Dongheon Lee | Medical Image Analysis | Best Researcher Award

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Prof . Dr . Dongheon Lee | Medical Image Analysis | Best Researcher Award

Assistant Professor at Seoul National University / College of Medicine, South Korea

Dr. Dongheon Lee is an Assistant Professor in the Department of Radiology at Seoul National University College of Medicine, with a joint appointment in the Interdisciplinary Program in Bioengineering. He specializes in medical image analysis, deep learning, and computer vision, with a strong emphasis on clinically relevant AI systems. His academic journey is deeply rooted in bioengineering, having completed both his M.S. and Ph.D. at Seoul National University. Dr. Lee has a proven record of innovation, evidenced by multiple high-impact publications and patents, many of which contribute directly to enhancing diagnostic accuracy and clinical workflow. He has served in leadership roles, including Deputy Director at Chungnam National University’s research institutes and active committee memberships. His research has received several national and international accolades, demonstrating both depth and translational impact. He continues to drive forward advancements at the intersection of AI and medical practice, with a focus on diagnostic technologies and clinical decision support.

Professional Profile 

Education🎓 

Dr. Dongheon Lee’s educational foundation is built on interdisciplinary expertise in bioengineering and medical imaging. He earned his Ph.D. in Bioengineering from Seoul National University in 2020, under the mentorship of Professor Hee Chan Kim. His doctoral research, titled “Deep Learning Approaches for Clinical Performance Improvement: Applications to Colonoscopic Diagnosis and Robotic Surgical Skill Assessment”, reflects his early focus on practical, AI-based clinical solutions. Prior to that, he completed his M.S. in the same interdisciplinary program at Seoul National University in 2015, where he also concentrated on medical image analysis. His academic journey began with a B.S. degree in Electronic System Engineering from Hanyang University in 2013, providing him with a strong technical foundation in systems engineering and computational methods. This combination of engineering, medicine, and AI has shaped his approach to research and allowed him to work at the intersection of technology and clinical application with considerable effectiveness.

Professional Experience📝

Dr. Dongheon Lee has held multiple academic and research roles that showcase a steady progression in responsibility and impact. He currently serves as an Assistant Professor in the Department of Radiology at Seoul National University College of Medicine. Prior to this, he was an Assistant Professor in the Department of Biomedical Engineering at Chungnam National University from 2021 to 2025. During that time, he also served as Deputy Director at both the Biomedical Engineering Research Institute and the Big Data Center at Chungnam National University Hospital. Earlier in his career, Dr. Lee worked as a Research Assistant Professor and Research Specialist at the Biomedical Research Institute of Seoul National University Hospital. These roles have enabled him to gain comprehensive experience across clinical, academic, and data-intensive research environments. His career reflects a sustained commitment to developing AI solutions for healthcare, combining technical skill with clinical relevance in both research and educational settings.

Research Interest🔎

Dr. Dongheon Lee’s research interests lie at the intersection of medical image analysis, artificial intelligence, and computer vision, with a strong focus on clinical application. He is particularly invested in developing deep learning frameworks for diagnostic accuracy, disease classification, and surgical skill assessment. His work addresses real-world challenges in radiology and endoscopy, such as colorectal polyp detection and lung cancer screening, through robust AI-driven solutions. Dr. Lee is also deeply interested in uncertainty quantification, out-of-distribution detection, and the interpretability of AI models in clinical workflows. His research aims to make AI not only accurate but also explainable and trustworthy in medical environments. By integrating multimodal data and advanced visualization techniques, he seeks to improve human-AI collaboration in diagnosis and treatment planning. His ongoing projects involve 3D anatomical modeling, radiograph-based biological age estimation, and virtual simulation technologies, all of which reflect his mission to bridge engineering innovation with practical healthcare delivery.

Award and Honor🏆

Dr. Dongheon Lee has received multiple prestigious awards that underscore the impact and innovation of his research. In 2023, he was honored with the Medical Research Academic Award from Chungnam National University Hospital, recognizing his contributions to clinical imaging research. The same year, he was a winner in the MICCAI Grand Challenge (LDCTIQAC 2023), a significant achievement in the international medical image computing community. Earlier, in 2020, he received both the Outstanding Paper Award from Seoul National University Hospital and the ICT Colloquium Minister of Science and ICT Award, conferred by the Korean government and the Institute for Information & Communications Technology Planning & Evaluation (IITP). These awards highlight his excellence in both academic and applied domains, demonstrating a consistent ability to innovate in healthcare technologies. His achievements reflect strong peer recognition and align with his commitment to advancing artificial intelligence in real-world medical settings.

Research Skill🔬

Dr. Dongheon Lee possesses a robust and diverse set of research skills that bridge engineering, medical imaging, and artificial intelligence. He is highly proficient in deep learning model development for classification, detection, segmentation, and uncertainty estimation tasks, particularly in the context of radiological and endoscopic data. His expertise extends to algorithmic optimization, multi-modal data fusion, and computational modeling, with a focus on practical deployment in clinical workflows. Dr. Lee is experienced in designing and validating AI systems with real-world datasets, ensuring clinical relevance and regulatory compliance. He has also developed patented technologies for 3D anatomical mapping, lesion tracking, and endoscopic path guidance. Additionally, he demonstrates strong capabilities in interdisciplinary collaboration, leading cross-functional teams in bioengineering, computer science, and clinical departments. His skills in grant writing, manuscript preparation, and research leadership complement his technical acumen, enabling him to contribute meaningfully to both academic advancement and translational medical innovation.

Conclusion💡

Dr. Dongheon Lee is exceptionally qualified and stands out as a top-tier candidate for the Best Researcher Award. His research has made tangible impacts in clinical medicine, particularly through AI-driven diagnostics and medical imaging. The combination of high-impact publications, innovation through patents, and recognized academic leadership makes his profile exemplary.

With minor enhancements in global outreach and broader authorship representation, he could further solidify his stature as a global leader in biomedical AI.

Publications Top Noted✍

  • Title: Improved accuracy in optical diagnosis of colorectal polyps using convolutional neural networks with visual explanations
    Authors: EH Jin, D Lee, JH Bae, HY Kang, MS Kwak, JY Seo, JI Yang, SY Yang, …
    Year: 2020
    Citations: 137

  • Title: Evaluation of surgical skills during robotic surgery by deep learning-based multiple surgical instrument tracking in training and actual operations
    Authors: D Lee, HW Yu, H Kwon, HJ Kong, KE Lee, HC Kim
    Year: 2020
    Citations: 104

  • Title: CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates
    Authors: H Kim, D Lee, WS Cho, JC Lee, JM Goo, HC Kim, CM Park
    Year: 2020
    Citations: 49

  • Title: Vision-based tracking system for augmented reality to localize recurrent laryngeal nerve during robotic thyroid surgery
    Authors: D Lee, HW Yu, S Kim, J Yoon, K Lee, YJ Chai, JY Choi, HJ Kong, KE Lee, …
    Year: 2020
    Citations: 29

  • Title: Deep learning to optimize candidate selection for lung cancer CT screening: advancing the 2021 USPSTF recommendations
    Authors: JH Lee, D Lee, MT Lu, VK Raghu, CM Park, JM Goo, SH Choi, H Kim
    Year: 2022
    Citations: 28

  • Title: Preliminary study on application of augmented reality visualization in robotic thyroid surgery
    Authors: D Lee, HJ Kong, D Kim, JW Yi, YJ Chai, KE Lee, HC Kim
    Year: 2018
    Citations: 27

  • Title: Estimating maximal oxygen uptake from daily activity data measured by a watch-type fitness tracker: cross-sectional study
    Authors: SB Kwon, JW Ahn, SM Lee, J Lee, D Lee, J Hong, HC Kim, HJ Yoon
    Year: 2019
    Citations: 23

  • Title: Augmented reality to localize individual organ in surgical procedure
    Authors: D Lee, JW Yi, J Hong, YJ Chai, HC Kim, HJ Kong
    Year: 2018
    Citations: 23

  • Title: Online learning for the hyoid bone tracking during swallowing with neck movement adjustment using semantic segmentation
    Authors: D Lee, WH Lee, HG Seo, BM Oh, JC Lee, HC Kim
    Year: 2020
    Citations: 21

  • Title: Endoscopists performance in optical diagnosis of colorectal polyps in artificial intelligence studies
    Authors: S Pecere, G Antonelli, M Dinis‐Ribeiro, Y Mori, C Hassan, L Fuccio, …
    Year: 2022
    Citations: 17

  • Title: Low-dose computed tomography perceptual image quality assessment
    Authors: W Lee, F Wagner, A Galdran, Y Shi, W Xia, G Wang, X Mou, MA Ahamed, …
    Year: 2025
    Citations: 13

  • Title: Enhancing artificial intelligence-doctor collaboration for computer-aided diagnosis in colonoscopy through improved digital literacy
    Authors: Y Mori, EH Jin, D Lee
    Year: 2024
    Citations: 10

  • Title: Practical training approaches for discordant atopic dermatitis severity datasets: merging methods with soft-label and train-set pruning
    Authors: SI Cho, D Lee, B Han, JS Lee, JY Hong, JH Chung, DH Lee, JI Na
    Year: 2022
    Citations: 10

  • Title: Reliability of suprahyoid and infrahyoid electromyographic measurements during swallowing in healthy subjects
    Authors: MW Park, D Lee, HG Seo, TR Han, JC Lee, HC Kim, BM Oh
    Year: 2021
    Citations: 8

  • Title: Essential elements of physical fitness analysis in male adolescent athletes using machine learning
    Authors: YH Lee, J Chang, JE Lee, YS Jung, D Lee, HS Lee
    Year: 2024
    Citations: 7

  • Title: External testing of a deep learning model to estimate biologic age using chest radiographs
    Authors: JH Lee, D Lee, MT Lu, VK Raghu, JM Goo, Y Choi, SH Choi, H Kim
    Year: 2024
    Citations: 5

  • Title: Effect of an anti-adhesion agent on vision-based assessment of cervical adhesions after thyroid surgery: randomized, placebo-controlled trial
    Authors: HW Yu, D Lee, K Lee, S Kim, YJ Chai, HC Kim, JY Choi, KE Lee
    Year: 2021
    Citations: 5

  • Title: Augmented Reality-Based Visual Cue for Guiding Central Catheter Insertion in Pediatric Oncologic Patients
    Authors: JK Youn, D Lee, D Ko, I Yeom, HJ Joo, HC Kim, HJ Kong, HY Kim
    Year: 2022
    Citations: 4

  • Title: Texture-preserving low dose CT image denoising using Pearson divergence
    Authors: J Oh, D Wu, B Hong, D Lee, M Kang, Q Li, K Kim
    Year: 2024
    Citations: 2

  • Title: Optimal view detection for ultrasound-guided supraclavicular block using deep learning approaches
    Authors: Y Jo, D Lee, D Baek, BK Choi, N Aryal, J Jung, YS Shin, B Hong
    Year: 2023
    Citations: 2

Yuanyuan QIN | Medical Image Analysis | Best Researcher Award

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Dr . Yuanyuan QIN | Medical Image Analysis | Best Researcher Award

Associate Chief Physician, Associate Professor at  Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology , China

Dr. Yuanyuan Qin is a distinguished Associate Chief Physician and Associate Professor in the Department of Radiology at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. With a strong foundation in clinical radiology and advanced neuroimaging, she has dedicated her career to investigating brain disorders such as Alzheimer’s disease, Parkinson’s disease, and post-COVID neurological changes. Her research integrates multimodal imaging techniques with cognitive neuroscience and machine learning, emphasizing non-invasive diagnostic innovations. A recipient of national research funding and provincial awards, Dr. Qin has published extensively in leading international journals, with several high-impact and highly cited articles. She has also demonstrated leadership in academic teaching through the adoption of blended learning methodologies. Her interdisciplinary expertise, clinical insights, and research productivity make her a recognized contributor to the fields of radiology and neuroscience, with ongoing work focused on understanding neural mechanisms underlying cognitive decline and aging-related diseases.

Professional Profile 

Education🎓

Dr. Yuanyuan Qin pursued her advanced medical education at Huazhong University of Science and Technology, completing a prestigious Combined Master-PhD program between 2008 and 2013. Her doctoral training emphasized advanced neuroimaging techniques, with research exploring structural and functional brain alterations in neurodegenerative conditions. During her PhD, she was selected for a one-year joint PhD training program at the esteemed Johns Hopkins University in the United States (2011–2012), where she gained international exposure to state-of-the-art imaging methodologies and collaborative research environments. Her interdisciplinary education integrated clinical radiology, neuroscience, and data-driven analysis, laying a strong foundation for her later research on cognitive disorders and aging. This cross-institutional and cross-national academic background not only enriched her scientific expertise but also cultivated her capacity to approach radiological challenges from both a clinical and research perspective. Her academic training continues to inform her innovative work in diagnostic imaging and cognitive neurodegeneration.

Professional Experience📝

Dr. Yuanyuan Qin has built a progressive and impactful professional career in radiology at Tongji Hospital. Starting in 2013 as a Resident Physician, she rapidly advanced through roles as an Attending Physician (2014–2019), Associate Chief Physician (2019–2020), and ultimately to Associate Professor (2020–present). Throughout her career, she has been deeply engaged in clinical diagnostics, medical imaging interpretation, and mentoring medical students and interns. Her dual roles in academic and clinical settings have allowed her to integrate patient-centered care with research-led innovation. Dr. Qin’s experience spans routine radiological evaluations to complex imaging studies in patients with neurological and neurodegenerative conditions. She has actively contributed to improving radiology internship training programs through digital platforms and 3D simulation tools. Her leadership within the department is recognized not only in her clinical acumen but also in fostering collaborative research projects and guiding junior physicians and researchers in translational imaging studies.

Research Interest🔎

Dr. Yuanyuan Qin’s research interests lie at the intersection of neuroimaging, cognitive neuroscience, and clinical radiology. Her primary focus is on understanding the neural mechanisms of neurodegenerative diseases, particularly Alzheimer’s and Parkinson’s, through advanced magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and functional connectivity analysis. She is also deeply interested in the application of repetitive transcranial magnetic stimulation (rTMS) combined with cognitive training as a therapeutic and diagnostic tool. Recently, her research has extended into the neurological impacts of COVID-19, exploring long-term cerebral microstructure changes in asymptomatic patients. Her work frequently integrates artificial intelligence, deep learning, and image quantification methods to improve diagnostic precision. Dr. Qin is committed to developing non-invasive imaging biomarkers that can track disease progression and predict cognitive decline. Her interdisciplinary approach bridges clinical needs with technological advancement, contributing valuable insights into early detection and intervention strategies for aging-related cognitive disorders.

Award and Honor🏆

Dr. Yuanyuan Qin has been widely recognized for her academic excellence and scientific contributions. Notably, she received the First Prize in the 2019 Hubei Provincial Science and Technology Progress Award for her innovative work on the integration of structural and functional MRI in brain development and aging-related diseases. In teaching, she earned the Second Prize in the 2020 Young Teacher Teaching Competition at Huazhong University of Science and Technology, highlighting her commitment to educational innovation. As a principal investigator, she has secured multiple competitive grants, including a General Program and a Youth Project from the National Natural Science Foundation of China (NSFC). Her work has garnered national attention and peer acknowledgment, with multiple publications cited widely in top-tier journals. Her research article in the Journal of Clinical Investigation is listed as a Highly Cited Article, further validating her impact in the fields of radiology and neuroscience.

Research Skill🔬

Dr. Yuanyuan Qin possesses a robust portfolio of research skills, especially in neuroimaging analysis, multimodal MRI, and diffusion tensor imaging (DTI). She has extensive expertise in image processing platforms such as 3D-Slicer, FSL, and SPM, along with experience in deep learning algorithms for radiological quantification. Her technical strengths extend to designing and conducting longitudinal studies, particularly in evaluating cognitive interventions like rTMS paired with cognitive training in Alzheimer’s patients. She demonstrates proficiency in integrating clinical data with imaging outcomes to derive meaningful correlations for disease diagnosis and prognosis. Additionally, she has contributed to the development of automated MRI quantification pipelines, including those for Parkinsonism index assessment. Her interdisciplinary methods often incorporate statistical modeling, functional connectivity analysis, and AI-based imaging biomarker discovery. These research capabilities position her as a key contributor in translating complex neuroimaging insights into real-world clinical applications.

Conclusion💡

Dr. Yuanyuan Qin is highly suitable for the Best Researcher Award based on her exceptional track record in neuroimaging research, consistent national-level funding, scientific leadership in Alzheimer’s and Parkinson’s research, and significant contributions to radiological education and practice. Her trajectory exemplifies a balance between academic rigor, innovation, and clinical relevance.

Publications Top Noted✍

  1. Title: Surface-Based Vertexwise Analysis of Morphometry and Microstructural Integrity for White Matter Tracts in Diffusion Tensor Imaging: With Application to the Corpus Callosum in Alzheimer’s Disease
    Authors: Tang, Xiaoying; Qin, Yuanyuan; Zhu, Wenzhen; Miller, Michael I.
    Year: 2017
    Citation: Human Brain Mapping, DOI: 10.1002/hbm.23491

  2. Title: Atlas-based deep gray matter and white matter analysis in Alzheimer’s disease: diffusion abnormality and correlation with cognitive function
    Authors: Qin Yuanyuan; Zhang Shun; Guo Linying; Zhang Min; Zhu Wenzhen
    Year: 2016
    Citation: Chinese Journal of Radiology, WOSUID: CSCD:5699935

  3. Title: Shape and diffusion tensor imaging based integrative analysis of the hippocampus and the amygdala in Alzheimer’s disease
    Authors: Tang, Xiaoying; Qin, Yuanyuan; Wu, Jiong; Zhang, Min; Zhu, Wenzhen; Miller, Michael I.
    Year: 2016
    Citation: Magnetic Resonance Imaging, DOI: 10.1016/j.mri.2016.05.001

  4. Title: Simulating the Evolution of Functional Brain Networks in Alzheimer’s Disease: Exploring Disease Dynamics from the Perspective of Global Activity
    Authors: Li, Wei; Wang, Miao; Zhu, Wenzhen; Qin, Yuanyuan; Huang, Yue; Chen, Xi
    Year: 2016
    Citation: Scientific Reports, DOI: 10.1038/srep34156

  5. Title: Frequency-specific Alterations of Large-scale Functional Brain Networks in Patients with Alzheimer’s Disease
    Authors: Qin, Yuan-Yuan; Li, Ya-Peng; Zhang, Shun; Xiong, Ying; Guo, Lin-Ying; Yang, Shi-Qi; Yao, Yi-Hao; Li, Wei; Zhu, Wen-Zhen
    Year: 2015
    Citation: Chinese Medical Journal, DOI: 10.4103/0366-6999.151654

  6. Title: Frequency-specific Alterations of Large-scale Functional Brain Networks in Patients with Alzheimer’s Disease (Correction)
    Authors: Qin, Y. Y.; Li, Y. P.; Zhang, S.; Xiong, Y.; Guo, L. Y.; Yang, S. Q.
    Year: 2015
    Citation: Chinese Medical Journal, DOI: 10.4103/0366-6999.156150

  7. Title: An Efficient Approach for Differentiating Alzheimer’s Disease from Normal Elderly Based on Multicenter MRI Using Gray-Level Invariant Features
    Authors: Li, Muwei; Oishi, Kenichi; He, Xiaohai; Qin, Yuanyuan; Gao, Fei; Mori, Susumu
    Year: 2014
    Citation: PLOS ONE, DOI: 10.1371/journal.pone.0105563

  8. Title: Discriminative Analysis of Multivariate Features from Structural MRI and Diffusion Tensor Images
    Authors: Li, Muwei; Qin, Yuanyuan; Gao, Fei; Zhu, Wenzhen; He, Xiaohai
    Year: 2014
    Citation: Magnetic Resonance Imaging, DOI: 10.1016/j.mri.2014.05.008

  9. Title: Exploring the Functional Brain Network of Alzheimer’s Disease: Based on the Computational Experiment
    Authors: Li, YaPeng; Qin, Yuanyuan; Chen, Xi; Li, Wei
    Year: 2013
    Citation: PLOS ONE, DOI: 10.1371/journal.pone.0073186

  10. Title: Gross Feature Recognition of Anatomical Images Based on Atlas Grid (GAIA)
    Authors: Qin, Yuan-Yuan; Hsu, Johnny T.; Yoshida, Shoko; Faria, Andreia V.; Oishi, Kumiko; et al.
    Year: 2013
    Citation: NeuroImage: Clinical, DOI: 10.1016/j.nicl.2013.08.006

  11. Title: In vivo Quantitative Whole-brain Diffusion Tensor Imaging Analysis of APP/PS1 Transgenic Mice
    Authors: Qin, Yuan-Yuan; Li, Mu-Wei; Zhang, Shun; Zhang, Yan; Zhao, Ling-Yun; et al.
    Year: 2013
    Citation: Neuroradiology, DOI: 10.1007/s00234-013-1195-0

  12. Title: The Functional Brain Network Changes of Alzheimer’s Disease
    Authors: Li YaPeng; Qin YuanYuan; Li Wei
    Year: 2013
    Citation: Chinese Journal of Medical Physics, WOSUID: CSCD:5004621

  13. Title: Voxel-Based Diffusion Tensor Imaging of an APP/PS1 Mouse Model of Alzheimer’s Disease
    Authors: Shu, Xiaogang; Qin, Yuan-Yuan; Zhang, Shun; Jiang, Jing-Jing; Zhang, Yan; et al.
    Year: 2013
    Citation: Molecular Neurobiology, DOI: 10.1007/s12035-013-8418-6

  14. Title: Stromal Cell-Derived Factor 1 Alpha Decreases Beta-Amyloid Deposition in Alzheimer’s Disease Mouse Model
    Authors: Wang, Qi; Xu, Yi; Chen, Jin-Cao; Qin, Yuan-Yuan; Liu, Mao; et al.
    Year: 2012
    Citation: Brain Research, DOI: 10.1016/j.brainres.2012.04.011

 

Bharati Chaudhari | Edge Detection | Best Researcher Award

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Ms . Bharati Chaudhari | Edge Detection | Best Researcher Award

Assitstant Professor at Maharashtra Institute of Technology, Chh. Sambhajinagar, India

Ms. Bharati Prakash Chaudhari is an experienced academician and researcher with over 18 years of teaching experience in computer science and engineering. Currently serving as an Assistant Professor at MIT, Aurangabad, she has consistently demonstrated a strong commitment to research and education. Her expertise spans image processing, machine learning, and digital system development, with active contributions to both academic research and industry-oriented projects. She has authored multiple research papers in international journals and conferences, including Scopus-indexed publications and IEEE proceedings. Additionally, her involvement in intellectual property development through several copyrights underscores her original contributions to technical education. Ms. Chaudhari continues to pursue her Ph.D. in Computer Science and Engineering at Dr. Babasaheb Ambedkar Marathwada University, reflecting her dedication to academic growth. Her work bridges theoretical knowledge with practical application, particularly through collaborations with industry for digital tool development. She is a proactive, skilled, and forward-looking researcher shaping the field of computer engineering.

Professional Profile 

Education🎓

Ms. Bharati Prakash Chaudhari holds a Master of Engineering degree in Computer Science and Engineering from Government College of Engineering, Aurangabad, affiliated with Dr. Babasaheb Ambedkar Marathwada University (Dr. B.A.M.U.), where she graduated in 2010 with distinction, scoring 81.25%. She earned her Bachelor of Engineering in Computer Engineering from K.K. Wagh College of Engineering, Nashik under Pune University in 2003, securing first-class marks with 62.2%. Currently, she is pursuing her Ph.D. in Computer Science and Engineering from Dr. B.A.M.U., Aurangabad. Her academic background showcases a steady progression through well-regarded institutions and reflects a continuous pursuit of advanced knowledge in her domain. Her postgraduate studies have equipped her with a solid foundation in algorithm development, computational models, and system-level design. The ongoing doctoral research further strengthens her analytical and research capabilities, positioning her to contribute meaningfully to emerging trends in machine learning and image processing.

Professional Experience📝

Ms. Bharati Prakash Chaudhari has over 18 years of professional academic experience in engineering education. She began her teaching career in February 2003 at MIT IT College, Cidco, Aurangabad, serving as a Lecturer for over three years. Since July 2006, she has been affiliated with MIT, Aurangabad, initially as a Lecturer and later redesignated as an Assistant Professor. Throughout her tenure, she has taught various core subjects in computer science and engineering and actively engaged in curriculum development and mentoring students. Her long-standing commitment to teaching is complemented by her involvement in research, project guidance, and departmental responsibilities. She has also contributed to industry-academic collaboration through participation in projects like digital tool development for transformer design, under GIZ–MASSIA initiatives. Ms. Chaudhari’s experience demonstrates not only her academic dedication but also her ability to integrate applied engineering practices into her educational approach, enhancing student learning and research culture.

Research Interest🔎

Ms. Bharati Prakash Chaudhari’s research interests center around Image Processing, Machine Learning, and Optimization Algorithms, with a keen focus on applying intelligent computing methods to solve practical problems in healthcare and security. Her recent work on edge detection using Ant Colony Optimization for medical images illustrates her interest in bio-medical image analysis. She also explores areas such as reversible data hiding, digital watermarking, and encrypted image processing—topics that are critical to data security and digital forensics. Her Ph.D. research and publications reflect an effort to integrate biologically inspired algorithms into traditional image processing techniques. Moreover, she has shown a consistent interest in enhancing data representation, pattern recognition, and system intelligence. Through hybrid algorithm development and advanced segmentation techniques, Ms. Chaudhari aims to push the boundaries of image understanding and machine learning applications, particularly in domains where accurate visual interpretation is crucial, such as diagnostics, surveillance, and automation.

Award and Honor🏆

Ms. Bharati Prakash Chaudhari has been recognized for her scholarly contributions through multiple Intellectual Property Rights (IPRs) registrations, including copyrights on algorithmic learning materials and applied computer science concepts such as Dijkstra’s Algorithm, Histogram Equalization, and Finite Automata Design. These IPRs reflect her dedication to developing high-quality, original educational content and research outputs. While formal academic awards are not explicitly listed, her achievements in publishing papers in Scopus-indexed journals and prestigious conferences like IEEE and Elsevier Procedia signify academic excellence. Her active involvement in applied research projects, such as the Digital Tool Development for Transformer Design under a government-industry partnership (GIZ-MASSIA), further underscores her practical impact. Through these achievements, she has earned peer recognition within academic and industrial circles. Her participation in international events and successful collaborations with senior researchers demonstrate her growing reputation as a capable and emerging researcher in the field of computer engineering.

Research Skill🔬

Ms. Bharati Prakash Chaudhari possesses strong research skills across multiple domains of computer science, particularly in image analysis, optimization algorithms, and machine learning models. She is proficient in applying Ant Colony Optimization, ICA (Independent Component Analysis), and encryption-based data hiding techniques for real-world problems. Her skill set includes the ability to design experimental methodologies, simulate and validate results, and interpret complex datasets for image processing tasks. She is adept at using MATLAB and other relevant software tools for developing and testing algorithms. Additionally, she is capable of translating conceptual ideas into practical implementations, as evident in her industry collaboration for transformer design automation. Her copyright registrations for algorithmic content reflect her strength in educational research and tool development. With a foundation in both academic writing and hands-on experimentation, Ms. Chaudhari’s research competencies bridge theoretical understanding and applied problem-solving—making her a valuable contributor to innovation-driven computing research.

Conclusion💡

Ms. Bharati Prakash Chaudhari is a strong candidate for the Best Researcher Award, especially given her longevity in academia, publication record, IPRs, and participation in reputed conferences. However, to be a top-tier awardee, finalizing her Ph.D. and enhancing her presence in globally ranked journals, along with measurable citation metrics, would make her profile even more competitive.

Publications Top Noted✍

  • Title: Hepatoprotective activity of Hydroalcoholic extract of Momordica charantia Linn. leaves against Carbon tetrachloride induced Hepatopathy in Rats
    Authors: KRB, Chaudhari BP, VJ Chaware, YR Joshi
    Year: 2009
    Citations: 45

  • Title: Protective effect of the aqueous extract of Momordica charantia leaves on gentamicin induced nephrotoxicity in rats
    Authors: KRB, VJ Chaware, BP Chaudhary, MK Vaishnav
    Year: 2011
    Citations: 20

  • Title: Protective effect of the aqueous extract of Phaseolus radiatus seeds on gentamicin induced nephrotoxicity in rats
    Authors: VJ Chaware
    Year: 2012
    Citations: 16

  • Title: Quality by design (QbD) concept review in pharmaceuticals
    Authors: K Jagtap, B Chaudhari, V Redasani
    Year: 2022
    Citations: 11

  • Title: Development and validation of spectrophotometric method for simultaneous estimation of meclizine hydrochloride and pyridoxine hydrochloride in tablet dosage form
    Authors: SA Shinde, ZM Sayyed, BP Chaudhari, VJ Chaware, KR Biyani
    Year: 2016
    Citations: 10

  • Title: Development and validation of UV-spectrophotometric method for simultaneous estimation of amlodipine besylate and hydrochlorothiazide in combined dosage form
    Authors: Z Sayyed, S Shinde, V Chaware, B Chaudhari, K Biyani
    Year: 2015
    Citations: 9

  • Title: A cross-sectional prescription audit database for anti-anginal drugs with impact of essential drug list and standard treatment guidelines on prescription pattern in Nasik city
    Authors: V Chaudhari, B Chaudhari, A Khairnar
    Year: 2011
    Citations: 7

  • Title: Approaches of digital image watermarking using ICA
    Authors: BP Chaudhari, AK Gulve
    Year: 2010
    Citations: 7

  • Title: A Review on in situ Gel of Gastro Retentive Drug Delivery System
    Authors: BV Aiwale, BP Chaudhari, AB Velhal, VK Redasani
    Year: 2022
    Citations: 6

  • Title: Image segmentation using hybrid ant colony optimization: A review
    Authors: B Chaudhari, P Shetiye, A Gulve
    Year: 2021
    Citations: 6

  • Title: A Review on Diverging approaches to Fabricate Polymeric Nanoparticles
    Authors: S Deshmukh, B Chaudhari, A Velhal, V Redasani
    Year: 2022
    Citations: 5

  • Title: A Validated RP-HPLC Method for Simultaneous Estimation of Tizanidine and Nimesulide in Bulk and Pharmaceutical Formulation
    Authors: KD Bharatee Chaudhari
    Year: 2020
    Citations: 5

  • Title: Pharmacosome as a Vesicular Drug Delivery System
    Authors: RR Shinde, BP Chaudhari, AB Velhal, VK Redasani
    Year: 2022
    Citations: 4

  • Title: Influence of Newly Synthesized Superdisintegrant on Dissolution Rate Enhancement of Carbamazepine using Liquisolid Compact Technique
    Authors: GV Raut, PB Chaudhari, KV Redasani
    Year: 2022
    Citations: 4

  • Title: Development and validation of UV-spectrophotometric method for simultaneous estimation of spironolactone and hydrochlorothiazide in pharmaceutical formulation
    Authors: Z Sayyed, S Shinde, V Chaware, B Chaudhari, M Zuber, M Sayyed
    Year: 2015
    Citations: 4

  • Title: A compendious review on biodegradable polymeric nanoparticles
    Authors: S Deshmukh, B Chaudhari, A Velhal, V Redasani
    Year: 2022
    Citations: 3

  • Title: Cleaning Validation in Pharmaceutical Industry
    Authors: P Khalate, B Chaudhari, V Redasani
    Year: 2022
    Citations: 2

  • Title: A Novel Tool for Controlled Delivery: Transdermal Drug Delivery System
    Authors: AV Panval, BP Chaudhari, AB Velhal, VK Redasani
    Year: 2022
    Citations: 2

  • Title: A Review on Pharmaceutical Regulatory Authority of India, USA, UK, Australia
    Authors: AA Shinde, AS Gurav, BP Chaudhari, VK Redasani
    Year: 2024
    Citations: 1

  • Title: Review on Colon Targeted Drug Delivery System
    Authors: NB Waghmode, SV Dhanje, BP Chaudhari, VK Redasani
    Year: 2024
    Citations: 1

Mrs. Deepthi S | Medical Image Analysis | Best Researcher Award

Published on by Computer Vision Awards

Mrs. Deepthi S | Medical Image Analysis | Best Researcher Award

Presidency University, India

👨‍🎓 Profiles

Scopus

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Gradient Propagation Based DenseNet121 with ResNet50 Feature Extraction for Lymphoma Classification

  • Author: Srinivasan, D.; Kalaiarasan, C.
    Journal: Journal of The Institution of Engineers (India): Series B
    Year: 2024

Non Hodgkin’s Lymphoma Classification using Improved Predator Optimization Based Densenet121 Model

  • Author: Deepthi S; Dr. M. Chandrasekhar
    Journal: Journal of Electrical Systems
    Year: 2024

Harnessing ResNet50 and DenseNet201 for Enhanced Lymphoma Diagnosis via Feature Extraction

  • Author: Deepthi S; Dr. M. Chandrasekhar
    Journal: Frontiers in Health Informatics
    Year: 2024

An efficient face image retrieval system based on attribute sparse codewords

  • Author: Deepthi S
    Journal: International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES)
    Year: 2016

Dr. Yijie Ning | Medical Image Analysis | Best Researcher Award

Published on by Computer Vision Awards

Dr. Yijie Ning | Medical Image Analysis | Best Researcher Award

Doctorate at the First Hospital of Shanxi Medical University, China

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NIR-II imaging-based detection of early changes in lower limb perfusion in type 2 diabetes patients without peripheral artery disease

  • Author: Yijie Ning, Jie Hu, Yikun Zhu, Ruijing Zhang, Honglin Dong, et al.
    Journal: Diabetes Research and Clinical Practice
    Year: 2025

Prof. Krishan Kumar | Medical Image Analysis | Best Researcher Award

Published on by Computer Vision Awards

Prof. Krishan Kumar | Medical Image Analysis | Best Researcher Award

Professor at Hindu College, Amritsar, India

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Enhancing Transparency and Trust in Brain Tumor Diagnosis: An In-Depth Analysis of Deep Learning and Explainable AI Techniques

  • Authors: Krishan Kumar, Kiran Jyoti
    Journal: Preprint
    Year: 2025

Machine Learning for Brain Tumor Classification: Evaluating Feature Extraction and Algorithm Efficiency

  • Authors: Krishan Kumar, Kiran Jyoti
    Journal: Discover Artificial Intelligence
    Year: 2024

Explainable AI in Brain Tumor Diagnosis: A Critical Review of ML and DL Techniques

  • Authors: Krishan Kumar, Kiran Jyoti
    Journal: Preprint
    Year: 2024

Recent Advancements in Grad-CAM and Variants: Enhancing Brain Tumor Detection, Segmentation, and Classification

  • Authors: Krishan Kumar, Kiran Jyoti
    Journal: Preprint
    Year: 2024

A Comparative Analysis of Static and Dynamic Java Bytecode Watermarking Algorithms

  • Authors: Krishan Kumar, Prabhpreet Kaur
    Journal: Advances in Intelligent Systems and Computing
    Year: 2019

Prof. Zhitao Xiao | Medical Image Analysis | Best Researcher Award

Published on by Computer Vision Awards

Prof. Zhitao Xiao | Medical Image Analysis | Best Researcher Award

School of Life Sciences of Tiangong University, China

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MSTNet: Multi-scale spatial-aware transformer with multi-instance learning for diabetic retinopathy classification

  • Author: X. Wei, Xin; Y. Liu, Yanbei; F. Zhang, Fang; X. Cao, Xiangyu; Z. Xiao, Zhitao
    Journal: Medical Image Analysis
    Year: 2025

A Deep Learning-Based Modeling Method for Phase-Free Near-Field Scanning Measurement

  • Author: S. Zhao, Shuli; J. Wu, Jianfei; Y. Song, Yang; L. Chen, Ledong; Z. Xiao, Zhitao
    Journal: IEEE Transactions on Antennas and Propagation
    Year: 2025

Stripe Pooling and Vessel-Constraint Network for Fundus Image Artery /Vein Classification

  • Author: Z. Xiao, Zhitao; X. Peng, Xinwen; Y. Liu, Yanbei; F. Zhang, Fang; W. Wang, Wen
    Journal: Chinese Journal of Biomedical Engineering
    Year: 2024

Diabetic Retinopathy Segmentation Using Dense Dilated Attention Pyramid and Multi-Scale Features

  • Author: Z. Wang, Zhilu; Y. Chi, Yue; Y. Zhou, Yatong; Z. Xiao, Zhitao; S. Wang, Shaoqi
    Journal: Chinese Journal of Medical Physics
    Year: 2024

AGT: Enhancing Many-Body Interactions in Material Property Prediction

  • Author: L. Geng, Lei; Y. Niu, Yaxi; Z. Xiao, Zhitao; H. Yin, Huaqing
    Journal: Computational Materials Science
    Year: 2024

Ms. Yang Yuan | Medical Image Analysis | Best Researcher Award

Published on by Computer Vision Awards

Ms. Yang Yuan | Medical Image Analysis | Best Researcher Award

Chongqing University of Technology, China

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Stochastic Augmented-Based Dual-Teaching for Semi-Supervised Medical Image Segmentation

  • Authors: H. Liu, Y. Yuan, P. Ren, C. Song, F. Luo.
    Journal: Computers, Materials & Continua
    Year: 2025

Prof Dr. Yunyoung Nam | Medical Image Analysis | Best Researcher Award

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Prof Dr. Yunyoung Nam | Medical Image Analysis | Best Researcher Award

Soonchunhyang University, South Korea

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A Novel Approach for High-Resolution Coastal Areas and Land Use Recognition from Remote Sensing Images based on Multimodal Network-Level Fusion of SRAN3 and Lightweight Four Encoders ViT

  • Authors: M.K. Bhatti, Muhammad Kashif; M.A. Khan, Muhammad Attique; S. Shaheen, Saima; S.A. Algamdi, Shabbab Ali; Y. Nam, Yunyoung
    Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
    Year: 2025

Analysis of Near-Fall Detection Method Utilizing Dynamic Motion Images and Transfer Learning

  • Authors: J. Kim, Jungyeon; N. Mat, Nab; C. Kim, Chomyong; S. Jeon, Seob; Y. Nam, Yunyoung
    Journal: IEEE Access
    Year: 2025

Cooperative PPG/ECG Wearable System for Atrial Fibrillation Diagnosis

  • Authors: Y. Lee, Yonbin; S. Lee, Soyoung; S. Kim, Sang-kyu; Y. Nam, Yunyoung; J. Lee, Jinseok
    Journal: IEEE Sensors Journal
    Year: 2025

Energy-Efficient Discrete Cosine Transform Architecture Using Reversible Logic for IoT-Enabled Consumer Electronics

  • Authors: M. Awais, Muhammad; W. Khan, Wilayat; T. Akram, Tallha; Y. Nam, Yunyoung
    Journal: IEEE Access
    Year: 2025

Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI

  • Authors: I. Jeon, Insoo; M. Kim, Minjoong; D. So, Dayeong; J. Kim, Joungmin; J. Moon, Jihoon
    Journal: Diagnostics
    Year: 2024

Dr. Sajid Ullah Khan | Medical Image Analysis | Best Researcher Award

Published on by Computer Vision Awards

Dr. Sajid Ullah Khan | Medical Image Analysis | Best Researcher Award

Doctorate at Prince Sattam Bin Abdulaziz University, Saudi Arabia

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Chat-GPT; validating Technology Acceptance Model (TAM) in education sector via ubiquitous learning mechanism

  • Authors: Naveed Saif, Sajid Ullah Khan, Imrab Shaheen, Faiz Abdullah ALotaibi, Mrim M Alnfiai, Mohammad Arif
  • Journal: Computers in Human Behavior
  • Year: 2024

Energy-efficient routing protocols for UWSNs: A comprehensive review of taxonomy, challenges, opportunities, future research directions, and machine learning perspectives

  • Authors: Sajid Ullah Khan, Zahid Ulalh Khan, Mohammed Alkhowaiter, Javed Khan, Shahid Ullah
  • Journal: Journal of King Saud University-Computer and Information Sciences
  • Year: 2024

Multimodal medical image fusion towards future research: A review

  • Authors: Sajid Ullah Khan, Mir Ahmad Khan, Muhammad Azhar, Faheem Khan, Youngmoon Lee, Muhammad Javed
  • Journal: Journal of King Saud University-Computer and Information Sciences
  • Year: 2023

Historical text image enhancement using image scaling and generative adversarial networks

  • Authors: Sajid Ullah Khan, Imdad Ullah, Faheem Khan, Youngmoon Lee, Shahid Ullah
  • Journal: Sensors
  • Year: 2023

A novel CT image de-noising and fusion based deep learning network to screen for disease (COVID-19)

  • Authors: Sajid Ullah Khan, Imdad Ullah, Najeeb Ullah, Sajid Shah, Mohammed El Affendi, Bumshik Lee
  • Journal: Scientific Reports
  • Year: 2023