Mohammed Almulla | Artificial Intelligence | Best Researcher Award

Posted on by ScienceFather

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

Posted on by ScienceFather

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

 

Mohit Kataria | Machine Learning | Best Researcher Award

Posted on by ScienceFather

Mr. Mohit Kataria | Machine Learning | Best Researcher Award

Professor at IIT-Delhi

📌  Mohit Kataria is a 4th-year Ph.D. scholar at the School of Artificial Intelligence, IIT Delhi, India, specializing in Graph Machine Learning. His research focuses on scalability of graph algorithms, including graph coarsening, structure learning, federated learning, and large-scale applications. He has published in top venues like NeurIPS, MICAAI, and CBME. Mohit holds a Master’s in Computer Applications (80.1%) and has expertise in Python, PyTorch, TensorFlow, CUDA, and C/C++. His skill set spans deep learning (GNNs, CNNs, RNNs), machine learning (SVM, XGBoost), and mathematical optimization.

Publication Profile

Google Scholar

Academic Background 🎓🔬

📌 Mohit Kataria is a Ph.D. scholar in Graph Machine Learning at the MISN Lab, IIT Delhi, maintaining an 8.0 CGPA since August 2021. He holds a Master’s in Computer Applications (80.1%) from May 2020. His technical expertise spans Python, PyTorch, TensorFlow, CUDA, MPI, C/C++, Java, MySQL, and Erlang. 🖥️ He specializes in Machine Learning (SVM, Random Forest, XGBoost, Decision Trees) and Deep Learning (ANNs, GNNs, CNNs, RNNs, LSTM, VAE, GANs). 📊 His strong foundation in Linear Algebra, Probability, and Optimization fuels his research in scalable graph algorithms and AI applications. 🚀

💼 Professional Experience of Mohit Kataria

📌 Mohit Kataria has been actively involved in AI/ML training at IIT Delhi (2021-Present), where he has helped train 260+ industry experts in a six-month AI/ML program, covering fundamentals to advanced ML models. 🎓 He also conducted 5-day ML training programs for CAG and CRIS, Government of India. As a WebMaster (2022-Present), he manages the Yardi-ScAI and MISN group websites. 🌐 Previously, as a Member of Technical Staff at Octro.Inc (2020-2021), he led a team of four and contributed to the backend architecture of multiplayer games like Poker3D and Soccer Battles. 🎮🚀

🔬 Research Focus of Mohit Kataria

📌 Mohit Kataria specializes in Graph Machine Learning, focusing on graph coarsening, structure learning, and scalable AI applications. His work enhances GNN performance on heterophilic datasets 🧠, improves large-scale single-cell data analysis 🧬, and optimizes histopathological image processing 🔍. His research, published in NeurIPS, MICAAI, and CBME, develops efficient graph-based frameworks for biomedical and computational applications. 🏥 His expertise spans AI-driven healthcare, graph-based AI models, and machine learning scalability, making significant contributions to bioinformatics, medical imaging, and large-scale data processing. 🚀

Publication Top Notes 

 

 

 

Md Erfan | Machine Learning | Best Researcher Award

Posted on by ScienceFather

Mr. Md Erfan | Machine Learning | Best Researcher Award

Mr. Md Erfan, University of Barishal, Bangladesh

Assistant Professor, Department of Computer Science and Engineering, University of Barishal, Bangladesh. His research focuses on flaky test detection, compilation error resolution, and AI applications in automation, decision-making, and problem-solving. He holds an MSSE and BSSE from the University of Dhaka. Erfan has published in Elsevier, Springer, and IEEE, exploring NLP, machine learning, and software engineering. He serves as Project Coordinator for Bangladesh’s EDGE Project and has mentored in NASA Space Apps Challenge. An athlete, he won medals in national athletic competitions. 

Publication Profile

Google Scholar

Education 🎓📚

Md Erfan holds a Master of Science in Software Engineering (MSSE) 🖥️ from the Institute of Information Technology, University of Dhaka (2016), with an impressive CGPA of 3.81/4.0 (WES Equivalent: 3.97/4.00). His thesis, supervised by Dr. Md Shariful Islam, focused on an Efficient Runtime Code Offloading Mechanism for Mobile Cloud Computing ☁️💻. He also earned a Bachelor of Science in Software Engineering (BSSE) 🏆 from the same institute in 2014, achieving a CGPA of 3.80/4.0 (WES Equivalent: 3.88/4.00). His undergraduate thesis, guided by Dr. Kazi Muhaimin-us-Sakib, explored approximating social ties based on call logs 📞📊.

Research Experience 🔬📊

In Summer 2024, Md Erfan worked as a Research Student in the UIUC+/ASSIP Summer Research Program 🎓. Collaborating with Dr. Wing Lam (George Mason University) 🏛️ and Dr. August Shi (University of Texas at Austin) 🤖, he focused on automating the end-to-end reproduction of flaky test methods 🛠️. His work involved leveraging issue data, compiling code, running tests, analyzing results, and logging dependencies. Additionally, he created Dockerized environments 🐳 to ensure reproducibility, enhancing software testing efficiency and reliability. His contributions aimed at improving software quality assurance and automation in test debugging 🔍✅.

Professional Experience 💼📚

Md Erfan is an Assistant Professor (2020–Present) at the Department of Computer Science and Engineering, University of Barishal 🏛️, where he teaches Software Engineering, Software Quality Assurance, Data Structures, Algorithms, and Mathematical Analysis 📖💻. Since January 2024, he has also served as a Project Coordinator for the EDGE Project 🌐, managing a 5 crore BDT ($384,615 USD) fund 💰 to enhance digital governance and the economy in Bangladesh. Previously, he worked as a Lecturer (2016–2020) 🎓, a Trainer (2015–2016) 🖥️, and a Software Engineer Intern (2014) 🔍, focusing on testing tools and Microsoft SharePoint development.

Awards and Achievements 🏆🎖️

Md Erfan has been a Regional Mentor (2021–2023) 🌍🚀 for the NASA Space Apps Challenge, guiding innovative projects. He received the Pre-graduation Merit Award (2015) 🎓 from the University of Dhaka for outstanding academic performance. Beyond academics, he has excelled in athletics, securing 3rd place 🥉 in the 5000m and 10000m races 🏃‍♂️ at the Bangladesh Inter-University Athletic Competition (2015) and 2nd place 🥈 in multiple track events (2014–2015). Since 2016, he has been the Coach and Manager ⚽🏅 of the University of Barishal Football and Athletics teams, fostering sports excellence.

 

Research Interests 🔍💻

Md Erfan’s research primarily focuses on Software Engineering, specializing in flaky test detection and mitigation as well as compilation error resolution to enhance software reliability and development efficiency. Additionally, he explores the applications of Artificial Intelligence (AI), leveraging Machine Learning (ML) 🤖, Natural Language Processing (NLP) 🗣️, and Computer Vision 👀 to tackle real-world challenges. His work aims to improve automation, decision-making, and problem-solving across various domains, ensuring smarter and more efficient technological advancements. Through his research, Erfan contributes to optimizing software development and AI-driven innovations for practical applications. 🚀

Research Focus Areas 🧑‍💻📡

Md Erfan’s research spans multiple domains in Software Engineering and Artificial Intelligence. His work focuses on Mobile Cloud Computing ☁️📱, including task allocation and code offloading for performance optimization. He explores Machine Learning 🤖 applications, such as flaky test detection, compilation error resolution, and autism spectrum disorder detection 🧠. His contributions in Natural Language Processing (NLP) 🗣️ involve cyberbullying classification and user similarity computation. Additionally, he applies Computer Vision 👁️ techniques for mosquito species identification and assistive robotics. His interdisciplinary approach integrates automation, decision-making, and problem-solving in real-world applications.

Publication Top Notes

  • Mobility aware task allocation for mobile cloud computing
    Cited by: 8
    Year: 2016 📱☁️
  • Task allocation for mobile cloud computing: State-of-the-art and open challenges
    Cited by: 4
    Year: 2016 📊
  • Identification of Vector and Non-vector Mosquito Species Using Deep Convolutional Neural Networks with Ensemble Model
    Cited by: 2
    Year: 2022 🦟🤖
  • Recurrent neural network based multiclass cyber bullying classification
    Cited by: 1
    Year: 2024 💻🗣️
  • User Similarity Computation Strategy for Collaborative Filtering Using Word Sense Disambiguation Technique
    Cited by: 1
    Year: 2023 🔍📚
  • Approximating Social Ties Based on Call Logs: Whom Should We Prioritize?
    Cited by: 1
    Year: 2015 📱📞
  • An exploration of machine learning approaches for early Autism Spectrum Disorder detection
    Year: 2025 🧠🤖
  • Experimental Study of Four Selective Code Smells Declining in Real Life Projects
    Year: 2024 🧑‍💻🔧
  • Autism Spectrum Disorder Detecting Mechanism on Social Communication Skills Using Machine Learning Approaches
    Year: 2023 🧠💡
  • Dynamic Method Level Code Offloading for Performance Improvement and Energy Saving
    Year: 2017 ⚡💻
  • A comparative study of early autism spectrum disorder detection using deep learning based models
    Year: 2017 🧠🔍
  • An Optimal Task Scheduling Mechanism for Mobile Cloud Computing
    Year: 2016 ☁️📊
  • WVGM: Water View Google Map, Introducing Water Paths on Rivers to Reach One’s Destination using Various Types of Vehicles
    Year: 2016 🌍🚗
  • A comprehensive survey of code offloading mechanisms for mobile cloud computing
    Year: 2016 ☁️🔄
  • MICROCONTROLLER BASED ROBOTICS SUPPORT FOR BLIND PEOPLE
    Year: 2016 🤖👨‍🦯

Conclusion 🌟

Mr. Md Erfan is a highly suitable candidate for the Research for Best Researcher Award due to his strong academic background, impactful research in software engineering and AI, extensive publications, leadership in digital governance projects, and active contributions to global research collaborations. His work demonstrates innovation, technical expertise, and a commitment to advancing knowledge in his field.

 

 

Nunzio Alberto Borghese | Cognitive science | Best Researcher Award

Posted on by ScienceFather

Prof. Nunzio Alberto Borghese | Cognitive science | Best Researcher Award

Prof. Nunzio Alberto Borghese, Università degli Studi di MIlano, Italy

Prof. N. Alberto Borghese, a magna cum laude graduate in Electrical Engineering from Politecnico di Milan (1986), is a Full Professor at the Department of Computer Science, UNIMI, and Director of the Laboratory of Applied Intelligent Systems. With expertise in computational intelligence, he has pioneered predictive methods like multi-scale hierarchical neural networks and adaptive clustering. His innovations extend to e-Health platforms integrating AI 🤖, service robots, and smart objects. Prof. Borghese has 90+ journal papers (h-index: 42), 140+ conference papers, and 16 patents. He has led notable EC-funded projects, including REWIRE and MOVECARE, showcasing global research impact. 🌍📚

 

Publication Profile

Orcid

Academic Background 🎓

Prof. N. Alberto Borghese graduated magna cum laude in Electrical Engineering from Politecnico of Milan in 1986. His exceptional academic foundation enabled him to embark on a distinguished research and academic career. From 1987 to 2000, he was a tenured researcher at CNR, after which he became an Associate and then Full Professor at the Department of Computer Science, UNIMI. Currently, he directs the Laboratory of Applied Intelligent Systems, focusing on innovative solutions in computational intelligence. His career reflects a strong commitment to excellence and groundbreaking research. 🌟

Research Expertise 🔬

Prof. Borghese specializes in developing and applying computational intelligence methods to real-world problems. His work includes predictive techniques like multi-scale hierarchical neural networks, adaptive clustering, and statistical data processing. He emphasizes creating solutions with limited processing time to enhance practical usability. Recently, he has integrated Artificial Intelligence, smart objects, and robotics to innovate platforms for e-Health and e-Welfare. His work bridges cutting-edge technology and societal needs, demonstrating versatility and impact in the research community. 🤖💡

Research Focus

Prof. N. Alberto Borghese focuses on applied computational intelligence and innovative solutions for e-Health, rehabilitation, and gaming technologies. His research explores the intersection of artificial intelligence (AI), serious games, robotics, and virtual reality (VR) for improving physical and cognitive health. Key contributions include developing smart systems for rehabilitation, virtual communities for eldercare, and exergames to enhance recovery in stroke and arthritis patients. His work also involves assessing stress and arousal in VR games and advancing educational tools like handwriting apps. Prof. Borghese’s impactful research integrates technology with healthcare for community well-being. 🌟🕹️💻

 

Publication Top Notes 📚

  • Exploring AR Experience with Thermojelly: a Competitive AR Board-game with Tangible Interfaces (2024) 🕹️📱
  • Tracing Stress and Arousal in Virtual Reality Games Using Players’ Motor and Vocal Behaviour (2023) 🎮📊
  • Tuning Stressful Experience in Virtual Reality Games (2023) 🎮⚡
  • Evaluation of the V-Arcade Serious Games Framework for Upper Limbs Rehabilitation at Home for Children with Juvenile Idiopathic Arthritis (2022) 🕹️🏠
  • A Community-Based Activity Center to Promote Social Engagement and Counteract Decline of Elders Living Independently (2021) 👴📱
  • A Smart Ink Pen for Ecological Assessment of Age-Related Changes in Writing and Tremor Features (2021) 🖊️📈 Multimodal Empathic Feedback Through a Virtual Character (2021) 🤖🎭
  • V-Arcade: Design and Development of a Serious Games Framework to Support Upper Limbs Rehabilitation (2021) 🕹️💪 | Cited by: TBD | DOI: 10.1109/SEGAH52098.2021.9551858
  • A Tablet App for Handwriting Skill Screening at the Preliteracy Stage: Instrument Validation Study (2020) 📱📝
  • Hand Rehabilitation and Telemonitoring Through Smart Toys (2019) 🎮🧸

 

 

 

 

 

Dinesh Sharma | Computer Science | Best Researcher Award

Posted on by ScienceFather

Dr. Dinesh Sharma | Computer Science | Best Researcher Award

Dr. Dinesh Sharma, Manipal University Jaipur, India

Dr. Dinesh Sharma holds a Ph.D. in Computer Science and Engineering from Uttarakhand and an M.E. from C-DAC, Pune. With over 14 years of experience in technical and engineering education, he currently serves as an Associate Professor at Manipal University Jaipur. He has published multiple patents, including innovations in animal wellbeing and waste management. Dr. Sharma is a technical committee member for various international conferences and has acted as a guest editor for respected journals. He is also an AICTE High-Performance Computing Master Trainer, dedicated to advancing technology in education. 🌍✨

 

Publication profile

Scopus

Qualification

Dr. Dinesh Sharma is an accomplished academic in the field of Computer Science and Engineering, holding a Ph.D. from Uttarakhand Technical University. He also earned a Master’s degree in CSE from C-DAC, Pune, and a Bachelor’s degree from R.G.P.V., Bhopal. With over 14 years of experience in technical education, he currently serves as an Associate Professor at Manipal University Jaipur. Dr. Sharma has a strong research background, with multiple patents and publications focusing on innovative technologies. His contributions to academia include serving as a reviewer for numerous journals and as a technical committee member for various international conferences. 🌍✨

 

Professional Achievements 🏆

Dr. Dinesh Sharma has made significant contributions to academia and industry, serving as a Guest Editor for a special issue on “Industrial System Pioneering in Industry 4.0” in the Journal of New Materials and Electrochemical Systems. He is an AICTE High-Performance Computing Master Trainer and has been invited as a session chair at numerous international conferences, including IEEE CSNT and CICN. Dr. Sharma coordinated a five-day Faculty Development Program on IoT at Amity University and served as an Associate Editor for Pragyan Journal of Information Technology. Additionally, he reviews for various SCI, IEEE, and Scopus-indexed journals. 🌐✨

 

Awards & Guided Projects 🏅

Dr. Dinesh Sharma has successfully mentored CSE students who achieved remarkable milestones, including securing international funding of $1,000 and $250 from Latrobe University Technology Grand Challenge, where one project also won the 1st runner-up prize. Under his guidance, Mr. Ashish Kumar Mishra developed a “Smart Attendance System,” earning 1st position in a national challenge organized by Amazon and receiving ₹35,000. Additionally, Ms. Priyanshi Gupta won ₹30,000 and the runner-up prize at the “Gwalior Smart City Tech Challenge 2020.” Dr. Sharma also led the development of the web conferencing platform “Bharat Live” for online activities. 🌍🎉

 

Professional Experience 📚

Dr. Dinesh Sharma brings over 14 years of expertise in technical and engineering education, specializing in software development with 8 years of freelance experience in C#, ASP.Net, PHP, Java, and Android app development. Currently, he serves as an Associate Professor in Data Science and Engineering at Manipal University Jaipur since August 2023, where he is also a software developer, KPI coordinator, and E-cell coordinator. Previously, he worked as an Assistant Professor at Amity University Madhya Pradesh and IMS Unison University, contributing significantly as a software developer and coordinator for various academic initiatives. His journey began as the Head of the Computer Science & Engineering Department at Amardeep College of Engineering and Management. 🎓💻

 

Conclusion

Dr. Dinesh Sharma’s qualifications, innovative research contributions, professional achievements, and mentorship make him an exemplary candidate for the Best Researcher Award. His commitment to advancing technology and educating future generations in the field of computer science is commendable, and he is well-deserving of this recognition.

 

Publication Top Notes

  • Neural network-based soil parameters predictive coordination algorithm for energy efficient wireless sensor network – Cited by: 0 (2024) 🐾
  • Automatic detection and classification of plant leaf diseases using image processing: A survey – Cited by: 1 (2023) 🌱
  • Enhancing Feature Extraction in Plant Image Analysis through a Multilayer Hybrid DCNN – Cited by: 0 (2023) 🖼️
  • Comparative Analysis of Skin Cancer Detection Using Classification Algorithms – Cited by: 1 (2023) 🎗️
  • Face Mask Detection Analysis for Covid19 Using CNN and Deep Learning – Cited by: 3 (2022) 😷
  • Energy Efficient Multitier Random DEC Routing Protocols for WSN: In Agricultural – Cited by: 18 (2021) 🌾
  • A new energy efficient multitier deterministic energy-efficient clustering routing protocol for wireless sensor networks – Cited by: 34 (2020) 💡
  • Comparative energy evaluation of lEACH protocol for monitoring soil parameter in wireless sensors network – Cited by: 7 (2018) 🌍
  • Enhance PeGASIS algorithm for increasing the life time of wireless sensor network – Cited by: 6 (2018) ⚡

Federico D’ Asaro | Artificial intelligence | Best Researcher Award

Posted on by ScienceFather

Mr. Federico D’ Asaro | Artificial intelligence | Best Researcher Award

Mr. Federico D’ Asaro, Politecnico di Torino, Italy

Based on Mr. Federico D’Asaro’s background and achievements, he appears to be a strong candidate for the Research for Best Researcher Award. Here’s an evaluation of his suitability:

Publication profile

Education 🎓

  • Polytechnic University of Turin: M.Sc. in Data Science and Engineering with a thesis on algorithm discrimination. Achieved a final grade of 110/110.
  • University of Palermo: B.Sc. in Engineering and Management, graduating cum laude with a final grade of 110/110.
  • Scientific Lyceum “Galileo Galilei”: High School Diploma with a grade of 83/100.

Work Experience 💼

  • Ph.D. Student at Polytechnic University of Turin: Conducting research on Modality-Gap in multimodal feature space and submitting articles to prominent conferences.
  • AI Applied Researcher at LINKS Foundation: Developed advanced applications in business analytics, sentiment analysis, retrieval systems, and speech emotion recognition. Engaged in proposal writing and reviewing conference papers.
  • Intern at Technology Reply: Gained experience in NLP, sentiment analysis, and textual data modelization.

Skills and Competencies 🛠️

  • Proficient in multiple programming languages and tools including Python, Java, TensorFlow, PyTorch, and SQL.
  • Experienced in data visualization, machine learning, and deep learning.
  • Competent in using various IT tools and frameworks like Apache Spark and Hadoop.

Other Information 🌍

  • Languages: Fluent in Italian and proficient in English (B2 level).
  • Interests: Diverse interests including sports, literature, and technology.
  • Certifications: B2 First (FCE) and driving license.

Publication Top Notes

Zero-Shot Content-Based Crossmodal Recommendation System

Sensitive attributes disproportion as a risk indicator of algorithmic unfairness

Conclusion🏆

Mr. Federico D’Asaro demonstrates a solid academic background, relevant work experience, and a diverse skill set, aligning well with the criteria for the Research for Best Researcher Award. His ongoing research and contributions to AI applications show a strong potential for impactful research and innovation.

Souhail Dhouib | Artificial Intelligence | Best Researcher Award

Posted on by ScienceFather

Prof. Souhail Dhouib | Artificial Intelligence | Best Researcher Award

Full Professor, Higher Institute of Industrial Management, University of Sfax, Tunisia

Prof. Souhail Dhouib 🌟 is a distinguished academic and industry expert specializing in Artificial Intelligence and Operations Research. He holds the position of Full Professor at the Higher Institute of Industrial Management, University of Sfax, Tunisia, where he has taught for over twenty years. Prof. Dhouib is renowned for his pioneering work in matrix optimization concepts and has made significant contributions to decision-making and planning through his innovative algorithms and methodologies.

ProfileArtificial Intelligence 

ORCID

 

Education

Prof. Dhouib completed his Ph.D. in Quantitative Methods from the Faculty of Management and Economics Sciences, Sfax University, Tunisia (2004-2009). He also holds a Master’s degree in Operations Research and Production Management (2001-2003) and a Bachelor’s degree in Management Information Systems (1992-1996), all from the same institution. 📚🎓

Experience

Prof. Dhouib has over twenty years of extensive experience in both academia and industry. He has served as a General Manager and an Analyst Programmer, where he was involved in software development and implementation. His academic roles include positions as a Full Professor, Associate Professor, and Assistant Professor, contributing significantly to teaching and research. 🏢💻

Research Interests

Prof. Dhouib’s research focuses on Artificial Intelligence, Operations Research, and Optimization algorithms. His work spans various domains, including Logistics, Supply Chain Management, Business Intelligence Systems, and ERP. He is particularly known for his Dhouib-Matrix methods and their applications in cognitive robotics, multi-objective optimization, and path planning. 🔍📈

Awards

Prof. Dhouib’s contributions to the field have been recognized through numerous journal publications, although specific awards are not listed in the provided information. His innovative research and development efforts continue to impact the industry and academia. 🏆👏

Publications

Intelligent Path Planning for Cognitive Mobile Robot Based on Dhouib-Matrix-SPP Method (2024) – Cognitive Robotics

Multi-Start Constructive Heuristic through Descriptive Statistical Metrics: The Dhouib-Matrix-4 Metaheuristic (2024) – International Journal of Operational Research

Innovative Method to Solve the Minimum Spanning Tree Problem: The Dhouib-Matrix-MSTP (DM-MSTP) (2024) – Results in Control and Optimization

Enhancing the Dhouib-Matrix-4 Metaheuristic to Generate the Pareto Non-Dominated Set Solutions for Multi-objective Travelling Salesman Problem: The DM4-PMO Method (2024) – Results in Control and Optimization

Faster than Dijkstra and A* Methods for the Mobile Robot Path Planning Problem Using Four Movement Directions: The Dhouib-Matrix-SPP-4 (2024) – Advances in Transdisciplinary Engineering, Mechatronics and Automation Technology

Nafis Uddin Khan | Artificial Intelligence | Best Researcher Award

Posted on by ScienceFather

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 

Computer Science

Posted on by ScienceFather

Introduction of Computer Science

 

Computer Science research forms the backbone of the digital age, driving innovation and shaping the future of technology. This dynamic field explores the design, development, and application of computer systems, algorithms, and software to tackle a diverse range of challenges. It encompasses everything from artificial intelligence and data analysis to network security and human-computer interaction, making it an integral part of our increasingly interconnected world.

 

Artificial Intelligence (AI):

AI research focuses on creating intelligent systems that can learn, reason, and make decisions. Subfields within AI include machine learning, natural language processing, and computer vision, with applications in robotics, healthcare, and more.

Cybersecurity:

In an age of data breaches and cyber threats, cybersecurity research is critical. Researchers investigate methods to safeguard digital systems and networks, including encryption, threat detection, and ethical hacking.

Data Science:

Data science is all about extracting insights and knowledge from vast datasets. Researchers in this subfield develop techniques for data analysis, data mining, and predictive modeling, fueling advancements in fields like healthcare and finance.

Human-Computer Interaction (HCI):

HCI research seeks to improve the interaction between humans and computers. It involves the study of user interfaces, usability, and user experience design, ensuring technology is accessible and user-friendly.

Software Engineering:

Software engineering researchers work to develop methodologies and tools for designing and building high-quality software. This subfield includes software architecture, testing, and project management to ensure efficient and reliable software development.

Agricultural and Biological Science
Introduction of Agricultural and Biological Sciences Agricultural and Biological Sciences research plays a pivotal role in addressing the multifaceted challenges of our ever-evolving world. This field encompasses a wide array
Arts and Humanities
Introduction of Arts and Humanities Arts and Humanities research represents the intellectual and creative exploration of the human experience, culture, and society. This broad field encompasses a rich tapestry of
Biochemistry
Introduction of Biochemistry Biochemistry is a captivating scientific discipline that delves into the intricate world of molecules and processes within living organisms. It serves as the bridge between biology and
Genetics and Molecular Biology
Introduction of Genetics and Molecular Biology Genetics and Molecular Biology are at the forefront of understanding the intricate machinery that governs life itself. This dynamic field investigates the genetic material
Business
Introduction of Business Business research is the driving force behind informed decision-making in the corporate world. It encompasses an array of methodologies and disciplines that aim to understand and improve
Management and Accounting
Introduction of Management and Accounting Management and Accounting research is the backbone of effective decision-making in organizations, spanning from the corporate world to the public sector. It encompasses the systematic
Chemical Engineering
Introduction of Chemical Engineering   Chemical Engineering research plays a pivotal role in transforming raw materials into valuable products, advancing environmental sustainability, and developing innovative solutions across various industries. It
Chemistry
Introduction of Chemistry    Chemistry research lies at the heart of our understanding of matter and its interactions, and it's a cornerstone of scientific progress. Researchers in this dynamic field
Computer Science
Introduction of Computer Science   Computer Science research forms the backbone of the digital age, driving innovation and shaping the future of technology. This dynamic field explores the design, development,
Decision Sciences
Introduction of Decision Sciences   Decision Sciences research serves as a compass for informed decision-making across various industries and domains. This multidisciplinary field combines elements of mathematics, economics, psychology, and