Osman Yildirim | Deep Learning | Best Researcher Award

Prof. Osman Yildirim | Deep Learning | Best Researcher Award

Head of the Department | Istanbul Aydın University | Turkey 

Prof. Osman Yildirim is a distinguished academic and researcher recognized for his contributions at the intersection of engineering, business, sustainability, and biomedical applications. He holds dual doctoral degrees in Engineering and Business Administration, a unique combination that has enabled him to approach research challenges with a strong interdisciplinary perspective. Over the course of his career, he has taken on significant academic leadership roles, including serving as Head of Department at Istanbul Aydin University, while also guiding doctoral students and fostering collaborative research projects. His professional experience spans teaching across engineering and business disciplines, coordinating research initiatives, and contributing to institutional development through mentorship and administrative leadership. His primary research interests focus on green transformation, sustainable supply chains, carbon policy impacts, energy management systems in universities, and AI-based medical imaging applications for improved diagnostics. These areas reflect his commitment to aligning research with both technological advancements and societal needs, particularly in the context of sustainable development and healthcare innovation. He has published widely in reputed Q1 and Q2 indexed journals such as Scopus and SCI, showcasing the impact of his work in both technical and applied fields. His achievements have been recognized through awards and honors that acknowledge his contributions to advancing interdisciplinary research and education. In addition, he has built valuable collaborations with international teams, integrating expertise from engineering, business, and medicine to deliver impactful solutions with global relevance. His research skills include expertise in machine learning, AI-driven image analysis, sustainable system design, and computational modeling for optimization under carbon constraints. These technical strengths, combined with his leadership and mentorship, position him as a leading scholar dedicated to advancing academic excellence and addressing global challenges through innovative and socially relevant research.

Profile: Google Scholar | Scopus Profile | ORCID Profile

Featured Publications

Ozturk, A. I., Yıldırım, O., İdman, E., & İdman, E. (2025). A comparative study of hybrid decision tree–deep learning models in the detection of intracranial arachnoid cysts. Neuroscience Informatics, 100234.

Ozturk, A. I., Yildirim, O., Kaygusuz, K., Idman, E., & Idman, E. (2025). Brain cyst detection using deep learning models. International Journal of Innovative Research and Scientific Studies, 8(5), 8974.

Borhan Elmi, M. M., & Yıldırım, O. (2025). Improve MPPT in organic photovoltaics with chaos-based nonlinear MPC. Balkan Journal of Electrical and Computer Engineering, 13(1), 1418574.

Ozturk, A. I., Yıldırım, O., & Deryahanoglu, O. (2025). A comprehensive strategy for the identification of arachnoid cysts in the brain utilizing image processing segmentation methods. International Journal of Innovative Technology and Exploring Engineering, 14(2), 1031.

Borhan Elmi, M. M., & Yıldırım, O. (2024). Improve LVRT capability of organic solar arrays by using chaos-based NMPC. International Journal of Energy Studies, 4(3), 1449558.

Yildirim, O., Khaustova, V. Y., & Ilyash, O. I. (2023). Reliability and validity adaptation of the hospital safety climate scale. The Problems of Economy, 4(1), 207–216.

Yildirim, O. (2023). Multidimensional and strategic outlook in digital business transformation: Human resource and management recommendations for performance improvement. In Book chapter.

Yildirim, O. (2023). Health professionals’ perspective in the context of social media, paranoia, and working autonomy during the COVID-19 pandemic period. Archives of Health Science Research, 10(1), 30–37.

Yildirim, O. (2023). The personified model for supply chain management. In Multidimensional and strategic outlook in digital business transformation: Human resource and management recommendations for performance improvement.

Yildirim, O., Ilyash, O. I., Khaustova, V. Y., & Celiksular, A. (2022). The effect of emotional intelligence and work-related strain on the employee’s organizational behavior factors. The Problems of Economy, 2(1), 124–131.

Yildirim, O. (2022). Investigation of the electrical conductivity of pernigranilin with carbon monoxide and nitrogen monoxide doping. Mathematical Statistician and Engineering Applications, 9(4).

Yildirim, O. (2022). Cyst segmentation using filtering technique in computed tomography abdominal kidney images. Mathematical Statistician and Engineering Applications, 9(4).

Yildirim, O. (2022). Design of flyback converter by obtaining the characteristics of polymer based R2R organic PV panels. International Journal of Renewable Energy Research, 12(4).

Avdullahi, A., & Yildirim, O. (2021). The mediating role of emotional stability between regulation of emotion and overwork. In Book chapter.

Tunç, P., Yıldırım, O., Göktepe, E. A., & Çapuk, S. (2021). Investigation of the relationship between personality, organizational identification and turnover in competitive flight model. TroyAcademy, 6(1), 894141.

Tunç, P., Yıldırım, O., Göktepe, E. A., & Çapuk, S. (2021). Investigation of the relationship between personality, organizational identification and turnover in competitive flight model. Çanakkale Onsekiz Mart Üniversitesi Uluslararası Sosyal Bilimler Dergisi, 4(1), 804959.

Prof. Hoonsoo Lee | Applications of Computer Vision | Best Researcher Award

Hoonsoo Lee | Applications of Computer Vision | Best Researcher Award

Hoonsoo Lee at Chungbuk National University, South Korea

Profiles

Scopus

Orcid

 Academic Background:

He is an Associate Professor in the Dept. of Biosystems Engineering at Chungbuk National University, located in Cheongju, Korea. The university is situated at 1 Chungdae-ro, BLDG# S21-24, RM# 202, Seowon-gu, Cheongju-si, Chungcheongbuk-do, 28644, Republic of Korea.

Education:

Prof. Lee earned his Ph.D. in Agricultural Machinery Engineering from Chungnam National University in August 2015, with a dissertation on the rapid detection of pathogenic infections in watermelon seeds using spectral image analysis. He completed his M.S. in the same field in August 2009, focusing on the development of an electronic nose system for evaluating meat freshness. He holds a B.S. in Bioindustrial Machinery Engineering, which he completed in August 2007.

 Employment History:

Prof. Lee has been an Associate Professor at Chungbuk National University since September 2018. Prior to this, he worked as a PostDoc Researcher at the United States Department of Agriculture (USDA) Agricultural Research Service (ARS) in Beltsville, MD, USA, from August 2015 to August 2018. His experience also includes serving as a Research Assistant at Chungnam National University from June 2008 to August 2015 and an internship at USDA, ARS from July 2010 to June 2011.

 Research Interests:

Prof. Lee’s research focuses on developing nondestructive sensing technology for agricultural and food products. He is also interested in data analysis using hyperspectral imaging in conjunction with machine learning and artificial intelligence techniques.

 Research Experience:

Prof. Lee specializes in non-destructive quality measurement of food and agricultural products using vibrational spectroscopic techniques. His work includes developing and commercializing a high-throughput online detection system utilizing optical techniques. He has created hyperspectral and multispectral imaging systems for pathogen-infected seeds and fecal contamination on leafy greens. Additionally, he has developed hyperspectral imaging systems to evaluate food quality, focusing on applications such as detecting physical damages in pears, identifying cracks in tomatoes, assessing color levels in pepper powder, and measuring moisture distribution in cooked meats, rice, and soybeans. Furthermore, he has created a multipurpose floating platform for hyperspectral imaging and monitoring E. coli concentrations in irrigation ponds in Maryland. His research also includes developing Vis/NIR hyperspectral models for assessing the effects of water and fertilizer on crops like cabbage, garlic, and soybeans, as well as laser speckle technology for diagnosing crop stress to enhance precision agriculture practices.

 Publications:

Current trends in the use of thermal imagery in assessing plant stresses: A review
  • Authors: Adhitama Putra Hernanda, R., Lee, H., Cho, J.-I., Cho, B.-K., Kim, M.S.
  • Journal: Computers and Electronics in Agriculture
  • Year: 2024
Chlorophyll Fluorescence Imaging for Environmental Stress Diagnosis in Crops
  • Authors: Park, B., Wi, S., Chung, H., Lee, H.
  • Journal: Sensors
  • Year: 2024
Construction of a sustainable model to predict the moisture content of porang powder (Amorphophallus oncophyllus) based on pointed-scan visible near-infrared spectroscopy
  • Authors: Amanah, H.Z., Rahayoe, S., Harmayani, E., Lee, H.
  • Journal: Open Agriculture
  • Year: 2024
Spectroscopy Imaging Techniques as In Vivo Analytical Tools to Detect Plant Traits
  • Authors: Hernanda, R.A.P., Lee, J., Lee, H.
  • Journal: Applied Sciences (Switzerland)
  • Year: 2023
Snapshot-Based Multispectral Imaging for Heat Stress Detection in Southern-Type Garlic
  • Authors: Ryu, J., Wi, S., Lee, H.
  • Journal: Applied Sciences (Switzerland)
  • Year: 2023

Mr. Wenming Chen | Applications of Computer Vision | Industry Innovator Award

Mr. Wenming Chen, Applications of Computer Vision, Industry Innovator Award

Wenming Chen at Ningbo Polytechnic, China

Professional Profile

🌟 Summary:

Mr. Wenming Chen is a Lecturer and Engineer at the School of Artificial Intelligence, Ningbo Polytechnic. He specializes in developing machine vision and industrial control systems, significantly improving operational efficiency and accuracy in various industries.

🎓 Education:

  • Bachelor’s Degree, Ningbo University, 2012
  • Master’s Degree, Ningbo University, 2015

💼 Professional Experience:

  • Lecturer, School of Artificial Intelligence, Ningbo Polytechnic
  • Led projects on machine vision inspection, industrial robot vision measurement systems, and infrared imaging correction detection systems.

🔬 Research Interests:

  • Industrial visual inspection
  • Industrial control systems
  • Object detection

📖 Publications Top Noted:

Paper Title: Recognition and analysis system of steel stamping character based on machine vision
  • Authors: Wenming Chen
  • Journal: AUTOMATIKA
  • Year: 2023
Paper Title: A rotatable battery recognition method based on improved YOLOv5
  • Authors: Wenming Chen
  • Journal: International Journal of Sensor Networks
  • Year: 2023