Assistant Professor, Kalinga Institute of Industrial Technology (KIIT) Deemed to Be University, India

Dr. Subhadip Pramanik is an accomplished academic and researcher specializing in Data Science and Artificial Intelligence. He earned his Ph.D. in Data Science & AI from IIT Kharagpur in 2023. With a strong educational foundation in applied mathematics and computer science, Dr. Pramanik has made significant contributions to the field of evolutionary optimization and machine learning. Currently, he serves as an Assistant Professor at the Kalinga Institute of Industrial Technology, Bhubaneswar, India, where he teaches advanced topics in computer science. His prolific research has been published in leading journals, and he has received accolades such as the Best Paper Award at IEEE INDICON 2021.

PROFILE

Google Scholar

Orcid

Scopus

STRENGTHS FOR THE AWARD

Academic Excellence:
- Holds a Ph.D. in Data Science and AI from IIT Kharagpur, one of the most prestigious institutions in India.
- Demonstrated exceptional academic performance throughout, including high scores in M.Tech and M.Sc.
Significant Research Contributions:
- Published extensively in reputed journals and conferences, including Mathematics, Structural and Multidisciplinary Optimization, and Applied Intelligence.
- Innovations such as adaptive model selection frameworks and nature-inspired algorithms showcase expertise in solving real-world optimization problems.
- The award-winning research on “GL-DDEA” highlights the practical impact and originality of contributions in AI and Data Science.
Recognitions:
- Best Paper Award in the AI & Data Science Track at IEEE INDICON 2021, a testament to the quality and impact of his work.
- Strong citation and publication record reflecting a high level of research engagement.
Diverse Work Experience:
- Currently serving as an Assistant Professor at KIIT, mentoring undergraduate students in advanced topics such as Data Analytics, AI, and DBMS.
- Prior experience as a Research Fellow at IIT Kharagpur involved developing groundbreaking methods for engineering optimization.
Technical Expertise:
- Specialized in cutting-edge domains such as evolutionary algorithms, surrogate modeling, and high-utility itemset mining.
- Proficiency in applying research methodologies to solve expensive, data-driven optimization problems, bridging theory and application.

AREAS FOR IMPROVEMENT

Broader Collaborative Research:
- While his contributions are notable, expanding collaborations with international researchers could elevate the global visibility of his work.
Industry Engagement:
- Engagement in industry-funded projects or partnerships could demonstrate real-world applications of his research.
Interdisciplinary Applications:
- Exploring applications of his frameworks in areas beyond engineering optimization, such as healthcare or environmental science, may further diversify his portfolio.

EDUCATION

Dr. Pramanik has an extensive academic background:

Ph.D. in Data Science & AI, IIT Kharagpur (2018–2023)
M.Tech. in Computer Science & Data Processing, IIT Kharagpur (2016–2018, CGPA 8.61/10)
M.Sc. in Applied Mathematics, Vidyasagar University (2014–2016, 77%)
B.Sc. in Mathematics, Vidyasagar University (2011–2014, 65.75%)
Higher Secondary (82.8%) and Secondary (83.5%) Examinations completed in West Bengal.

This foundation underscores his expertise in applying mathematical rigor to solve complex engineering problems using AI and data science.

EXPERIENCE

Dr. Pramanik is currently an Assistant Professor at Kalinga Institute of Industrial Technology, where he teaches Data Analytics, AI, and Python to undergraduates. His research fellowship at IIT Kharagpur (2018–2023) resulted in pioneering contributions like developing evolutionary algorithms for solving expensive engineering optimization problems. His notable projects include a novel framework utilizing ant colony systems for mining high-utility itemsets and innovative surrogate modeling approaches for multi-objective optimization. With practical teaching and research experience, Dr. Pramanik bridges academic rigor with real-world applications.

AWARDS & HONORS 🏆

Best Paper Award in AI & Data Science Track, IEEE INDICON 2021
GATE 2016 Qualified: Scored 532 in Mathematics
Numerous accolades for his impactful publications and contributions to Data Science & AI research.

RESEARCH FOCUS 🔬

Dr. Pramanik focuses on evolutionary optimization, active learning, and data-driven decision-making. His research interests include:

Data-Driven Multi-Objective Optimization: Using adaptive and reliable frameworks for engineering challenges.
High-Utility Pattern Mining: Ant colony systems for large transactional datasets.
Surrogate Modeling: Combining global and local models for efficiency in offline and incremental data optimization.

PUBLICATION TOP NOTES 📚

AdaMoR-DDMOEA: Adaptive Model Selection Framework for Offline Optimization (Mathematics, 2025)
ALeRSa-DDEA: Active Learning and Reliability Sampling for Expensive Optimization (SMO, 2022)
GL-DDEA: Surrogate-Based Framework for Offline Optimization (IEEE INDICON, 2021)
Ant Colony Algorithm: Mining Closed High-Utility Itemsets (Applied Intelligence, 2021)

CONCLUSION

Subhadip Pramanik is an outstanding candidate for the Best Researcher Award due to his exemplary academic record, innovative research contributions, and impactful publications. His award-winning work and continued commitment to advancing Data Science and AI demonstrate his potential to excel further in his field. With additional focus on interdisciplinary and global collaborations, he could strengthen his position as a leading researcher in his domain.

Prasad Mutkule | Machine Learning | Best Researcher Award

Posted on 02/01/202502/01/2025 by ScienceFather

Mr Prasad Mutkule | Machine Learning | Best Researcher Award

Assistant Professor, Sanjivani College of Engineering, Kopargaon, India

Prasad Mutkule is an accomplished academic and researcher serving as an Assistant Professor at Sanjivani College of Engineering, Kopargaon. He holds expertise in Machine Learning, Data Science, and Artificial Intelligence, contributing significantly to academia and industry. His work spans developing advanced algorithms for healthcare and agriculture, with a strong emphasis on practical applications. Prasad is known for his dedication to research and education, mentoring students and fostering innovation.

PROFILE

Google Scholar

Orcid

Scopus

STRENGTHS FOR THE AWARD

ACADEMIC BACKGROUND:
- Advanced academic qualifications, including a pursuing Ph.D. in Computer Engineering, focusing on cutting-edge research.
- High academic performance in Master’s and Bachelor’s programs, showcasing a strong foundation in computer engineering.
RESEARCH CONTRIBUTIONS:
- A significant number of publications in reputed journals and conferences.
- Research topics include brain tumor segmentation, agriculture disease detection, predictive analytics in healthcare, and integration of AI/ML for societal applications like cybersecurity and smart farming.
- Contributions are well-cited, with notable impact in the field of computational intelligence and applied machine learning.
PROFESSIONAL EXPERIENCE:
- Diverse professional background encompassing academia and industry, with over 6 years in teaching and 1 year in Android development.
- Current role as an Assistant Professor at a reputed autonomous institution emphasizes leadership in research and teaching.
MULTIDISCIPLINARY IMPACT:
- Research spans critical areas such as healthcare, agriculture, and traffic prediction, reflecting versatility.
- Innovative projects like IoT-based interactive clothing and AI-based health monitoring systems underscore practical applications of research.
TEAM COLLABORATION:
- Collaboration with various researchers and authors in multiple publications, indicating strong teamwork and networking abilities.

AREAS FOR IMPROVEMENT

ONGOING RESEARCH FOCUS:
- Completing the Ph.D. will further solidify expertise and enhance research credentials.
- Exploring patent filings or practical implementations of research outcomes could amplify real-world impact.
INCREASED GLOBAL PRESENCE:
- Expanding participation in international conferences or collaborations could increase visibility on a global scale.
FOCUSED SPECIALIZATION:
- While multidisciplinary research is a strength, deeper specialization in one or two niches can establish leadership in specific domains.
FUNDING AND GRANTS:
- Securing funded projects or grants for research would demonstrate recognition and support for work.

EDUCATION

Ph.D. (Computer Engineering) – Pursuing at Vishwakarma Institute of Information Technology, Pune, affiliated with Savitribai Phule Pune University (2023–ongoing).
M.E. (Computer Engineering) – Completed at Sanjivani College of Engineering, Kopargaon, Savitribai Phule Pune University, with a CGPA of 8.25 (2016–2018).
B.E. (Computer Engineering) – Graduated from Sanjivani College of Engineering, Kopargaon, under Savitribai Phule Pune University, achieving 68.46% (2012–2016).

EXPERIENCE

Assistant Professor, Sanjivani College of Engineering (2021–present).
Assistant Professor, Shri Chatrapati Shivaji Maharaj College of Engineering, Ahmednagar (2021).
Assistant Professor, Adsul’s Technical Campus, Ahmednagar (2019–2021).
Lecturer, S.P.I.T. Polytechnic, Ahmednagar (2017–2019).
Android Developer, Advitiya IoT Solutions, Pune (2016–2017).

AWARDS AND HONORS

Recognized for impactful research contributions in Machine Learning and Artificial Intelligence.
Awarded for excellence in teaching and academic service.
Published influential papers in top-tier journals.
Honored as a mentor for guiding student innovations in computing and IoT.
Esteemed presenter at international conferences.

RESEARCH FOCUS

Prasad Mutkule focuses on developing intelligent systems using Machine Learning and Data Science. His areas of interest include healthcare diagnostics, agricultural optimization, and IoT applications. He aims to bridge the gap between academia and industry through innovative solutions in Artificial Intelligence and its transformative applications.

PUBLICATION TOP

📘 Development of machine learning and medical-enabled multimodal for brain tumor classification.
📗 Manipulation of flowering time to mitigate high temperature stress in rice.
📘 Identification of disease based on symptoms using ML.
📗 Efficient supervised learning algorithm for kidney stone prediction.
📘 One-stop solution for farmer-consumer interaction.
📗 Interactive clothing based on IoT with QR codes.
📘 A survey on interactive IoT-based clothing applications.
📗 ML algorithms for agricultural leaf disease detection.
📘 Predictive analytics for early brain tumor prevention using XAI.
📗 Applicability of AI in healthcare, banking, and education.

CONCLUSION

Prasad Mutkule has a strong academic and professional portfolio that demonstrates his expertise in machine learning, artificial intelligence, and their applications in healthcare and beyond. His research contributions are impactful, multidisciplinary, and address real-world challenges. With continued focus on specialization and global engagement, he is an excellent candidate for the Best Researcher Award.

Jiaming Zhong – Artificial intelligence – Best Researcher Award

Posted on 10/08/202410/08/2024 by ScienceFather

Jiaming Zhong - Artificial intelligence - Best Researcher Award

Wuyi university - China

AUTHOR PROFILE

SCOPUS

📚 SCIENTIFIC RESEARCH ACHIEVEMENTS

Jiaming Zhong has made significant contributions to the fields of video classification and tactile sensing. His groundbreaking papers include "Exploring Cross-video Matching for Few-shot Video Classification via Dual-Hierarchy Graph Neural Network Learning," published in Image and Vision Computing, and "Text-guided Graph Temporal Modeling for Few-Shot Video Classification," featured in Engineering Applications of Artificial Intelligence. These studies, published in top-tier journals, highlight Zhong's innovative approaches in utilizing graph neural networks and multimodal models for advanced video analysis and classification.

🛠️ PATENTS AND TECHNOLOGICAL INNOVATIONS

Zhong holds several patents that showcase his expertise in developing practical solutions for various technological challenges. His patents include methods for video anomaly classification, chip defect detection, and mobile robot obstacle avoidance. These patents reflect his commitment to translating theoretical research into tangible technological advancements that address real-world problems.

🔬 PROJECT EXPERIENCE: PEEL RECOGNITION

In a project focused on the precise identification of Chenpi years using a multimodal model, Zhong's work involved designing lightweight modules and fine-tuning models to achieve high recognition accuracy. His use of the CLIP multimodal model for feature extraction led to a remarkable 99% accuracy in recognizing Chenpi years with limited sample data. This project, detailed on GitHub, demonstrates his proficiency in applying advanced machine learning techniques to practical problems.

🎥 PROJECT EXPERIENCE: FEW-SHOT VIDEO CLASSIFICATION

Zhong's research in video behavior classification involved addressing challenges related to data scarcity and model capabilities. Collaborating with Macau University of Science and Technology and Wuyi University, he developed a dual-hierarchy graph neural network that significantly improved classification performance through cross-video frame matching. This innovative approach was published in Image and Vision Computing and showcased Zhong's ability to enhance model performance through sophisticated temporal modeling.

🔍 PROJECT EXPERIENCE: MULTIMODAL REPRESENTATION LEARNING

In a project focused on multimodal video behavior analysis, Zhong led efforts to develop a novel framework for self-supervised learning using multimodal data. This project, supported by a 500,000 RMB research grant, involved developing a text-guided feature optimization module and a query text token learning mechanism. His research aimed to leverage multimodal knowledge to improve the classification performance of few-shot video behaviors, with results published in top journals.

📈 IMPACTFUL RESEARCH AND PUBLICATIONS

Zhong's work has significantly impacted the fields of video classification and sensor technology. His papers in renowned journals and his patents contribute to advancing the understanding and application of these technologies. His research not only addresses current challenges but also paves the way for future innovations in these areas.

🏆 ACKNOWLEDGEMENTS AND RECOGNITION

Zhong's contributions to scientific research and technology have earned him recognition within the academic and professional communities. His innovative work in video classification and sensor technology continues to influence the field and inspire further research and development.

NOTABLE PUBLICATION

Ultra-sensitive and stable All-Fiber iontronic tactile sensors under high pressure for human movement monitoring and rehabilitation assessment
Authors: K. Ma, D. Su, B. Qin, Y. Xin, X. He
Year: 2024
Journal: Chemical Engineering Journal

Real-time citrus variety detection in orchards based on complex scenarios of improved YOLOv7
Authors: F. Deng, J. Chen, L. Fu, J. Li, N. Li
Year: 2024
Journal: Frontiers in Plant Science

Exploring cross-video matching for few-shot video classification via dual-hierarchy graph neural network learning
Authors: F. Deng, J. Zhong, N. Li, D. Wang, T.L. Lam
Year: 2023
Journal: Image and Vision Computing

Senbagavalli – Artificial Intelligence – Best Researcher Award

Posted on 31/07/202403/08/2024 by ScienceFather

Senbagavalli - Artificial Intelligence - Best Researcher Award

Alliance University - India

AUTHOR PROFILE

SCOPUS

EXPERT IN OPINION MINING AND FEATURE SELECTION

Senbagavalli's groundbreaking research in opinion mining of health data for cardiovascular disease diagnosis using an unsupervised feature selection algorithm spans five years. Her Ph.D. work is a testament to her dedication to leveraging data for medical advancements.

FACIAL RECOGNITION INNOVATOR

With a master's degree in engineering, Senbagavalli developed a face recognition system using Laplacian faces, showcasing her expertise in computer vision and pattern recognition. This project exemplified her ability to apply complex algorithms to practical applications within six months.

PIONEER IN UNICODE FILE SYSTEMS

During her undergraduate studies, Senbagavalli created a file system using the Unicode character set, a project completed in just six months. Her work in this area highlights her proficiency in software development and system design.

CREATOR OF GRAPHIC GAMING SYSTEMS

In her mini-project as an undergraduate, she developed a gaming system using graphics within three months. This early project laid the foundation for her interest in interactive and visual computing systems.

SEASONED ACADEMIC AND PROFESSOR

With 18 years and 7 months of teaching experience, Senbagavalli has held positions at prestigious institutions, including Alliance University and Kuppam Engineering College. Her extensive experience has made her a respected figure in the academic community.

VERSATILE SUBJECT EXPERT

Senbagavalli has taught a wide range of subjects to undergraduate, postgraduate, and Ph.D. students, including Data Modeling and Optimization, Object-Oriented Programming, and Software Engineering. Her comprehensive knowledge spans multiple domains of computer science.

ACTIVE RESEARCHER AND REVIEWER

An active member of various academic councils and editorial boards, Senbagavalli reviews for renowned publishers like Bentham Science and Elsevier. Her involvement in curriculum development, project evaluation, and seminar organization reflects her commitment to academic excellence and continuous learning.

NOTABLE PUBLICATION

Identification of Biomarker for Autism Spectrum Disorder Using EEG: A Review.
Authors: K. Lalli, M. Senbagavalli
Year: 2023
Conference: Proceedings - 2023 International Conference on Advanced Computing and Communication Technologies, ICACCTech 2023, pp. 45–50

Facemask Detection System Using CNN Model.
Authors: M. Senbagavalli, S. Debnath, R. Rajagopal, K. Ghildial
Year: 2023
Conference: International Conference on Recent Advances in Science and Engineering Technology, ICRASET 2023

An Evaluation of Machine Learning Techniques for Detecting Banking Frauds.
Authors: R. Rajagopal, M. Senbagavalli, S. Debnath, K. Darshan, K.S. Varun Tejas
Year: 2023
Conference: International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, pp. 359–365

Deep Learning Model for Flood Estimate and Relief Management System Using Hybrid Algorithm.
Authors: M. Senbagavalli, V. Sathiyamoorthi, S.K. Manju Bargavi, S. Shekarappa G., T. Jesudas
Year: 2023
Book: Artificial Intelligence and Machine Learning in Smart City Planning, pp. 29–44

An Effective Model for Predicting Agricultural Crop Yield on Remote Sensing Hyper-Spectral Images Using Adaptive Logistic Regression Classifier.
Authors: V. Sathiyamoorthi, P. Harshavardhanan, H. Azath, A.M. Viswa Bharathy, B.S. Chokkalingam
Year: 2022
Journal: Concurrency and Computation: Practice and Experience, 34(25), e7242

Fangyu Wu – Artificial Intelligence – Best Researcher Award

Posted on 20/07/202420/07/2024 by ScienceFather

Fangyu Wu - Artificial Intelligence - Best Researcher Award

AUTHOR PROFILE

SCOPUS

ACADEMIC AND PROFESSIONAL BACKGROUND

Fangyu Wu is a distinguished researcher and academic in the field of computer science, specializing in deep learning, multi-modal learning, and intelligent data analysis. He is currently an Associate Professor at Xi’an Jiaotong-Liverpool University (XJTLU) in China, where he supervises PhD and Master's students focusing on innovative research topics such as multi-modal learning and deep learning for computer vision. His previous role included co-supervising PhD students at Zhejiang University, contributing to advancements in facial recognition and image-text retrieval.

HONORS AND AWARDS

Dr. Wu's achievements have been recognized through several prestigious awards. He was named a Suzhou Youth Innovation Leading Talent in 2023 and won first prize at the 7th China Innovation Challenge for his project on intelligent tracking systems using infrared thermal imaging. Additionally, he received the Lotfi Zadeh Best Paper Award at ICMLC&ICWAPR 2017 and has been honored with the Outstanding Graduates award from Xi’an Jiaotong-Liverpool University and National Encouragement Scholarships from China.

RESEARCH PROJECTS

Fangyu Wu leads several high-impact research projects. These include “Intelligent Multimodal Data Analysis for Digital Twin Cities” under the Gusu Innovation and Entrepreneurship Leading Talents Programme, and “Relational Modeling and Reasoning for Reliable Cross-Modal Retrieval” funded by the Zhejiang Natural Science Foundation. His projects also cover advanced topics such as distributed AI platforms for Metaverse scenarios and optimization software for injection molding processes.

PUBLICATIONS

Dr. Wu has an extensive list of publications in top-tier conferences and journals. Notable works include papers on fine-grained image-text matching, relation-aware prototype networks, and pose-robust face recognition. His research has been featured at prestigious conferences such as CVPR, ECCV, and ICPR, showcasing his contributions to advancements in deep learning and computer vision.

CONFERENCE ORGANIZATION

In addition to his research, Fangyu Wu plays a vital role in organizing academic conferences. He served as the Publication Chair for the IEEE 17th International Conference on Computer Science & Education (ICCSE 2022) and as General Co-Chair for the 5th International Symposium on Emerging Technologies for Education (SETE 2020). His involvement ensures the smooth execution of these events and contributes to the dissemination of cutting-edge research.

STUDENT SUPERVISION

Fangyu Wu is actively engaged in supervising students at both the PhD and Master’s levels. He currently supervises a PhD student at XJTLU focusing on multi-modal learning and has previously co-supervised a PhD student at Zhejiang University on deep learning for computer vision. His mentorship extends to six Master’s students at XJTLU and three at Zhejiang University, covering areas such as facial recognition and image-text retrieval.

COMPETITIONS AND RECOGNITION

Dr. Wu has achieved notable success in various competitions. His project on human motion recognition based on deep neural networks won third prize at the China First Smart Manufacturing and Big Data Innovation Competition. Additionally, his participation in competitions has been marked by significant awards, including the first prize in the China Innovation Challenge for his intelligent tracking system.

NOTABLE PUBLICATION

Fine-grained Image-text Matching by Cross-modal Hard Aligning Network
- Authors: Pan, Z., Wu, F., Zhang, B.
- Year: 2023
- Conference: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)
- Pages: 19275–19284
Knowledge-embedded Prompt Learning for Zero-shot Social Media Text Classification
- Authors: Li, J., Chen, Q., Wang, W., Wu, F.
- Year: 2023
- Conference: IEEE International Conference on Smart Computing (SMARTCOMP)
- Pages: 222–224
Kernel Triplet Loss for Image-Text Retrieval
- Authors: Pan, Z., Wu, F., Zhang, B.
- Year: 2022
- Conference: Computer Animation and Virtual Worlds
- Article: e2093
FaceCaps for Facial Expression Recognition
- Authors: Wu, F., Pang, C., Zhang, B.
- Year: 2021
- Conference: Computer Animation and Virtual Worlds
- Article: e2021

Pramod Patil – Deep Learning and Smart Grid – Best Researcher Award

Posted on 07/06/202408/06/2024 by ScienceFather

Pramod Patil - Deep Learning and Smart Grid - Best Researcher Award

Dr.D.Y.Patil Institute of Technology - India

AUTHOR PROFILE

Google Scholar

ACADEMIC EXCELLENCE AND PROFESSIONAL JOURNEY 🎓

Pramod Patil's academic odyssey commenced with a Bachelor's degree in Computer Science and Engineering from S.G.G.S. College of Engineering and Technology, Nanded, followed by a Master's and Ph.D. in Computer Engineering from Govt. College of Engineering, Pune. Since November 2001, he has been an integral part of Dr.D.Y.Patil Institute of Technology, Pune, where he has held various academic positions, culminating in his current role as Professor.

EXEMPLARY ADMINISTRATIVE ROLES AND LEADERSHIP 🏢

Throughout his tenure, Patil has demonstrated exemplary leadership and administrative acumen. From serving as Dean and Principal to holding pivotal roles such as Vice Principal and Head of Department, his leadership has been instrumental in shaping the academic and administrative landscape of his institution.

COMMITMENT TO ACADEMIC ACCREDITATION AND ASSESSMENT 📚

Patil's commitment to academic quality and accreditation is evidenced through his involvement in various accreditation processes at both the institute and university levels. His expertise in accreditation, coupled with his roles as a member of inquiry committees and subject expert, underscores his dedication to upholding academic standards and fostering institutional growth.

PROFESSIONAL ENGAGEMENT AND MEMBERSHIPS 🔬

As a lifelong learner and academic stalwart, Patil is actively engaged in professional societies such as the Indian Society for Technical Education (ISTE), Computer Society of India (CSI), and Association of Computing Machinery (ACM). His membership and contributions to these esteemed organizations reflect his commitment to advancing the field of computer engineering.

RECOGNITION AND AWARDS 🏆

Patil's contributions to academia have garnered widespread recognition and acclaim. From receiving Best Paper Awards to being appointed as Dean of the Faculty of Science and Technology at Savitribai Phule Pune University, his accolades underscore his scholarly prowess and leadership excellence.

INSPIRING FUTURE GENERATIONS AND MENTORSHIP 🌱

As a mentor and guide, Patil has played a pivotal role in shaping the careers of numerous students and researchers. His dedication to nurturing talent and fostering academic excellence has left an indelible mark on the academic community, inspiring generations of scholars to pursue their academic and professional aspirations.

INNOVATIVE RESEARCH ENDEAVORS AND CONTRIBUTIONS 🚀

Patil's research endeavors have spanned diverse domains such as machine learning, data security, blockchain, and smart grid technology. His prolific publication record, patent contributions, and research projects highlight his commitment to advancing knowledge and addressing real-world challenges through innovative research methodologies.

NOTABLE PUBLICATION

Skewed Evolving Data Streams Classification with Actionable Knowledge Extraction using Data Approximation and Adaptive Classification Framework 2023 (7)

Context-aware clustering and the optimized whale optimization algorithm: An effective predictive model for the smart grid 2023 (9)

Blockchain-based security services for fog computing 2021 (16)

EFFECT OF EARLY FUNCTIONAL MOBILITY ON FUNCTIONAL INDEPENDENCE IN INCOMPLETE PARAPLEGIC INDIVIDUALS. 2022 (3)

Jamin Rahman Jim – Generative AI – Young Scientist Award

Posted on 02/05/2024 by ScienceFather

Jamin Rahman Jim - Generative AI - Young Scientist Award

Advanced Machine Intelligence Research Lab - Bangladesh

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Jamin Rahman Jim's academic journey commenced with a Bachelor of Science degree in Computer Science and Engineering, with a major in Information Systems, from the American International University-Bangladesh. His exceptional academic performance, evidenced by a final grade of 3.96/4.00, was complemented by a thesis focusing on assessing Personalized Federated Learning Algorithms for Pattern Recognition Tasks.

PROFESSIONAL ENDEAVORS

Jamin Rahman Jim has established himself as a dedicated researcher in the field of artificial intelligence and machine learning. His roles as a Research Assistant at Deepchain Labs and subsequently as a Researcher at the Advanced Machine Intelligence Research Lab (AMIR Lab) reflect his commitment to advancing knowledge and contributing to cutting-edge research projects.

CONTRIBUTIONS AND RESEARCH FOCUS

With a focus on artificial intelligence and machine learning, Jamin Rahman Jim has made significant contributions to the field through his publications and projects. His research spans various domains, including the trustworthy metaverse, NLP-based sentiment analysis, deep learning for medical image segmentation, and user authentication and authorization in cybersecurity. Through preprints and published articles, he continues to explore innovative approaches and address challenges in the application of machine learning techniques.

IMPACT AND INFLUENCE

Jamin Rahman Jim's research has garnered attention within the academic community and beyond, as evidenced by his publications in reputable journals and his receipt of prestigious awards and grants. His work on generative AI in medical imaging, fusion-enhanced terrain detection, and explainable AI approaches has the potential to influence the development of AI systems in various domains, including healthcare, autonomous vehicles, and cybersecurity.

ACADEMIC CITES

Jamin Rahman Jim's publications in journals such as IEEE Access, Natural Language Processing Journal, and Computers and Electrical Engineering have been cited by fellow researchers, indicating the relevance and impact of his work. His research on generative AI in medical imaging, personalized federated learning algorithms, and lightweight human activity recognition frameworks has contributed to advancing knowledge in the field of artificial intelligence.

LEGACY AND FUTURE CONTRIBUTIONS

As Jamin Rahman Jim continues his academic and professional journey, his legacy lies in his dedication to advancing the field of artificial intelligence and machine learning. Through his ongoing research projects, publications, and collaborations, he aims to address critical challenges and contribute to the development of innovative AI solutions. His focus on generative AI in medical imaging underscores his commitment to leveraging AI for improved healthcare outcomes and societal impact.

NOTABLE PUBLICATION

Generative Adversarial Networks (GANs) in Medical Imaging: Advancements, Applications and Challenges 2024

Toward Trustworthy Metaverse: Advancements and Challenges 2023 (4)

Samir Khatir – AI for fast prediction – Best Researcher Award

Posted on 30/03/202430/03/2024 by ScienceFather

Samir Khatir - AI for fast prediction - Best Researcher Award

Ho Chi Minh City Open university - Belgium

AUTHOR PROFILE

Google Scholar

Scopus

EARLY ACADEMIC PURSUITS

Dr. Samir Khatir embarked on his academic journey by earning a PhD in Mechanical Engineering from Boumerdes University, Algeria, in collaboration with Centre Val de Loire, France, focusing on damage detection using optimization techniques. He later pursued a second PhD in Civil Engineering at Ghent University, Belgium, specializing in artificial intelligence for fast crack identification in steel plate structures. His academic pursuits reflect a strong foundation in engineering and a commitment to advancing knowledge in his field.

PROFESSIONAL ENDEAVORS

Dr. Samir Khatir has held various prestigious positions, including Technical Manager at Btecch in Brussels, Belgium, and part-time distinguished researcher at CEATS Centre, Ho Chi Minh City Open University, Vietnam. Additionally, he serves as an editor-in-chief and member of the editorial board for several scientific journals, contributing to the dissemination of knowledge in his field. His extensive experience spans research, academia, and industry, showcasing his versatility and expertise.

CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Samir Khatir's research focuses on a wide range of topics, including characterization of metals and composite materials, design optimization, damage identification, static and dynamic tests, machine learning, and tribological analysis in metal contact. He has made significant contributions to projects addressing modal updating and structural health monitoring in metal bridges, fast crack identification using machine learning in steel plates, and impact identification in composite materials. His research underscores his dedication to advancing engineering solutions through innovative methodologies.

IMPACT AND INFLUENCE

Dr. Samir Khatir's work has had a profound impact on the field of engineering, particularly in the areas of structural health monitoring, damage identification, and optimization techniques. His collaborations with prestigious institutions and his role as a visiting researcher and research member highlight his influence and recognition within the global research community. His contributions have contributed to advancements in the understanding and application of artificial intelligence for predictive analysis in engineering structures.

ACADEMIC CITES

Dr. Samir Khatir's research has been widely cited and recognized in the academic community, with numerous publications and collaborations with renowned institutions. His work has been instrumental in shaping the discourse and driving innovation in engineering research, particularly in the application of machine learning techniques for fast prediction and damage identification in structural materials.

LEGACY AND FUTURE CONTRIBUTIONS

As Dr. Samir Khatir continues to excel in his career, his legacy in the field of engineering is poised to grow. His future contributions are expected to further enhance our understanding of structural behavior and advance predictive modeling techniques using artificial intelligence. Through his dedication to research and innovation, he will continue to shape the future of engineering and inspire the next generation of researchers and practitioners.

NOTABLE PUBLICATION

An efficient approach for damage identification based on improved machine learning using PSO-SVM 2022 (82)