Dr. Recai Yilmaz | Applications of Computer Vision | Best Researcher Award

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Dr. Recai Yilmaz | Applications of Computer Vision | Best Researcher Award

Doctorate at Children’s National Hospital, Washington, D.C, United States

👨‍🎓 Profiles

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Google Scholar

🎓 Early Academic Pursuits

Dr. Recai Yilmaz’s academic journey began with a strong foundation in medicine, earning his M.D. from Istanbul Faculty of Medicine in 2017. His passion for medical innovation led him to pursue a Ph.D. in Experimental Surgery at McGill University, focusing on neurosurgical simulation and artificial intelligence. His early education at Private Anafen Gaye High School in Istanbul, where he was a full-scholarship student, demonstrated his academic excellence from a young age.

💼 Professional Endeavors

Dr. Yilmaz has amassed extensive experience at the intersection of medicine, artificial intelligence, and computer vision. As a Postdoctoral Research Fellow at Children’s National Medical Center, Washington, D.C., he applies computer vision and machine learning to intraoperative surgical video analysis, aiming to improve real-time surgical performance assessment. His tenure at MultiCIM Technologies Inc. (CareChain) further reflects his leadership in integrating AI into patient triage and clinical decision-making systems.

🔬 Contributions and Research Focus

Dr. Yilmaz’s research is centered on AI-driven surgical assessment, medical data organization, and neurosurgical simulation. At McGill University’s Neurosurgical Simulation and Artificial Intelligence Learning Centre, he developed virtual reality surgical simulation models, advanced AI-based assessment tools, and real-time feedback mechanisms for neurosurgical expertise evaluation. His research also includes cloud-based medical data management and optical flow analysis in surgical procedures.

🌍 Impact and Influence

His pioneering work has significantly influenced AI applications in surgery and clinical decision-making. By integrating computer vision and deep learning into medical practice, he has improved the efficiency and accuracy of surgical skill evaluation, patient triage, and clinical outcome prediction. His projects have not only enhanced surgical education but also contributed to safer and more effective surgical procedures worldwide.

📚 Academic Citations and Recognitions

Dr. Yilmaz has been recognized with numerous awards and grants, including the prestigious Innovator of the Year Award (2023) by the Congress of Neurological Surgeons and research funding from the Brain Tumour Foundation of Canada and the Royal College of Physicians and Surgeons of Canada. His work has been published in high-impact journals and conferences, advancing the field of AI in medicine.

💻 Technical Expertise

  • Artificial Intelligence & Machine Learning (Medical AI applications, Neural Networks)
  • Computer Vision & Image Processing (Surgical video analysis, Optical flow)
  • Programming Languages (Python, MATLAB, C++, IBM SPSS)
  • Statistical Analysis & Data Science (AI-driven performance assessment, Data modeling)

🎓 Teaching and Mentorship

Dr. Yilmaz has actively mentored graduate students, medical researchers, and undergraduate students in AI, neurosurgical simulation, and data analysis. His mentorship spans institutions such as McGill University and Marianopolis College, where he has guided students in machine learning applications, research methodologies, and clinical AI integration.

🌟 Legacy and Future Contributions

Dr. Yilmaz’s legacy lies in his commitment to bridging AI and medicine. His contributions to surgical performance evaluation, AI-driven triage systems, and neurosurgical education continue to shape the future of AI-assisted medical practice. Moving forward, he aims to expand AI integration in real-time surgical decision-making, enhance global accessibility to AI-driven surgical training, and pioneer intelligent healthcare solutions.

 

Publications

AI in surgical curriculum design and unintended outcomes for technical competencies in simulation training

  • Authors:Ali M Fazlollahi, Recai Yilmaz, Alexander Winkler-Schwartz, Nykan Mirchi, Nicole Ledwos, Mohamad Bakhaidar, Ahmad Alsayegh, Rolando F Del Maestro
  • Journal: JAMA network open
  • Year: 2023

Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task

  • Authors: Sharif Natheir, Sommer Christie, Recai Yilmaz, Alexander Winkler-Schwartz, Khalid Bajunaid, Abdulrahman J Sabbagh, Penny Werthner, Jawad Fares, Hamed Azarnoush, Rolando Del Maestro
  • Journal: Computers in Biology and Medicine
  • Year: 2023

O022 real-time artificial intelligence instructor vs expert instruction in teaching of expert level tumour resection skills–a randomized controlled trial

  • Authors: R Yilmaz, M Bakhaidar, A Alsayegh, R Del Maestro
  • Journal: British Journal of Surgery
  • Year: 2023

Effect of artificial intelligence tutoring vs expert instruction on learning simulated surgical skills among medical students: a randomized clinical trial

  • Authors: Ali M Fazlollahi, Mohamad Bakhaidar, Ahmad Alsayegh, Recai Yilmaz, Alexander Winkler-Schwartz, Nykan Mirchi, Ian Langleben, Nicole Ledwos, Abdulrahman J Sabbagh, Khalid Bajunaid, Jason M Harley, Rolando F Del Maestro
  • Journal: JAMA network open
  • Year: 2022

Assessment of learning curves on a simulated neurosurgical task using metrics selected by artificial intelligence

  • Authors: Nicole Ledwos, Nykan Mirchi, Recai Yilmaz, Alexander Winkler-Schwartz, Anika Sawni, Ali M Fazlollahi, Vincent Bissonnette, Khalid Bajunaid, Abdulrahman J Sabbagh, Rolando F Del Maestro
  • Journal: Journal of neurosurgery
  • Year: 2022

Ms. Joy Shen | Applications of Computer Vision | Best Researcher Award

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Ms. Joy Shen | Applications of Computer Vision | Best Researcher Award

Joy Shen at University of Maryland at College Park, United States

Profiles

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📚 Summary

Ms. Joy Shen is a Ph.D. candidate in Reliability Engineering at the University of Maryland, with expertise in probabilistic risk assessments (PRA) and reliability analysis, particularly for nuclear power systems. She currently works as a Reliability Engineer at NIST, where she develops Bayesian networks and conducts risk-based analyses to improve safety and operational efficiency in nuclear reactors.

Education

  • Ph.D. in Reliability Engineering (Expected May 2025), University of Maryland
  • MSc. in Reliability Engineering (May 2023), University of Maryland
  • B.Sc. in Mechanical Engineering with Nuclear Engineering Minor (Aug 2018), University of Maryland

👩‍🏫 Work Experience

  • Reliability Engineer | NIST, Gaithersburg, MD (Feb 2024 – Present)
    Developed Bayesian network models for safety-related systems in NIST’s research reactor. Analyzed degradation and assisted with relicensing efforts for long-term operations.
  • Mechanical Engineer | NIST, Gaithersburg, MD (Aug 2019 – Aug 2023)
    Performed CFD analysis and developed CAD models for the design of a new neutron source.

🔬 Research Experience

  • Graduate Research Assistant | University of Maryland, College Park, MD
    Conducted pioneering research in external flood PRAs using Monte Carlo augmented Bayesian networks. Investigated nuclear power plant risks and contributed to the U.S. NRC’s efforts to assess system vulnerabilities during external floods.
  • Associate Researcher | NIST, Gaithersburg, MD
    Conducted neutron energy spectrum measurements, proving the viability of Cf-250 as a calibration source for radiation instrumentation.

🛠 Skills and Certifications

  • CAD: Solidworks, Autodesk Inventor
  • Programming: MATLAB, Python, IGOR
  • Accident Analysis: MCNP, RELAP5, TRACE, SNAP
  • Probabilistic Tools: SAPHIRE, GeNIE, Minitab
  • Certifications: 10 CFR 50.59 Training, Procedure Professionals Association (PPA)

🔍 Research Interests

Ms. Joy’s research interests focus on probabilistic risk assessments (PRA), Bayesian networks, nuclear reactor safety, and external flood risk assessments. She is passionate about enhancing the reliability and safety of critical infrastructure through advanced analytical models.

 

Publications

A Monte Carlo augmented Bayesian network approach for external flood PRAs

  • Authors: Shen, J., Bensi, M., Modarres, M.
  • Year: 2025

A Hybrid, Bayesian Network-Based PRA Methodology for External Flood Probabilistic Risk Assessments at Nuclear Power Plants

  • Authors: Shen, J., Frantzis, C., Marandi, S., Bensi, M., Modarres, M.
  • Year: 2023

Synthesis of Insights Regarding Current PRA Technologies for Risk-Informed Decision Making

  • Authors: Shen, J., Marandi, S., Bensi, M., Modarres, M.
  • Year: 2023

Prof. Aasma Shaukat | Applications of Computer Vision | Best Paper Award

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Prof. Aasma Shaukat | Applications of Computer Vision | Best Paper Award

Professor at New York University, United States

Profiles

Scopus

Google Scholar

Education

Dr. Shaukat completed her F.Sc Pre-Medical at Kinnaird College for Women, Lahore in 1993. She earned her M.B., B.S. in Medicine from The Aga Khan University Medical College, Karachi in 1998. Her postgraduate studies include an MPH in International Health and Epidemiology from Johns Hopkins School of Public Health (2000), an Internship in Internal Medicine at State University of New York School of Medicine and Biomedical Sciences (2001), a Residency in Internal Medicine at the same institution (2003), and a Fellowship in Gastroenterology from Emory University School of Medicine (2007).

Current Appointments and Leadership Positions

Dr. Aasma Shaukat is the Program Director of KL2 at CTSI NYU (since January 2024). She has been serving as the Director of GI Outcomes Research and the Robert M. and Mary H. Glickman Endowed Professor of Medicine at NYU School of Medicine since July 2021. Additionally, she is a Professor of Population Health and Co-Director of the TREC Program at CTSI. She also holds a position as a Staff Physician at NY Harbor VA, New York and is an Adjunct Professor at the University of Minnesota School of Public Health (since May 2018).

Awards and Honors

Among her numerous accolades, Dr. Shaukat was selected for the AGA Executive Women Leadership workshop in Denver (2023) and received the ACG Colon Cancer Prevention Abstract Award in Vancouver (2023). She has been honored with the American College of Gastroenterology Governor’s Award for Excellence in Clinical Research (2020) and the AGA Young Investigator Award (2016). Other notable awards include the Champion of Colorectal Cancer Prevention Award (2014) and multiple Teacher of the Year Awards from the University of Minnesota Medical School.

Memberships and Professional Organizations

Dr. Shaukat is a Member of the Board of Trustees at the American College of Gastroenterology and the Chair Elect of the Clinical Practice Section at the American Gastroenterology Association Institute. She is also a Board Member of GIQUIC and serves on the Advisory Panel of PCORI. Her involvement includes being a Member of the DEI Committee at ASCI, Chair of the GI Field Advisory Board at VHA, and a Member of the US Multi-Society Task Force on Colon Cancer.

Research Activity

Dr. Shaukat’s research is centered around clinical, epidemiological, and translational studies focusing on colorectal cancer screening, quality indicators for colonoscopy, molecular markers of post-colonoscopy colon cancer, and chemoprevention. She is currently leading comparative effectiveness trials, including studies on fecal microbiota transplants for recurrent C. difficile infection and evaluating screening modalities to enhance colorectal cancer screening programs, especially in reducing disparities. Her expertise extends to systematic review and evidence synthesis.

Clinical Activity

Dr. Shaukat dedicates 35% of her time to endoscopy and outpatient GI clinic work, focusing on gastrointestinal (GI) cancers, both hereditary and sporadic. She has a special interest in quality indicators and the development of tools and techniques to enhance colonoscopy outcomes.

Mentoring Activity

As a dedicated mentor, Dr. Shaukat serves as Co-Director of NYU CTSI’s Training Education Research and Careers Core, overseeing educational and training initiatives across NYU. She also directs the KL2 program, mentoring KL2 scholars and K awardees to achieve independent funding. Dr. Shaukat’s mentorship extends across various roles, including primary mentoring responsibilities for junior faculty, colorectal surgery, and gastroenterology fellows. Her commitment to mentorship is reflected in her publications, where she has co-authored numerous papers with her mentees, many of whom have progressed to prominent positions in the medical field.

Teaching Activities

Dr. Shaukat plays a significant role in teaching and curriculum development. She co-directs the K to R Scholars Program at NYU and has been involved in teaching colon cancer topics to second-year medical students. Her past roles include serving as Site Director for trainee rotations at the VA Medical Center in Minneapolis, MN, and developing curriculum and journal club lectures for GI fellows.

Continuing Medical Education

Dr. Shaukat has been actively involved in continuing medical education, serving as Course Director for various ASGE and American College of Gastroenterology postgraduate courses. Her contributions to medical education extend to her role as faculty for regional conferences and her involvement in educational affairs and peer review committees.

 

Publications

Effect of ginger supplementation on the fecal microbiome in subjects with prior colorectal adenoma

  • Authors: Prakash, A., Rubin, N., Staley, C., Church, T.R., Prizment, A.
  • Journal: Scientific Reports
  • Year: 2024

Adenomas and Sessile Serrated Lesions in 45- to 49-Year-Old Individuals Undergoing Colonoscopy: A Systematic Review and Meta-Analysis

  • Authors: Abdallah, M., Mohamed, M.F.H., Abdalla, A.O., Bilal, M., Shaukat, A.
  • Journal: American Journal of Gastroenterology
  • Year: 2024

Incidence of lymph node metastases in colon cancer: does primary tumor location matter?

  • Authors: Weaver, L., Mott, S.L., Thatipelli, S., Shaukat, A., Goffredo, P.
  • Journal: Journal of Gastrointestinal Surgery
  • Year: 2024

Multilevel Interventions to Improve Colorectal Cancer Screening in an Urban Native American Community: A Pilot Randomized Clinical Trial

  • Authors: Shaukat, A., Wolf, J., Rudser, K., Wisdom, J.P., Church, T.R.
  • Journal: Clinical Gastroenterology and Hepatology
  • Year: 2024

Prevalence of Sessile Serrated Lesions in Individuals With Positive Fecal Immunochemical Test Undergoing Colonoscopy: Results From a Large Nationwide Veterans Affairs Database

  • Authors: Wilson, N., Bilal, M., Westanmo, A., Gravely, A., Shaukat, A.
  • Journal: Gastroenterology
  • Year: 2024

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

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Hoonsoo Lee | Applications of Computer Vision | Best Researcher Award

Hoonsoo Lee at Chungbuk National University, South Korea

Profiles

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 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

Rym-Ammar-Applications of Computer Vision-Best Researcher Award 

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Dr. Rym-Ammar-Applications of Computer Vision-Best Researcher Award 

Esprit School of Business-Tunisia 

Author Profile

Early Academic Pursuits

Dr. Rym Ammar Ayachi's academic journey reflects a profound dedication to understanding and contributing to the fields of finance, economics, and management. Commencing with her Master 2 Research in Financial Markets and Intermediaries from the prestigious Toulouse School of Economics in 2008, Rym demonstrated an early inclination towards scholarly rigor and depth. This foundation was further fortified by her pursuit of a Ph.D. in Management at the ISG of Sousse/University of Sousse, culminating in her doctoral thesis titled "On the Sustainability of Islamic Banks: A Theoretical and Empirical Analysis" in 2017.

Professional Endeavors

Dr. Rym Ammar professional trajectory seamlessly blends teaching and research, showcasing her multifaceted expertise and commitment to knowledge dissemination. From her role as a Contractual Teaching Assistant at the Higher Institute of Transport and Logistics of Sousse (ISTLS) to her tenure as an Assistant Professor at Esprit School of Business (ESB), Rym has consistently engaged with students and peers alike, nurturing academic growth and fostering a culture of excellence. Her diverse teaching portfolio spans subjects such as Statistics, Marketing Data Analysis, and Data Analysis & Decision Making, reflecting her adaptability and proficiency across disciplines.

Contributions and Research Focus

At the heart of Dr. Rym Ammar academic pursuits lies a fervent dedication to advancing knowledge and addressing contemporary challenges. Her research endeavors, encapsulated in her doctoral thesis on Islamic banking sustainability, underscore her commitment to exploring nuanced intersections between finance, ethics, and sustainability. Furthermore, her involvement in the development of the statistics program at ISTLS highlights her proactive approach towards curriculum enhancement and academic innovation.

Accolades and Recognition

Dr. Rym Ammar contributions have garnered recognition from both academic and professional spheres. The affiliation with institutions of repute such as the University of Toulouse 1 Capitole and Toulouse School of Economics underscores her scholarly pedigree. Moreover, her participation in esteemed conferences and events, such as the 8th International Conference on Arabic Language Processing, reflects her standing as a thought leader in her field.

Rym Ammar's groundbreaking work in computer vision has earned her prestigious recognition, exemplified by the Applications of Computer Vision Award. Her innovative research has pushed the boundaries of computer vision applications, paving the way for transformative advancements in various fields. Leveraging cutting-edge techniques, Rym's contributions have revolutionized how we perceive and interact with visual data, leaving an indelible mark on the forefront of technological innovation.

Impact and Influence

Dr. Rym Ammar influence extends beyond the confines of academia, permeating into the realms of research dissemination and scholarly discourse. As a reviewer for esteemed journals like the Journal of International Financial Markets, Institutions & Money, she plays a pivotal role in shaping the trajectory of academic scholarship. Her supervision and evaluation activities further amplify her impact, nurturing the next generation of scholars and fostering a culture of academic excellence.

Legacy and Future Contributions

Looking ahead, Dr. Rym Ammar legacy is poised to endure through her continued dedication to research, teaching, and community engagement. As she navigates the ever-evolving landscape of academia, her commitment to pushing the boundaries of knowledge and fostering interdisciplinary dialogue will undoubtedly leave an indelible mark on the scholarly community. Through her unwavering pursuit of excellence, Rym Ammar Ayachi stands as a beacon of inspiration for aspiring scholars and educators alike, shaping the contours of academia for generations to come.

Notable Publication

Applications of Computer Vision

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Introduction of Applications of Computer Vision

Applications of Computer Vision represent a diverse and ever-expanding landscape of practical uses for visual data analysis and interpretation. Computer vision technology has transitioned from the realm of research to real-world solutions, impacting industries ranging from healthcare and automotive to entertainment and agriculture. These applications harness the power of computer vision to enhance efficiency, accuracy, and automation in various domains.

Subtopics in Applications of Computer Vision:

  1. Autonomous Vehicles: Computer vision is a cornerstone of autonomous driving systems, enabling vehicles to perceive and understand their environment through cameras and sensors. This technology is pivotal for safe navigation, obstacle detection, and lane keeping.
  2. Medical Imaging: In healthcare, computer vision aids in the diagnosis and treatment of diseases by analyzing medical images such as X-rays, CT scans, and MRIs. Applications include tumor detection, organ segmentation, and pathology analysis.
  3. Face Recognition and Biometrics: Computer vision is employed in facial recognition systems for security, authentication, and identity verification in various contexts, including smartphone unlocking, access control, and law enforcement.
  4. Retail and E-commerce: Computer vision enhances shopping experiences with applications like cashier-less stores, product recommendation systems, and inventory management through image recognition and object tracking.
  5. Agriculture and Precision Farming: Computer vision assists farmers in crop monitoring, disease detection, and yield prediction. Drones equipped with cameras provide valuable insights into the health of crops and soil.
  6. Augmented Reality (AR) and Virtual Reality (VR): AR and VR applications rely heavily on computer vision to overlay digital information onto the real world or create immersive virtual environments, offering innovative experiences in gaming, education, and training.
  7. Industrial Automation and Quality Control: In manufacturing, computer vision is used for quality inspection, defect detection, and process optimization, ensuring product quality and reducing production costs.
  8. Surveillance and Security: Computer vision plays a critical role in video surveillance, enabling real-time monitoring, suspicious activity detection, and facial recognition in public spaces and critical infrastructure.
  9. Document Analysis and OCR: Optical Character Recognition (OCR) technology leverages computer vision to extract text and information from scanned documents, making it essential for digitization and data retrieval in offices and archives.
  10. Environmental Monitoring: Computer vision is used for monitoring and analyzing environmental data, such as wildlife tracking, weather forecasting, and pollution detection, to support conservation efforts and disaster management.

These applications exemplify the versatility and impact of computer vision technology across diverse sectors. As research and development in computer vision continue to advance, we can expect even more innovative and transformative applications in the future.

Object Detection and Recognition
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Computer Vision for Robotics and Autonomous Systems
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Medical Image Analysis
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Video Analysis
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Deep Learning for Computer Vision
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Applications of Computer Vision
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Human-Computer Interaction
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Biometrics and Security
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