Nirmal Varghese Babu | Artificial Intelligence | Best Researcher Award 

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Dr. Nirmal Varghese Babu | Artificial Intelligence | Best Researcher Award 

Dr. Nirmal Varghese Babu | Karunya Institute of Technology and Sciences | India

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Early Academic Pursuits

Dr. Nirmal Varghese Babu began his academic journey with a strong inclination toward computer science and technology. He completed his B.Tech in Information Technology from Karunya Institute of Technology and Sciences, Coimbatore, in 2017 with a CGPA of 8.0. His passion for research and innovation in computing led him to pursue an M.Tech in Computer Science & Engineering from Amal Jyothi College of Engineering, Kanjirappally (2017–2019), graduating with an impressive CGPA of 8.72. Currently, he is pursuing a Ph.D. in Computer Science & Engineering from Karunya Institute of Technology and Sciences, expected to be completed in 2025. His academic excellence was rooted in his formative years at Mathews Mar Athanasius Residential School, Chengannur, where he built a strong foundation in analytical and computational thinking.

Professional Endeavors

Dr. Nirmal Varghese Babu is currently serving as an Assistant Professor at the School of Computer Science and Technology, Karunya Institute of Technology and Science, Coimbatore (since July 26, 2022). His professional endeavors include teaching, research, and mentoring in various areas of computer science and Artificial Intelligence. He has delivered lectures on Artificial Intelligence: Principles and Techniques, Cloud Computing for Data Analytics, AI for Games, AI for Food Processing Engineering, AI for Biotechnology, and MLOps. Alongside teaching, he mentors undergraduate students, coordinates final-year projects, and supervises academic research initiatives. His teaching methodology emphasizes experiential learning, guiding students to bridge theoretical knowledge with real-world technological applications.

Contributions and Research Focus

Dr. Nirmal’s research contributions revolve around Artificial Intelligence, machine learning, data analytics, and real-time systems. His M.Tech project, Multiclass Sentiment Analysis of Social Media Data using Neural Networks, explored advanced deep learning algorithms like CNN and RNN for classifying sentiment across social media platforms, specifically Twitter. This study integrated text and emoticon data for multiclass classification using one-hot encoding and neural networks. His earlier project, Real-Time Traffic Incident Detection using Social Media Data, demonstrated innovative use of Natural Language Processing to detect and analyze traffic incidents using Twitter data, integrating AI for real-time decision-making. His work exemplifies how Artificial Intelligence can transform data into actionable insights for societal and industrial benefit.

Impact and Influence

Dr. Nirmal Varghese Babu’s impact as an educator and researcher extends across academia and applied technology. At Karunya Institute, he plays a vital role in shaping the next generation of AI-driven engineers and data scientists. As a mentor and coordinator, he has successfully guided numerous B.Tech projects, fostering innovation in the domains of Artificial Intelligence, MLOps, and machine learning. His pedagogical style emphasizes research-based learning, promoting creative problem-solving and real-world application of AI. Through his leadership in academic project coordination and curriculum development, he has significantly influenced the integration of AI-based methodologies into modern engineering education.

Academic Cites

Dr. Nirmal’s academic contributions are recognized through his published works, research projects, and student-guided studies. His projects on sentiment analysis and traffic incident detection have been well-cited and appreciated within the AI and data analytics community. The relevance of his research is reflected in growing academic references to his work in areas such as neural networks, data mining, and sentiment classification. His scholarly achievements continue to inspire students and researchers pursuing advanced studies in Artificial Intelligence and computational learning.

Legacy and Future Contributions

Looking ahead, Dr. Nirmal Varghese Babu aims to expand his research in Artificial Intelligence, focusing on its integration with real-time analytics, smart systems, and cognitive computing. His future contributions are expected to advance the use of AI in multidisciplinary fields such as biotechnology, healthcare, and environmental systems. As an educator, his legacy lies in his ability to inspire and mentor young researchers, promoting a culture of innovation and ethical AI development. His ongoing research and academic leadership will undoubtedly continue to shape the evolution of AI-driven solutions and their transformative potential across industries.

Artificial Intelligence

Dr. Nirmal Varghese Babu’s expertise in Artificial Intelligence is evident through his teaching, research, and innovation in deep learning, neural networks, and data analytics. His projects and mentorship highlight the transformative role of Artificial Intelligence in addressing real-world challenges. The continued advancement of Artificial Intelligence under his guidance promises to create meaningful impact in both academic and applied technological domains.

Featured Publications

Babu, N. V., & Kanaga, E. G. M. (2022). Sentiment analysis in social media data for depression detection using artificial intelligence: A review. SN Computer Science, 3(1), 1–15. https://doi.org/10.1007/s42979-021-00921-2

Babu, D. E. G. M. K. N. V. (2022). Sentiment analysis in social media data for depression detection using artificial intelligence: A review. SN Computer Science, 3, 350.

Babu, N. V., & Rawther, F. A. (2021). Multiclass sentiment analysis in text and emoticons of Twitter data: A review. Proceedings of the Second International Conference on Networks and Advances in Computational Technologies (NetACT).

Prince, S. C., & Babu, N. V. (2024). Advancing multiclass emotion recognition with CNN-RNN architecture and illuminating module for real-time precision using facial expressions. Proceedings of the 2024 International Conference on Advances in Modern Age Technologies for Sustainable Development (AMATS).

Babu, N. V., Kanaga, E. G. M., Kattappuram, J. T., & Benny, R. V. (2023). AI-based EEG analysis for depression detection: A critical evaluation of current approaches and future directions. Proceedings of the 2023 International Conference on Computational Intelligence and Sustainable Technologies (CIST).

Babu, D. E. G. M. K. N. V. (2022). Depression analysis using electroencephalography signals and machine learning algorithms. Proceedings of the Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT).

Adityasai, B., & Babu, N. V. (2024). Advancing Alzheimer’s diagnosis through transfer learning with deep MRI analysis. Proceedings of the 2024 International Conference on Advances in Modern Age Technologies for Sustainable Development (AMATS).

Babu, N. V., & Kanaga, E. G. M. (2023). Multiclass text emotion recognition in social media data. In Machine Intelligence Techniques for Data Analysis and Signal Processing (pp. 123–135). Springer.

Rawther, F. A., & Babu, N. V. (2019). User behavior analysis on social media data using sentiment analysis or opinion mining. International Research Journal of Engineering and Technology (IRJET), 6(6), 3081–3085.

Jinkai Zheng | Computer Vision | Best Researcher Award 

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Prof. Jinkai Zheng | Computer Vision | Best Researcher Award 

Hangzhou Dianzi University, China

Prof. Jinkai Zheng is a Distinguished Associate Researcher at Hangzhou Dianzi University, Director of the Scientific Research Management Department at the Hangzhou Dianzi University Lishui Research Institute, and an active member of the Multimedia and Biometric Recognition Professional Committees of the China Society of Image and Graphics. His research focuses on artificial intelligence, computer vision, and multimedia analysis, with a particular emphasis on gait recognition and human-centered intelligent analysis. He has published over 40 academic documents, including multiple first-author and corresponding-author papers in top-tier venues such as CVPR, ACM Multimedia, and IEEE Transactions on Multimedia, accumulating more than 900 citations with an h-index of 16 (Google Scholar, 2025). His contributions include the Gait3D dataset, now a widely adopted benchmark by over 300 prestigious institutions worldwide, including Columbia University, University of Pennsylvania, Johns Hopkins University, and NUS. He has received notable accolades, such as the Special Prize of the 2024 Wu Wenjun Artificial Intelligence Science and Technology Progress Award, the Outstanding Paper Award at the 2023 CSIG Youth Scientists Conference, and the Best Paper Award-Honorable Mention at IEEE ISCAS 2021. With four authorized invention patents, long-term service as a reviewer for leading journals and conferences, and significant participation in national R&D projects, Prof. Zheng has become a recognized young leader in advancing AI-driven multimedia understanding.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Zheng, J., Liu, X., Gu, X., Sun, Y., Gan, C., Zhang, J., Liu, W., & Yan, C. (2022). Gait recognition in the wild with multi-hop temporal switch. Proceedings of the 30th ACM International Conference on Multimedia, 6136–6145.

Zheng, J., Liu, X., Wang, S., Wang, L., Yan, C., & Liu, W. (2023). Parsing is all you need for accurate gait recognition in the wild. Proceedings of the 31st ACM International Conference on Multimedia, 116–124.

Zheng, J., Liu, X., Yan, C., Zhang, J., Liu, W., Zhang, X., & Mei, T. (2021). Trand: Transferable neighborhood discovery for unsupervised cross-domain gait recognition. 2021 IEEE International Symposium on Circuits and Systems (ISCAS), 1–5. IEEE.

Zheng, J., Liu, X., Zhang, B., Yan, C., Zhang, J., Liu, W., & Zhang, Y. (2024). It takes two: Accurate gait recognition in the wild via cross-granularity alignment. Proceedings of the 32nd ACM International Conference on Multimedia, 8786–8794.

Yuan, S., Zheng, J., Li, X., Sun, Y., Li, W., Gao, R., Omar, M. H., & Zhang, J. (2025). Noisy label learning for gait recognition in the wild. Electronics, 14(19), 3752.

Zhang, S., Zheng, J., Zhu, S., & Yan, C. (2025). TrackletGait: A robust framework for gait recognition in the wild. arXiv preprint arXiv:2508.02143.

Zheng, J., Liu, X., Liu, W., He, L., Yan, C., & Mei, T. (n.d.). Supplementary material for “Gait recognition in the wild with dense 3D representations and a benchmark.”

Roshni Singh | Computer Vision | Best Researcher Award

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Ms. Roshni Singh | Computer Vision | Best Researcher Award

Ms. Roshni Singh | Computer Vision | Best Researcher Award

Delhi Technological University, India

Profile

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🎓 Early Academic Pursuits

Ms. Roshni Singh began her academic journey with a strong foundation in Information Technology, earning her Bachelor of Technology from Sri Sai College of Engineering & Technology, Pathankot, with a commendable score of 75%. Her pursuit of deeper knowledge led her to complete her Master of Technology in Computer Science and Engineering from Madan Mohan Malaviya University of Technology (MMMUT), Gorakhpur, securing 77.2%. With a vision to contribute to innovative technologies, she is currently pursuing a Ph.D. in Software Engineering at Delhi Technological University (DTU), New Delhi, focusing on Human Activity Recognition in Computer Vision since January 2022.

💼 Professional Endeavors

Ms. Singh has garnered valuable academic and industrial experience. She worked as an Assistant Professor (Visiting Faculty) in the Computer Science and Engineering Department at Motilal Nehru National Institute of Technology (MNNIT), Allahabad from January 2019 to January 2022, where she actively engaged in mentoring students and research activities. Prior to academia, she contributed as a Software Developer at IBM Cloud, Gurgaon (2017–2019), and Sysacs Tech Pvt. Ltd., Noida (2013–2014), strengthening her expertise in real-world software systems.

🔬 Research Focus and Contributions

Ms. Singh’s research interest lies in Computer Vision, Image Processing, Deep Learning, and Machine Learning. Her doctoral work targets Human Activity Recognition using deep learning techniques to improve surveillance and security systems. She has authored several high-impact publications in SCIE and Scopus-indexed journals and conferences. Notably, her work on ConvST-LSTM-Net and STAD-ConvBi-LSTM showcases advanced spatio-temporal modeling for abnormal activity detection. Her collaborations have resulted in recognition, including Best Paper Awards at ICICC-2025 and ICRAECA-2025.

🌐 Impact and Influence

Ms. Singh's publications reflect her contribution to both academic and applied research. Her work in journals such as the Journal of Visual Communication and Image Representation and the International Journal of Multimedia Information Retrieval is not only cited in academic circles but also relevant to industries working in surveillance and AI-based systems. Her active participation as a Ph.D. Representative, Research Council Group Member, and Joint Secretary of Reflect DTU highlights her commitment to fostering a strong research culture and academic governance.

📚 Academic Citations & Publications

Her most impactful papers include:

  • ConvST-LSTM-Net in International Journal of Multimedia Information Retrieval (IF 3.6)

  • STAD-ConvBi-LSTM in Journal of Visual Communication and Image Representation (IF 2.6)

  • Multiple conference papers awarded Best Paper Certificates
    Her citation count continues to grow, underscoring her role in advancing the field of intelligent systems and computer vision.

💻 Technical Skills

Ms. Singh is proficient in Python, MATLAB, and cloud computing frameworks. Her development experience is backed by real-world projects, including website development for the Ministry of Road Transport & Highways and High-Performance Computing at IIT Delhi. Her hands-on approach in combining software engineering with AI research gives her a unique edge in her field.

👩‍🏫 Teaching Experience

At MNNIT Allahabad, Ms. Singh contributed to teaching core computer science courses, while also mentoring students in project work and research writing. Her teaching philosophy emphasizes applied learning, fostering critical thinking and innovation in emerging areas like AI and cloud computing.

🏆 Accomplishments & Leadership Roles

Ms. Singh's achievements extend beyond research. She has:

  • Represented Ph.D. scholars in departmental meetings at DTU

  • Actively contributed to student development via training, placements, and workshops

  • Successfully anchored and coordinated Visions'24, a 24-hour hackathon

  • Volunteered in various university-level events, showcasing her organizational and leadership capabilities

🧪 Workshops and Faculty Development 🎓

She has upskilled through various FDPs and seminars, including:

  • Information Security and Privacy (ISP-2021) at MNNIT

  • Applied AI & ML with Python and MATLAB (AICTE Sponsored)

  • Cybercrime, NLP, Ethical Hacking, and IPR workshops
    These engagements reflect her ongoing commitment to academic growth and technological awareness.

🌱 Legacy and Future Contributions

Ms. Roshni Singh is poised to make long-term contributions in the intersection of AI, human-centric computing, and education. Her future aspirations include enhancing smart surveillance systems, mentoring young researchers, and fostering international collaborations. With a blend of industry expertise and academic depth, she is shaping up as a key influencer in AI research from India.

📚 Selected Publications

  • Title: ConvST-LSTM-Net: Convolutional Spatiotemporal LSTM Networks for Skeleton-Based Human Action Recognition

  • Authors: R. Singh, A. Sharma

  • Journal: International Journal of Multimedia Information Retrieval

  • Year: 2023

  • Title: High-Performance Fuzzy Optimized Deep Convolutional Neural Network Model for Big Data Classification Based on the Social Internet of Things

  • Authors: B. Shaji, R.L.R. Singh, K.L. Nisha

  • Journal: The Journal of Supercomputing, Vol. 79 (9), pp. 9509–9537

  • Year: 2023

  • Title: Privacy Preserving in TPA for Secure Cloud by Using Encryption Technique

  • Authors: R. Singh, S. Prakash

  • Journal: 2017 International Conference on Innovations in Information, Embedded and Communication Systems

  • Year: 2017

  • Title: Education and Learning: Preliminary Findings from the Young Lives Round 5 Survey in India

  • Author: R. Singh

  • Journal: Young Lives

  • Year: 2017

  • Title: Enhancement of Resource Allocation Using Load Balancing in Cloud Computing

  • Authors: R. Singh, S. Prakash

  • Journal: International Journal of Advanced Research in Computer Science, Vol. 8 (5)

  • Year: 2017

Mr. Hussm Rostum | Computer Science | Best Researcher Award

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Mr. Hussm Rostum | Computer Science | Best Researcher Award

Miskolc University, Institute of Automation and Info-communication, Hungary.

Hussam Rostum is a PhD candidate and researcher at the University of Miskolc in Hungary, specializing in computer vision for autonomous drone navigation. With a strong background in telecommunications and electronics, he blends academic excellence with hands-on experience as a part-time software engineer at FIEK. Hussam is known for developing cutting-edge solutions in industrial automation, biomedical imaging, and human–machine interfaces. Fluent in Arabic and English, he brings international insight into interdisciplinary research projects, merging software innovation with engineering systems.

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🎓 Education

Hussam holds a BSc and MSc in Telecommunication and Electronic Engineering, equipping him with deep theoretical and practical knowledge in signal processing, system design, and electronics. Currently, he is pursuing a PhD in Information Science at the University of Miskolc, focusing on AI-based vision systems for autonomous drone operations.

💼 Experience

Hussam serves as an Assistant Researcher and Part-time Software Engineer at FIEK, where he builds C# monitoring software, implements PLC-to-PC communications, and automates data workflows using Linux, Docker, and Excel. His professional journey includes work as a Full Stack Developer and Telecom Engineer, with experience in GUI development, DevOps collaboration, and .NET technologies.

🔬 Research Interests

📸 Computer Vision & Image Processing

🤖 Autonomous Systems & Drone Navigation

🩺 Biomedical Imaging & Oxygen Saturation Estimation

🔬 Optical System Design (Zemax)

⚙️ Industrial Automation & Data Visualization

🧠 Human–Machine Interfaces & Sensor Integration

📚 Selected Publications

Enhancing Machine Learning Techniques in VSLAM for Robust Autonomous Unmanned Aerial Vehicle Navigation
📅 2025-04-02 | 📰 Electronics
📌 Focus: Improving Visual SLAM with machine learning for UAVs in complex environments.
🔗 DOI: 10.3390/electronics14071440
👥 Co-author: József Vásárhelyi

Comparing the Effectiveness and Performance of Image Processing Algorithms in Face Recognition
📅 2024-05-22 | 📚 Conference Paper
📌 Focus: Evaluation of various image processing techniques for face recognition applications.
🔗 DOI: 10.1109/ICCC62069.2024.10569864
👥 Co-author: József Vásárhelyi

FPGA Implementation in Mobile Robot Applications: State of the Art Review
📅 2023-12-20 | 📰 Multidiszciplináris Tudományok
📌 Focus: Overview of FPGA-based systems in robotics.
🔗 DOI: 10.35925/j.multi.2023.2.21
👥 Co-authors: Omar M. Salih, Noha Hammami

An Overview of Energies Problems in Robotic Systems
📅 2023-12-14 | 📰 Energies
📌 Focus: Challenges in energy management for robotic systems.
🔗 DOI: 10.3390/en16248060
👥 Co-authors: József Vásárhelyi, Omar M. Salih, Rabab Benotsname

A Review of Using Visual Odometry Methods in Autonomous UAV Navigation in GPS-Denied Environments
📅 2023-12-01 | 📰 Acta Universitatis Sapientiae, Electrical and Mechanical Engineering
📌 Focus: Use of visual odometry for UAVs in GPS-denied settings.
🔗 DOI: 10.2478/auseme-2023-0002
👥 Co-author: József Vásárhelyi

 

 

 

 

Mr. Getachew Ambaye | Soft Robotics | Best Researcher Award

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Mr. Getachew Ambaye | Soft Robotics | Best Researcher Award

Wichita State University, United States.

Getachew Ambaye is an accomplished researcher, educator, and engineer specializing in industrial and mechanical engineering. Based in Wichita, KS, USA, he is currently completing his Ph.D. in Industrial & Manufacturing Engineering at Wichita State University (WSU). With extensive experience in academia and industry, he has contributed significantly to mechanical design, robotics, and manufacturing research. Getachew has a strong publication record in high-impact journals and actively participates in engineering education and research projects.

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Education 🎓

Getachew Ambaye is a dedicated researcher and engineer with a strong academic background in industrial and mechanical engineering. He is currently completing his Ph.D. in Industrial & Manufacturing Engineering at Wichita State University, USA (2022–Present) and is ready to defend his dissertation. Prior to this, he pursued a Higher Diploma Program at Bahir Dar Institute of Technology (BiT), Ethiopia (2021–2022) to enhance his expertise in engineering education. He holds an MSc. in Mechanical Design Engineering from Jimma Institute of Technology (JiT), Ethiopia (2017–2020), where he focused on advanced mechanical design principles and numerical analysis. His journey in engineering began with a BSc. in Mechanical Engineering from Jimma Institute of Technology (JiT), Ethiopia (2012–2016), providing him with a solid foundation in mechanical systems, design, and manufacturing. Through his academic and research pursuits, Getachew continues to contribute to advancements in robotics, manufacturing, and industrial automation.

Experience 💼

Teaching & Academic Positions

Getachew Ambaye has extensive teaching experience in engineering education across multiple institutions. Since 2022, he has been an Instructor at Wichita State University, USA, where he teaches IME 222: Engineering Graphics, its associated IME 222L lab (focusing on 3DX & CATIA V5), and serves as a Graduate Teaching Assistant (GTA) for IME 425: Kinematics and Dynamics Design. In 2024, he joined Hesston College, USA, as an Engineering Professor, where he teaches ENGR 422: Design of Machines, mentors students in ENGR 477 & 478: Senior Design Capstone Project, and guides courses in ENGR 372 & 371: Mechatronic System Design & Fundamentals. Before moving to the U.S., he was a Lecturer at Bahir Dar Institute of Technology (BiT), Ethiopia (2020–2022) and served as an Assistant Lecturer and Lecturer at Jimma Institute of Technology (JiT), Ethiopia (2016–2020). Additionally, he contributed as a Guest Lecturer/Trainer at Ethio Engineering Group (EEG), Ethiopia (2021–2022), delivering specialized training programs.

Research Interests 🔬

Soft Robotics & Finite Element Analysis

Machine Learning for Industrial Applications

Mechanical System Dynamics & Vibration Analysis

Product Design & Development

Advanced Manufacturing Processes

Awards & Recognitions 🏆

Dr. David M. Aber Scholarship, Wichita State University (2024)

Volunteer & Participant, 2024 COExperience & MBSE Cyber Systems Symposium

Presenter, Multiple international conferences including IWAMA, ICAST, and ICT4DA

Selected Publications 📚

Soft Robot Workspace Estimation via Finite Element Analysis and Machine Learning
Actuators, 2025 | DOI: 10.3390/act14030110
Contributors: Getachew Admassie Ambaye, Enkhsaikhan Boldsaikhan, Krishna Krishnan

Soft Robot Design, Manufacturing, and Operation Challenges: A Review
Journal of Manufacturing and Materials Processing, 2024 | DOI: 10.3390/jmmp8020079
Contributors: Getachew Admassie Ambaye, Enkhsaikhan Boldsaikhan, Krishna Krishnan

Robot Arm Damage Detection using Vibration Data and Deep Learning
Neural Computing and Applications, 2024 | DOI: 10.1007/s00521-023-09150-3
Contributors: Getachew Ambaye, Enkhsaikhan Boldsaikhan, Krishna Krishnan

Contact Temperature Analysis of the Classical Geneva Mechanism through Numerical Methods
Materials Today: Proceedings, 2022 | DOI: 10.1016/j.matpr.2022.01.420
Contributors: Getachew A. Ambaye, Hirpa G. Lemu, Mesay A. Tolcha

Numerical Stress Analysis and Fatigue Life Prediction of the Classical External Geneva Mechanism
Book Chapter, 2022 | DOI: 10.1007/978-981-19-0572-8_23
Contributors: Getachew A. Ambaye, Hirpa G. Lemu

 

 

Dr. Gunasekar Tharmalingam | Control Theory | Best Researcher Award

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Dr. Gunasekar Tharmalingam | Control Theory | Best Researcher Award

Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology (Deemed to be University), India.

Dr. S/Lt. Gunasekar T is a distinguished academician and researcher based in Chennai, India. Currently a professor and Head of Student Welfare at Vel Tech University, he has over 16 years of research and teaching experience. He holds a Ph.D. in Differential Equations from Karunya University, Coimbatore, and has also pursued advanced studies in Augmented Reality and Virtual Reality (AR & VR) at IIT Jodhpur. Apart from his academic role, Dr. Gunasekar is deeply involved in various administrative duties such as serving as an Associate NCC Officer and contributing to various national and international academic initiatives.

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Education 🎓

Dr. Gunasekar's educational background is extensive and diverse. He completed his Ph.D. in Differential Equations from Karunya University, Coimbatore, in June 2014, where his dissertation focused on "Existence and Controllability Results for Impulsive Integro-differential Systems with Infinite Delay." He is currently pursuing an M.Tech in AR & VR at IIT Jodhpur. His qualifications include a B.Ed. in Mathematics from Alwin College of Education, an M.Sc. in Mathematics from both R.K.M. Vivekananda College and Tamil University, and an M.Phil. in Functional Analysis from Pachaiyappa’s College, Chennai.

Experience 💼

With 16 years of experience, Dr. Gunasekar has held various academic and administrative positions at esteemed institutions. At Vel Tech University, he serves as a professor, NCC Officer, and Head of Student Welfare. He has been an Associate Professor and Associate NCC Officer at VIT University, Vellore, and has worked at institutions like Kalaignar Karunanidhi Institute of Technology and Arignar Anna Institute of Science and Technology. Dr. Gunasekar is also an active member in university committees and has organized several national and international faculty development programs.

Research Interests 🔬

Differential Equations: Emphasizing functional differential equations, impulsive, stochastic, and fuzzy differential equations.

Control Theory: Application of mathematical techniques to dynamic systems.

Fuzzy Graph Theory: Exploring the application of fuzzy logic to graph theory, including fuzzy graphs and their practical implications.

Cryptography: Applying mathematical models to secure communication.

Mathematical Modeling: Constructing models for real-world applications using mathematical concepts. He is deeply engaged in using fuzzy logic and stochastic methods to solve complex mathematical problems, with a focus on practical applications.

Awards 🏆

Faculty Excellence in Research and Publication Award (SNS Faculty Excellence Award 2024).

Best Teacher Award for multiple academic years, highlighting his exceptional teaching and commitment to student success.

Research Award at VIT University, underscoring his impactful research contributions.

Best Faculty Award for the academic years 2018-2019 and 2019-2020, acknowledging his excellence in both teaching and research.

Best Social Worker Award (2022-2023) from the Nature Science Foundation for his active involvement in social initiatives and community engagement.

Publications Top Notes 📚

HB Tharmalingam Gunasekar,"Application of Laplace Transform to Solve Fractional Integrodifferential Equations", Journal of Mathematics and Computer Science, 33(3), 2024, pp. 225-237.

T. Gunasekar,  "The Mohand Transform Approach to Fractional Integro-Differential Equations", Journal of Computational Analysis and Applications, 33(1), 2024, pp. 358-371.

T. Gunasekar,  "Symmetry Analyses of Epidemiological Model for Monkeypox Virus with Atangana–Baleanu Fractional Derivative"
Symmetry, 15(8), 2023, Article 1605.

FP Samuel, T. Gunasekar, "Controllability Results for Second Order Impulsive Neutral Functional Integrodifferential Inclusions with Infinite Delay", Italian Journal of Pure and Applied Mathematics, 31, 2013, pp. 319-332.

R. Prabakaran, T. Gunasekar, "Advancing Cryptographic Security with Kushare Transform Integration", 2024.

 

 

 

Prof. Wen Jiang | Artificial Intelligence | Best Researcher Award

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Prof. Wen Jiang | Artificial Intelligence | Best Researcher Award

Northwestern Polytechnical University, China.

Prof. Wen Jiang is a distinguished researcher and academic with a Ph.D. from Northwestern Polytechnical University, Xi’an, China (2009). She currently serves as a professor in the School of Electronics and Information at Northwestern Polytechnical University. Her work focuses on cutting-edge areas like information fusion, artificial intelligence, remote sensing image processing, and intelligent algorithm security, making her a leader in her field.

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Education 🎓

Prof. Wen Jiang has an impressive academic background in information systems and engineering. She earned her Ph.D. in Information Systems from Northwestern Polytechnical University, Xi’an, China, in 2009, where her research focused on innovative data systems and intelligent technologies. Prior to that, she completed her Master’s degree in Information Engineering at Information Engineering University, Zhengzhou, China, in 1997, gaining in-depth knowledge of advanced engineering concepts. She began her academic journey with a Bachelor’s degree in Information Engineering from the same university in 1994, building a strong foundation for her pioneering contributions to the field.

Experience 🏫

Prof. Wen Jiang is a Professor at the School of Electronics and Information, Northwestern Polytechnical University, where she has made a significant impact in academia. She is highly regarded for mentoring aspiring researchers and leading innovative projects in advanced technologies. Her leadership and expertise have been instrumental in driving forward research in areas like artificial intelligence, information fusion, and algorithm security..

Research Interests 🔍

Information Fusion:
Integrating data from diverse sources to enable smarter and more efficient decision-making processes, crucial for applications in defense, healthcare, and industry.

Artificial Intelligence:
Advancing machine learning and intelligent systems to solve complex problems and enhance automation across various domains.

Remote Sensing Image Processing:
Developing cutting-edge tools for environmental monitoring, urban planning, disaster management, and mapping applications.

Intelligent Algorithm Security:
Ensuring the robustness, reliability, and safety of AI-driven solutions to address vulnerabilities in critical systems.

Publications Top Notes 📚

A New Data Augmentation Method Based on Mixup and Dempster-Shafer Theory IEEE Transactions on Multimedia, 2024
Contributors: Zhuo Zhang, Hongfei Wang, Jie Geng, Xinyang Deng, Wen Jiang. Link

A Novel Air Target Intention Recognition Method Based on Sample Reweighting and Attention-Bi-GRU IEEE Systems Journal, 2024
Contributors: Yu Zhang, Weichen Ma, Fanghui Huang, Xinyang Deng, Wen Jiang. Link

Causal Intervention and Parameter-Free Reasoning for Few-Shot SAR Target Recognition IEEE Transactions on Circuits and Systems for Video Technology, 2024, Contributors: Jie Geng, Weichen Ma, Wen Jiang. Link

CMSE: Cross-Modal Semantic Enhancement Network for Classification of Hyperspectral and LiDAR Data IEEE Transactions on Geoscience and Remote Sensing, 2024, Contributors: Wenqi Han, Wang Miao, Jie Geng, Wen Jiang. Link

Dual-Path Feature Aware Network for Remote Sensing Image Semantic Segmentation IEEE Transactions on Circuits and Systems for Video Technology, 2024, Contributors: Jie Geng, Shuai Song, Wen Jiang. Link

 

 

 

Subhrangshu Das | Bioinformatics | Best Researcher Award

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🌟Mr. Subhrangshu Das, Bioinformatics, Best Researcher Award🏆

Subhrangshu Das at CSIR-Indian Institute of Chemical Biology, India

Subhrangshu Das is a highly qualified individual with a diverse academic background and extensive experience in both computer science and structural biology/bioinformatics. He holds a B.Tech. in Computer Science & Engineering, an M.E. in Computer Science & Engineering, and is on the verge of completing his Ph.D. in Structural Biology and Bioinformatics. Throughout his career, Das has demonstrated a keen interest in interdisciplinary research, utilizing his expertise in computer science to contribute to the field of biology.

Author Metrics:

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Das has an impressive publication record, with several articles published in reputable scientific journals. His research contributions span topics such as Alzheimer’s disease detection, protein-protein interaction interface prediction, and sub-cellular organelle analysis. He has also presented his work at conferences and workshops, further showcasing his expertise and involvement in the scientific community.

Citations: 115 citations by 110 documents.

Documents: 9 documents authored.

h-index: 6. The h-index is a metric that attempts to measure both the productivity and citation impact of the publications of a scientist or scholar. An h-index of 6 means the author has at least 6 papers that have been cited at least 6 times each.

Education:

Das’s educational journey includes a Bachelor of Technology in Computer Science & Engineering, a Master of Engineering in Computer Science & Engineering, and a pending Ph.D. in Structural Biology and Bioinformatics. His academic achievements demonstrate a strong foundation in both computer science and biological sciences, providing him with a unique skill set for interdisciplinary research.

Research Focus:

Das’s research focuses on the intersection of computer science and biology, particularly in the areas of structural biology and bioinformatics. His work involves the development and application of computational algorithms and techniques for analyzing biological data, with specific emphasis on Alzheimer’s disease detection, protein-protein interaction interface prediction, and sub-cellular organelle analysis.

Professional Journey:

Das has a rich professional journey, starting as a Junior Research Fellow and progressing to the role of Senior Research Fellow before becoming a Research Associate at CSIR – Indian Institute of Chemical Biology. Throughout his career, he has been actively involved in research projects, contributing to advancements in structural biology and bioinformatics.

Honors & Awards:

Das has received several honors and awards for his academic and research achievements. Notable accolades include qualifying in GATE and CSIR NET exams, as well as receiving scholarships during his Master’s and Ph.D. studies. These recognitions underscore his dedication and excellence in both academic and research endeavors.

Publications Noted & Contributions:

Das has made significant contributions to the scientific community through his publications in reputable journals. His research on Alzheimer’s disease detection, protein-protein interaction interface prediction, and sub-cellular organelle analysis has advanced our understanding of these complex biological processes. Additionally, his presentations at conferences and workshops have disseminated valuable insights to the scientific community.

Title: CMT2A‐linked mitochondrial hyperfusion‐driving mutant MFN2 perturbs ER‐mitochondrial associations and Ca2+ homeostasis

  • Authors: R. Das, S. Das, S. Chakrabarti, O. Chakrabarti
  • Journal: Biology of the Cell
  • Volume/Issue: 114 (11)
  • Pages: 309-319
  • Year: 2022
  • Citations: 4

Title: Three Dimensional Face Registration by Pose Orientation and Recognition using PCA

  • Author: S. Das
  • Year: 2014
  • Citations: 1
  • Title: CCADD: An Online Webserver for Alzheimer’s Disease Detection from Brain MRI
  • Authors: P. Panigrahi, S. Das, S. Chakrabarti
  • Journal: Computers in Biology and Medicine
  • Article Number: 108622
  • Year: 2024

Title: SARS-CoV-2: From Genetic Variability to Vaccine Design

  • Authors: Nupur Biswas*, Krishna Kumar, Priyanka Mallick, Subhrangshu Das, Izaz Monir Kamal, Sarpita Bose, Anindita Choudhury, Saikat Chakrabarti
  • Editors: I. Saha, W.H. Chen
  • Publisher: Springer
  • Year: 2022

Title: Structural and Drug Screening Analysis of the Non-structural Proteins of Severe Acute Respiratory Syndrome Coronavirus 2 Virus Extracted From Indian Coronavirus Disease 2019

  • Authors: N. Biswas, K. Kumar, P. Mallick, S. Das, I.M. Kamal, S. Bose, A. Choudhury, …
  • Journal: Frontiers in Genetics
  • Article Number: 171

Research Timeline:

Das’s research timeline spans his academic journey from his Bachelor’s degree to his current role as a Ph.D. candidate. Throughout this timeline, he has been actively engaged in research projects, focusing on various aspects of structural biology and bioinformatics. His progression from a Junior Research Fellow to a Research Associate reflects his growth and expertise in the field.

Collaborations and Projects:

Das has been involved in numerous research projects, collaborating with fellow scientists and researchers to address key challenges in structural biology and bioinformatics. His projects have encompassed diverse topics such as Alzheimer’s disease detection, stroke quantification, protein-protein interaction interface prediction, and sub-cellular organelle analysis. Through these collaborations, Das has contributed to interdisciplinary research efforts and fostered innovation in the field.