Sangchun Choi | Artificial Intelligence | Best Researcher Award

Published on by Global Academic Awards

Best Researcher Award

Sangchun Choi
Soonchunhyang University
Sangchun Choi
Affiliation Soonchunhyang University
Country South Korea
Scopus ID 57213151463
Documents 35
Citations 464
h-index 11
Subject Area Artificial Intelligence
Event Global Academic Awards
ORCID Research Profile Available

Sangchun Choi of Soonchunhyang University, South Korea, whose research contributions in artificial intelligence have been reflected through peer-reviewed publications, scholarly citations, and recognized academic engagement.[1]

Abstract

Sangchun Choi has established a documented research presence within the field of artificial intelligence through scholarly publications, citation performance, and participation in internationally recognized research activities. Academic metrics indexed through Scopus indicate a consistent contribution to scientific literature, supporting recognition within the context of research excellence and academic achievement.[1]

Keywords

Artificial Intelligence, Machine Learning, Research Excellence, Scholarly Publications, Citation Impact, Academic Recognition, Best Researcher Award, Scientific Contribution.

Introduction

Research awards serve as mechanisms for acknowledging scholarly productivity, innovation, and influence across academic disciplines. Evaluation criteria commonly include publication quality, citation performance, research originality, and broader contributions to scientific advancement. Within this framework, Sangchun Choi’s documented record in artificial intelligence demonstrates characteristics frequently associated with research distinction and academic recognition.[1]

Research Profile

Sangchun Choi is affiliated with Soonchunhyang University in South Korea and maintains a research portfolio indexed in Scopus under Author ID 57213151463. The available bibliometric profile reports 35 indexed documents, 464 citations, and an h-index of 11, indicating measurable scholarly engagement and influence within the research community.[1]

  • Affiliation: Soonchunhyang University
  • Country: South Korea
  • Primary Subject Area: Artificial Intelligence
  • Indexed Documents: 35
  • Total Citations: 464
  • h-index: 11

Research Contributions

The research activities associated with Sangchun Choi contribute to ongoing developments in artificial intelligence and related computational methodologies. Published work in this area supports advancements in intelligent systems, data-driven decision-making, and emerging digital technologies. Such contributions enhance scholarly dialogue and provide foundations for future investigations.[2]

  • Development of artificial intelligence methodologies.
  • Contribution to peer-reviewed scientific literature.
  • Support for interdisciplinary computational research.
  • Participation in knowledge dissemination through scholarly publication.

Publications

The research record includes publications indexed within internationally recognized databases. Publication activity demonstrates engagement with contemporary scientific challenges and contributes to cumulative knowledge development within artificial intelligence and associated domains.[1]

  1. Peer-reviewed journal articles.
  2. Conference proceedings.
  3. Collaborative research publications.
  4. Works indexed through Scopus and related scholarly databases.

Representative scholarly outputs may include publications associated with digital intelligence, machine learning applications, and advanced computational frameworks. DOI-linked research dissemination supports transparency, discoverability, and long-term accessibility within the scientific record.[3]

Research Impact

Research impact can be evaluated through citation indicators, publication visibility, and influence on subsequent investigations. With 464 citations and an h-index of 11, Sangchun Choi’s scholarly record demonstrates measurable engagement from the academic community. Such indicators suggest that published research has contributed to ongoing scientific discussions and knowledge advancement.[1]

Award Suitability

Eligibility for the Best Researcher Award may be assessed through objective academic indicators including publication volume, citation performance, research quality, innovation, and disciplinary impact. The documented scholarly achievements of Sangchun Choi align with several commonly recognized evaluation criteria utilized by academic award committees. Bibliometric performance, research continuity, and subject-area relevance collectively support consideration for research excellence recognition.[1]

Conclusion

Sangchun Choi’s academic profile reflects sustained engagement in artificial intelligence research through peer-reviewed publications, scholarly citations, and measurable research impact. The combination of documented productivity, citation performance, and contribution to scientific advancement provides a scholarly basis for recognition within the framework of the Best Researcher Award presented by the Global Academic Awards program.[1]

References

  1. Scopus author details: Sangchun Choi, Author ID 57213151463. Scopus.https://www.scopus.com/authid/detail.uri?authorId=57213151463
  2. Artificial Intelligence-Derived Electrocardiogram Analysis for Identification of Carbon Monoxide-Induced Cardiomyopathy: A Retrospective Studyhttps://www.mdpi.com/1648-9144/62/6/1081
  3. Role of Aspartate in Immune Response and Mortality in a Polymicrobial Sepsis Model: Insights from Metabolomics and Transcriptomicshttps://www.mdpi.com/2073-4409/15/6/513

Mehdi Moayed Mohseni | Machine Learning | Best Researcher Award

Published on by Global Academic Awards

Assist. Prof. Dr. Mehdi Moayed Mohseni | Machine Learning | Best Researcher Award

Islamic Azad University Science and Research Branch | Iran

Assist. Prof. Dr. Mehdi Moayed Mohseni is a distinguished chemical engineer at Islamic Azad University, Tehran, Iran, with expertise in non-Newtonian fluid mechanics, convective heat transfer, viscoelastic fluids, rheology, and exergy analysis. He earned his Ph.D. in Chemical Engineering from Amirkabir University of Technology, Iran, focusing on hydrodynamic and heat transfer modeling and entropy analysis of viscoelastic fluids in centric and eccentric annuli, followed by an M.Sc. on heat transfer of Giesekus viscoelastic fluids and a B.Sc. on biological natural gas sweetening processes. His research integrates analytical and semi-analytical methods (HPM, perturbation, homotopy) with computational fluid dynamics (CFD) and mass/heat transfer studies. Assist. Prof. Dr. Mehdi Moayed Mohseni has authored 17 publications, including studies on thermal and rheological performance of nanofluids, contributing to 229 citations and an h-index of 8. He actively participates in conferences, such as the National Iranian Chemical Engineering Congress, and his work demonstrates a strong commitment to advancing understanding of complex fluid behavior and transport phenomena.

Profile: Scopus | Google Scholar

Featured Publications

Mohseni, M. M., Jouyandeh, M., Sajadi, S. M., Hejna, A., Habibzadeh, S., … (2022). Metal-organic frameworks (MOF) based heat transfer: A comprehensive review. Chemical Engineering Journal, 449, 137700.

Montazeri, N., Salahshoori, I., Feyzishendi, P., Miri, F. S., Mohseni, M. M., … (2023). pH-sensitive adsorption of gastrointestinal drugs (famotidine and pantoprazole) as pharmaceutical pollutants by using the Au-doped@ ZIF-90-glycerol adsorbent: Insights from … Journal of Materials Chemistry A, 11(47), 26127–26151.

Salahshoori, I., Vaziri, A., Jahanmardi, R., Mohseni, M. M., Khonakdar, H. A. (2024). Molecular simulation studies of pharmaceutical pollutant removal (rosuvastatin and simvastatin) using novel modified-MOF nanostructures (UIO-66, UIO-66/chitosan, and UIO-66 …). ACS Applied Materials & Interfaces, 16(20), 26685–26712.

Mohseni, M. M., & Rashidi, F. (2010). Viscoelastic fluid behavior in annulus using Giesekus model. Journal of Non-Newtonian Fluid Mechanics, 165(21-22), 1550–1553.

Bateni, A., Salahshoori, I., Jorabchi, M. N., Mohseni, M. M., Asadabadi, M. R., … (2025). Molecular simulation-based assessing of a novel metal-organic framework modified with alginate and chitosan biopolymers for anionic reactive black 5 and cationic crystal violet … Separation and Purification Technology, 354, 128986.

Kachi Anvesh | Machine Learning | Best Researcher Award

Published on by Global Academic Awards

Mr. Kachi Anvesh | Machine Learning | Best Researcher Award

Vardhaman College of Engineering | India

Mr. Kachi Anvesh is an Assistant Professor in the Department of Information Technology at Vardhaman College of Engineering, Hyderabad, with over 12 years of teaching and research experience. He is currently pursuing a Ph.D. in Computer Science at Visvesvaraya Technological University, Belagavi, and holds an M.Tech in Software Engineering with distinction and a B.Tech in Information Technology. His research focuses on medical image processing, deep learning, machine learning, and intelligent systems, with notable contributions including the detection of tessellated retinal disease, hypertensive retinopathy, glaucoma, cataract, and wheat head detection using advanced AI models. He has published in reputed journals and conferences such as JIKM, TSP-CMES, and Journal of Autonomous Intelligence, accumulating 13 citations and an h-index of 2. Mr. Anvesh has led innovative projects including bone age detection from X-ray images, facial expression recognition, emotion detection, foreign object debris detection, and predictive analytics systems, and holds certifications in AI and deep learning from IIT Ropar and other platforms, reflecting his strong contribution to engineering and AI research.

Profile: Scopus | Orcid | Google Scholar

Featured Publications

Anvesh, K., Prasad, S., Laxman, V. V. S. R., & Narayana, B. S. (2019). Automatic student analysis and placement prediction using advanced machine learning algorithms. International Journal of Innovative Technology and Exploring Engineering, 8, 9.

Suma, K., Sunitha, G., Karnati, R., Aruna, E. R., Anvesh, K., Kale, N., & Kishore, P. K. (2024). CETR: CenterNet-Vision transformer model for wheat head detection. Journal of Autonomous Intelligence, 7(3), 6.

Venkatesh, M., Dhanalakshmi, C., Adapa, A., Manzoor, M., & Anvesh, K. (2023). Criminal face detection system.

Anvesh, K., Srilatha, M., Raghunadha Reddy, T., Gopi Chand, M., & Jyothi, G. D. (2018). Improving student academic performance using an attribute selection algorithm. Proceedings of the First International Conference on Artificial Intelligence and Cognitive…, 3.

Rajendar, B., Bhavana, K., Divya, C., Swarna, M., & Anvesh, K. (2017). Evaluation of cardiac tonic activity of methanolic leaf extract of Moringa oleifera. International Journal of Pharma Sciences and Research, 8(6), 152–156.

Alper Mitincik | Artificial Intelligence | Best Researcher Award

Published on by Global Academic Awards

Mr. Alper Mitincik | Artificial Intelligence | Best Researcher Award

Galatasaray University | Turkey

Mr. Alper Mitincik is an accomplished software engineer and researcher with extensive expertise in Java, Python, SQL, and scalable data-driven applications. He has led significant projects, including a national cloud storage system and one of the largest Turkish-language crawling-based search engines, demonstrating exceptional skills in search engine architecture, Elasticsearch optimization, ranking algorithms, and large-scale data pipelines. Alper has published research on information retrieval and deep learning, notably “Text-Based Image Retrieval System Using Semantic Visual Content for Re-Ranking” in Engineering Applications of Artificial Intelligence (2025), and his M.Sc. thesis focused on semantic search frameworks. Currently pursuing a Ph.D. in Computer Engineering, his research emphasizes advanced recommendation systems, transformers, and graph attention networks. With experience mentoring engineers, implementing best practices, and designing robust software architectures, Alper combines industrial impact with academic innovation. Recognized with awards such as Turkcell’s CXO Award and holding certifications in machine learning,

Profile: Google Scholar

Featured Publications

Parlak, İ. B., & Mıtıncık, A. (2022). Designing an information framework for semantic search. Avrupa Bilim ve Teknoloji Dergisi, 682–689.

Topcu, B., Mıtıncık, A., Erdem, M. G., & Yanikoglu, B. (2025). Text-based image retrieval system using semantic visual content for re-ranking. Engineering Applications of Artificial Intelligence, 160, 111770.

Mohammed Almulla | Artificial Intelligence | Best Researcher Award

Published on by Global Academic Awards

Prof. Mohammed Almulla | Artificial Intelligence | Best Researcher Award

Prof. Mohammed Almulla, Kuwait University, Kuwait

Prof. Mohammed Ali Almulla, a distinguished Kuwaiti computer scientist, serves as a Professor at Kuwait University. With a Ph.D. in Computer Science from McGill University, he has contributed extensively to academia, research, and administrative leadership. His expertise spans artificial intelligence, automated theorem proving, and IT consultancy. Prof. Almulla has held prominent roles, including Chairman of the Computer Science Department and Acting Vice President for Academic Support Services. Beyond academia, he has influenced national IT policies as an advisor. A dedicated educator and researcher, he actively supports academic development and technological innovation.

Publication Profile

Scopus

Google Scholar

🎓 Education

Prof. Mohammed Almulla earned his B.Sc., M.Sc., and Ph.D. in Computer Science from McGill University, Canada. His Ph.D. thesis, “Analysis of the Use of Semantic Trees in Automated Theorem Proving,” reflects his deep interest in artificial intelligence. His rigorous academic training equipped him with comprehensive expertise in programming, networking, and advanced computer science concepts. With a solid foundation in both theoretical and applied research, Prof. Almulla has contributed to academic growth and scientific discovery. His multilingual proficiency in Arabic and English further enhances his research collaborations and educational impact.

💼 Experience

Prof. Mohammed Almulla has an illustrious career in academia and administration. Since 1995, he has progressed from Assistant Professor to Professor at Kuwait University. He served as Chairman of the Computer Science Department, securing ABET accreditation. His leadership extended to acting roles as Vice President for Academic Support Services and Planning. Prof. Almulla also contributed as an IT Consultant for Kuwait’s Council of Ministers and led the AI Policy Implementation Committee. With decades of service in education, administration, and national IT development, his expertise remains highly influential in Kuwait’s technological landscape.

🏆 Awards and Honors

Prof. Mohammed Almulla has received numerous accolades for his academic and administrative contributions. Notably, he served as a member and coordinator of the Evaluation Committee for the H.H. Sheik Salem Al-Ali AlSabah Award for Informatics, earning recognition for his dedication to technological advancements. As a valued IT consultant and university leader, his work has significantly shaped Kuwait’s digital landscape. His participation in major university and national projects has further solidified his reputation as a pioneer in computer science and informatics.

🔎 Research Focus

Prof. Mohammed Almulla’s research interests include artificial intelligence, automated theorem proving, and decision support systems. His work explores the applications of semantic trees in AI-driven problem-solving. With a passion for advancing intelligent systems, he investigates areas like AI policy implementation and large-scale data analysis. His contributions as a reviewer for over 30 prestigious journals emphasize his influence in the field. Additionally, Prof. Almulla is committed to mentoring students and advancing AI technologies to address real-world challenges.

 

Publication Top Notes

  • 📝 The Effectiveness of the Project-Based Learning (PBL) Approach as a Way to Engage Students in Learning – 947 citations (2020)

  • 🌿 Integrated Social Cognitive Theory with Learning Input Factors: The Effects of Problem-Solving Skills and Critical Thinking Skills on Learning Performance Sustainability – 104 citations (2023)

  • 🎓 Constructivism Learning Theory: A Paradigm for Students’ Critical Thinking, Creativity, and Problem Solving to Affect Academic Performance in Higher Education – 94 citations (2023)

  • 📖 Investigating Teachers’ Perceptions of Their Own Practices to Improve Students’ Critical Thinking in Secondary Schools in Saudi Arabia – 56 citations (2018)

  • 🧠 Using Conceptual Mapping for Learning to Affect Students’ Motivation and Academic Achievement – 47 citations (2021)

  • 🏫 An Investigation of Teachers’ Perceptions of the Effects of Class Size on Teaching – 46 citations (2015)

  • 📘 The Efficacy of Employing Problem-Based Learning (PBL) Approach as a Method of Facilitating Students’ Achievement – 44 citations (2019)

  • 💻 Technology Acceptance Model (TAM) and E-Learning System Use for Education Sustainability – 38 citations (2021)

  • 🤖 Investigating Influencing Factors of Learning Satisfaction in AI ChatGPT for Research: University Students Perspective – 24 citations (2024)

  • 🧑‍🏫 Using Digital Technologies for Testing Online Teaching Skills and Competencies During the COVID-19 Pandemic – 24 citations (2022)

  • 🧑‍🤝‍🧑 An Investigation of Cooperative Learning in a Saudi High School: A Case Study on Teachers’ and Students’ Perceptions and Classroom Practices – 24 citations (2017)

  • 🏗 Investigating Important Elements That Affect Students’ Readiness for and Practical Use of Teaching Methods in Higher Education – 15 citations (2022)

  • 📊 Developing a Validated Instrument to Measure Students’ Active Learning and Actual Use of Information and Communication Technologies for Learning in Saudi Arabia’s Higher Education – 8 citations (2022)

  • 🏅 An Investigation of Saudi Teachers’ Perceptions Towards Training in Cooperative Learning – 8 citations (2016)

  • 🌐 The Changing Educational Landscape for Sustainable Online Experiences: Implications of ChatGPT in Arab Students’ Learning Experience – 5 citations (2024)

  • 📲 Investigating Students’ Intention to Use M-Learning: The Mediating Role of Mobile Usefulness and Intention to Use – 5 citations (2024)

  • 🖥 Using Digital Technologies for Testing Online Teaching Skills and Competencies During the COVID-19 Pandemic – 4 citations (2022)

  • 👫 Students’ Perceptions of the Academic and Social Benefits of Working with Cooperative Learning – 3 citations (2016)

 

 

Zuheng Ming | Artificial intelligence | Best Researcher Award

Published on by Global Academic Awards

Dr. Zuheng Ming | Artificial intelligence | Best Researcher Award

Associate professor at Sorbonne Paris North University, France

🧑‍🏫 Dr. Zuheng Ming is an Assistant Professor at L2TI, Sorbonne Paris North University, France. He earned his PhD in 2013 from Grenoble Alpes University 🇫🇷, specializing in speech parameter mapping. His expertise spans multimodal learning, computer vision, and deep learning 🤖. Dr. Ming has 30+ publications 📝 in top-tier journals (JCR Q1/Q2) and conferences (ICIP, ICPR, ICDAR). He has supervised doctoral and master’s theses and collaborated internationally with CVC, RIKEN AIP, and Oulu University 🌍. He has led funded research projects on face anti-spoofing and document analysis 📄. Additionally, he serves as a guest editor and reviewer for prestigious journals. ✨

Publication Profile

Google Scholar

🏅 Professional Experience

Dr. Zuheng Ming is an accomplished researcher and educator in computer vision and deep learning 🤖. Since September 2022, he has been serving as an Assistant Professor at L2TI, Sorbonne Paris North University, France 🇫🇷. Prior to this, he was a Lecture-Researcher at L3i, La Rochelle University (2021-2022) 📚. From 2016 to 2021, he worked as a Postdoctoral Fellow and Assistant Lecturer at L3i, La Rochelle University. Earlier, from 2014 to 2015, he pursued a postdoctoral fellowship at Bordeaux University 🏛️, contributing significantly to cutting-edge research in multimodal learning and artificial intelligence. ✨

🎓 Educational Background

Dr. Zuheng Ming holds a PhD in Computer Science from Grenoble Alpes University, France (2013) 🇫🇷, where he specialized in spectral parameters mapping for cued speech using multi-linear and GMM approaches 🔬. He earned his Master’s degree in Pattern Recognition and Artificial Intelligence from Beijing Institute of Technology (2008) 🎭🤖. His academic journey began with a Bachelor’s degree in Electronic and Automatic Systems Engineering from Hunan University, China (2003) ⚡. His strong educational foundation has driven his research contributions in computer vision, deep learning, and multimodal learning 📚✨.

🔬 Research Activities

Dr. Zuheng Ming has been actively involved in research supervision, mentoring 1 PhD thesis, 2 Master’s theses, and 6 internships 🎓📖. He has established six international collaborations with prestigious institutions, including CVC (Spain) 🇪🇸, RIKEN AIP (Japan) 🇯🇵, Oulu University (Finland) 🇫🇮, Northwestern Polytechnical University (China) 🇨🇳, and Xidian University (China) 🇨🇳. His global academic engagement also includes an academic visit to Kyoto University, Japan, in 2015 🌍🏫. Through his extensive research network, Dr. Ming continues to make significant contributions to computer vision, deep learning, and multimodal learning 📊🤖.

🎓 Teaching Experience

Dr. Zuheng Ming has extensive teaching experience in cutting-edge technologies related to artificial intelligence and computer vision 🧠📸. He has taught courses on Deep Learning, Advanced Image Processing, and Intelligent Systems in Computer Vision 🤖🖼️, equipping students with the latest advancements in AI. Additionally, he has imparted knowledge in Database Management and Object-Oriented Programming 💾💻, fostering strong software development skills. His expertise in both theoretical foundations and practical applications makes him a valuable mentor in the field of AI and computer vision, guiding students toward innovative research and industry-ready solutions 🚀📚.

🔍 Research Focus

Dr. Zuheng Ming’s research primarily focuses on computer vision, deep learning, and document security 🧠📸🔏. His contributions span facial recognition, anti-spoofing techniques, and face liveness detection 🤖😃, enhancing biometric security. He has also worked extensively on document image classification and authentication 📄🔍, improving identity verification systems. His expertise in multi-modal learning, pattern recognition, and deep feature fusion enables advancements in AI-driven document forensics and secure authentication 🚀🔐. Collaborating internationally, he applies machine learning and self-attention networks to solve real-world challenges in face recognition, fraud detection, and intelligent systems 🌍🔬.

Publication Top Notes

📸 A survey on anti-spoofing methods for facial recognition with RGB cameras of generic consumer devices – Z Ming, M Visani, MM Luqman, JC Burie | Journal of Imaging | 88 citations | 2020

📄 Visual and textual deep feature fusion for document image classification – S Bakkali, Z Ming, M Coustaty, M Rusiñol | IEEE/CVF Conference on Computer Vision | 63 citations | 2020

🔍 Simple triplet loss based on intra/inter-class metric learning for face verification – Z Ming, J Chazalon, MM Luqman, M Visani, JC Burie | IEEE/CVF International Conference on Computer Vision | 57 citations | 2017

😊 Facial action units intensity estimation by fusion of features with multi-kernel SVM – Z Ming, A Bugeau, JL Rouas, T Shochi | IEEE International Conference on Automatic Face and Gesture Recognition | 54 citations | 2015

🆔 MIDV-2020: A comprehensive benchmark dataset for identity document analysis – BK Bulatovich, EE Vladimirovna, TD Vyacheslavovich, SN Sergeevna, … | Computer Optics | 51 citations | 2022

🙂 Dynamic Multi-Task Learning for Face Recognition with Facial Expression – Z Ming, J Xia, MM Luqman, JC Burie, K Zhao | IEEE/CVF International Conference on Computer Vision Workshop | 40 citations | 2019

📜 VLCDoC: Vision-language contrastive pre-training model for cross-modal document classification – S Bakkali, Z Ming, M Coustaty, M Rusiñol, OR Terrades | Pattern Recognition | 33 citations | 2023

🔐 FaceLiveNet: End-to-end networks combining face verification with interactive facial expression-based liveness detection – Z Ming, J Chazalon, MM Luqman, M Visani, JC Burie | International Conference on Pattern Recognition | 30 citations | 2018

📑 Cross-modal deep networks for document image classification – S Bakkali, Z Ming, M Coustaty, M Rusiñol | IEEE International Conference on Image Processing | 23 citations | 2020

📃 Document liveness challenge dataset (DLC-2021) – DV Polevoy, IV Sigareva, DM Ershova, VV Arlazarov, DP Nikolaev, Z Ming, … | Journal of Imaging | 21 citations | 2022

📹 ViTransPAD: Video Transformer using convolution and self-attention for Face Presentation Attack Detection – Z Ming, Z Yu, M Al-Ghadi, M Visani, M Muzzamil Luqman, JC Burie | IEEE International Conference on Image Processing | 21 citations | 2022

🌲 Multiple sources data fusion via deep forest – J Xia, Z Ming, A Iwasaki | IGARSS IEEE International Geoscience and Remote Sensing Symposium | 15 citations | 2018

🆔 Face detection in camera captured images of identity documents under challenging conditions – S Bakkali, MM Luqman, Z Ming, JC Burie | International Conference on Document Analysis and Recognition Workshops | 11 citations | 2019

📑 EAML: Ensemble self-attention-based mutual learning network for document image classification – S Bakkali, Z Ming, M Coustaty, M Rusiñol | International Journal on Document Analysis and Recognition | 10 citations | 2021

🧠 Synthetic evidential study as augmented collective thought process – Preliminary report – T Nishida, M Abe, T Ookaki, D Lala, S Thovuttikul, H Song, Y Mohammad, … | ACIIDS Asian Conference | 10 citations | 2015

🆔 Identity documents authentication based on forgery detection of guilloche pattern – M Al-Ghadi, Z Ming, P Gomez-Krämer, JC Burie | arXiv preprint | 8 citations | 2022

 

Nafis Uddin Khan | Artificial Intelligence | Best Researcher Award

Published on by Global Academic Awards

Dr Nafis Uddin Khan | Artificial Intelligence | Best Researcher Award 

Dr Nafis Uddin Khan, SR University Warangal India, India

Dr. Nafis Uddin Khan is a distinguished academic and researcher at SR University in Warangal, India. His expertise spans a variety of fields, contributing significantly to both the academic community and industry advancements. Dr. Khan’s work is characterized by a strong focus on innovative solutions and sustainable practices, reflecting his commitment to addressing contemporary challenges through research and education. At SR University, he plays a pivotal role in mentoring students and leading research initiatives that aim to drive technological progress and societal impact.

Profile

Orcid

Education

       Bachelor of Engineering (B.E.) in Electronics and Telecommunication Engineering from Amravati University  Maharashtra, in 2003.

       Master of Technology (M.Tech.) in Software Systems from S.A.T.I. Vidisha under Rajiv Gandhi Technological University, Bhopal, in 2008.

        Doctor of Philosophy (Ph.D.) in Signal and Image Processing from the Atal Bihari Vajpayee – Indian Institute of Information Technology & Management, Gwalior

Professional experience

  1. Workshop Coordinator: Coordinated a two-day workshop titled “Synthesis of Wisdom: Crafting AI Tutor Assistants, Navigating Future-Ready Digital Libraries and Elevating Pedagogy in the Age of Skill Enhancement and AI Mastery” on February 02–03, 2024, at the School of CS & AI, SR University, Warangal, India.
  2. Faculty Development Program Coordinator: Coordinated “Utkarsh – Take Flight,” a two-day Faculty Development Program on Leadership and Excellence in Quality Education organized by Jaypee University of Information Technology, Solan (H.P.), on December 22–23, 2022.
  3. Chief Coordinator: Served as Chief Coordinator in a student outreach activity organized by the Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Solan (H.P.), on December 20, 2022.
  4. Invited Session Chair: Served as an Invited Session Chair in the Congress on Intelligent Systems (CIS 2020), World Conference in virtual format, on September 05–06, 2020.
  5. Organizing Committee Member and Reviewer: Participated as an Organizing Committee Member and Reviewer in the Congress on Intelligent Systems (CIS 2020), World Conference in virtual format, on September 05–06, 2020.
  6. Convener: Organized a one-week online short-term course on “Recent Advances in Computational Intelligence for Signal Processing” (RACISP – 2020) at Jaypee University of Information Technology, Solan (H.P.), from August 10–15, 2020.
  7. Coordinator: Coordinated a five-day short-term course on “Recent Advances in Signal and Image Processing” (RASIP – 2019) at Jaypee University of Information Technology, Solan (H.P.), from June 24–28, 2019.
  8. Organizing Committee Member: Served in the organizing committee for the 5th IEEE International Conference on “Signal Processing, Computing and Control” (ICSPC 2019) organized by the Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Solan (H.P.), from October 10–12, 2019.
  9. Invited Session Chair: Chaired an invited session in the 2019 IEEE International Conference on “Image Information Processing” (ICIIP 2019) organized by the Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan (H.P.), from November 15–17, 2019.
  10. Organizing Committee Member: Participated as an organizing committee member in the 4th IEEE International Conference on “Signal Processing, Computing and Control” (ICSPC 2017) at Jaypee University of Information Technology, Solan (H.P.), from September 21–23, 2017.
  11. Invited Session Chair: Served as an invited session chair at the 7th IEEE International Conference on “Computational Intelligence and Communication Networks” (CICN 2015) at Gyan Ganga Institute of Technology and Science, Jabalpur (M.P.), on December 12, 2015.
  12. National Advisory Committee Member: Served on the National Advisory Committee for the National Conference on Contemporary Computing organized by the Department of Computer Science and Information Technology, Chameli Devi Group of Institutions, Indore (M.P.), from October 21–22, 2016.

Research Focus

      Fuzzy Logic and Optimization: Utilizing fuzzy logic for applications in signal and image processing, including the development of fuzzy-based diffusion coefficient functions for selective noise smoothing.

      Medical Image Processing: Enhancing medical imaging techniques, such as de-speckling in ultrasound and X-ray images, and improving image de-noising using soft optimization techniques.

      Pattern Analysis in Machine Intelligence: Investigating pattern analysis and its applications within machine intelligence to improve the accuracy and efficiency of image processing algorithms.

Awards and Honors