadeh, Siant Louis University, United States

Maryam Moshrefizadeh is a Ph.D. student in Computer Science at Saint Louis University, with previous experience as a Graduate Research Assistant at South Dakota State University. She holds a Master’s degree in Artificial Intelligence from Amirkabir University of Technology and a Bachelor’s degree in Computer Software Engineering from K. N. Toosi University of Technology, both in Tehran, Iran. Maryam’s research interests lie in computer vision, deep learning, and machine learning. Professionally, she has worked as an AI researcher and developer, including roles at DRNEXT.IR, Payesh24, and Cobenefit, where she contributed to the development of AI-driven platforms, machine learning models, and website functionality. She has a strong technical background in programming languages like Python, JavaScript, and C, as well as expertise in frameworks and tools like PyTorch, TensorFlow, Vue.js, and Docker. Maryam is fluent in English and Persian and is passionate about mountaineering, cycling, photography, and outdoor activities.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Maryam Moshrefizadeh is a promising and highly capable PhD student with extensive experience and research contributions in the field of Artificial Intelligence (AI), Machine Learning (ML), and Computer Vision. Her academic background, practical work experience, and emerging research output position her as an excellent candidate for the Best Researcher Award.

Education

🎓 Saint Louis University
Ph.D. | Graduate Research Assistant | Computer Science
📅 Jan 2024 ‑ Dec 2028 | St. Louis, MO, USA

🎓 South Dakota State University
Ph.D. | Graduate Research Assistant | Computer Science
📅 Aug 2022 ‑ Dec 2023 | Brookings, SD, USA

🎓 Amirkabir University of Technology (Polytechnic)
M.S. in Artificial Intelligence
📅 Jan 2014 ‑ Sept 2017 | Tehran, Iran

🎓 K. N. Toosi University of Technology
B.S. in Computer Software Engineering
📅 Sept 2009 ‑ Aug 2013 | Tehran, Iran

Work Experience

💼 DrNext.ir | Developer and AI Researcher
📅 Nov 2020 – Present
• Developed prescription writing notepad allowing doctors to type or use a pen 🖊️
• Implemented features for appointment scheduling and clinic reception handling 🗓️
• Worked in an agile team with Kanban, Scrum, Jira, and Git 🔧

💼 Payesh24 | AI Engineer
📅 Nov 2017 – Jul 2020
• Researched and implemented various AI algorithms and machine learning models 🤖
• Worked with supervised and unsupervised learning algorithms such as SVM and KNN 📊

💼 BeFine | Developer
📅 Apr 2006 – Feb 2009
• Developed and maintained website for diabetic products and information 💻
• Shared health tips and updates on diabetes 🩺

💼 Cobenefit Developer | Remote
📅 Oct 2021 – Present
• Develop and maintain websites using Vue.js, ES6, HTML5, CSS3, and SASS 🌐

Research Interests

🔍 Computer Vision | 🤖 Deep Learning | 📚 Machine Learning

Publication Top Notes

EC-WAMI: Event Camera-Based Pose Optimization in Remote Sensing and Wide-Area Motion Imagery

Multimodal Fusion of Heterogeneous Representations for Anomaly Classification in Satellite Imagery