Subhodeep Moitra | Artificial Intelligence | Young Researcher Award

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Mr. Subhodeep Moitra | Artificial Intelligence | Young Researcher Award

Techno College Hooghly | India

Subhodeep Moitra is a computer science researcher focused on advancing artificial intelligence through the fusion of human-like visual perception and cognition. His academic foundation spans computer applications at both undergraduate and postgraduate levels, where he built strong expertise in machine learning, deep learning, computer vision, neural networks, adversarial robustness, and cognitive modeling. His research explores self-supervised reconstruction, adversarial recovery, AGI-oriented theoretical computing, medical prediction systems, and environmental forecasting, with publications in journals, conferences, preprint platforms, and book chapters. He has contributed to projects ranging from temperature forecasting and brain-stroke detection to adversarially robust autoencoders and AGI theory. His professional experience includes serving as a visiting faculty member, teaching programming, mentoring research projects, and engaging in active collaborative work. His technical skills extend across Python, deep learning frameworks, MERN stack development, and cloud-based AI tools, supported by multiple certifications from NASA, NVIDIA, CERN, IBM, Oracle, and Coursera. He has presented papers at international conferences and earned best paper presentation awards for his contributions in machine learning–driven forecasting and adversarial perception. His long-term research interest lies in building unified AI systems capable of perceiving, reasoning, and adapting with human-inspired intelligence, aiming to push the boundaries of next-generation cognitive AI.

Profile: Google Scholar

Featured Publications

Moitra, S., & Banerjee, D. (n.d.). Robustness as Latent Symmetry: A Theoretical Framework for Semantic Recovery in Deep Learning. OSF.

Moitra, S., & Banerjee, D. (n.d.). Are We Even on the Right Track? A Theoretical Framework for AGI Beyond Classical Computation. Authorea Preprints.

Moitra, S., & Banerjee, D. (n.d.). Skip the Chaos: A Self-Supervised Learning-Powered Autoencoder for Adversarial Recovery. OSF.

Pintu, P., Subhodeep, M., & Deblina, B. (n.d.). The mystery of Neural Network: Linked with quantum mechanics and universe. ResearchGate.

Pal, P., Moitra, S., & Banerjee, D. (n.d.). The mystery of Neural Network: Linked with quantum mechanics and universe.

Vaijayanthimala Jayavel | Artificial Intelligence | Best Researcher Award

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Dr. Vaijayanthimala Jayavel | Artificial Intelligence | Best Researcher Award

Dhirajlal Gandhi College of Technology| India

Dr. J. Vaijayanthimala is a dynamic academic and researcher recognized for her extensive contributions in computer science and engineering, particularly in artificial intelligence, image processing, sensor networks, and intelligent computing systems. Her Google Scholar profile records 16 total citations with an h-index of 2 and i10-index of 0, reflecting her growing scholarly influence across interdisciplinary domains. She has published widely in reputed journals including the ECS Journal of Solid State Science and Technology and Journal of The Electrochemical Society, with research spanning photonic biosensors, AI-based news aggregation, virtual reality accessibility, and smart agriculture. She has co-authored and authored multiple technical books on AI, machine learning, database systems, and data structures, demonstrating her commitment to quality education and knowledge dissemination. Her innovations include patents in automated voice recognition and eco-friendly 3D printing technology. A recipient of the “Innovative Technologist and Dedicated Teaching Professional Award,” she actively contributes as a reviewer for Springer Nature and Elsevier journals. With research interests that merge intelligence, automation, and sustainable technology, Dr. Vaijayanthimala continues to advance computational research and inspire the next generation of scholars.

Profile: Google Scholar

Featured Publications

Vaijayanthimala, J., Pon Bharathi, A., Ramkumar Raja, M., & Arun Kumar, U. (2024). Enhanced sensing of diseased blood samples through one-dimensional MgO-SiO2 photonic crystal sensor. Journal of The Electrochemical Society, 171(10), 107505.

V.M. Manish, J. Vaijayanthimala. (2014). Diminution of packet drop by efficient selection of network route in MANET. International Journal of Computer Science Information Technology (IJCSIT), 5, 1852–1855.

Vaijayanthimala, J., Vaishnavi, K., & Arun Kumar, U. (2025). High-sensitivity terahertz metasensor for cervical cancer diagnosis: Graphene modulation and XGBoost-assisted optimization. Sensors International, 2666–3511, Article 2666.

Vaijayanthimala, J., Alam, M.K., Shqaidef, A., & Mahmoud, O. (2024). Performance evaluation of refractive index biosensor in THz regime for clinical applications: A simulation approach. ECS Journal of Solid State Science and Technology, 13(10), 107005.

Vaijayanthimala, J., & Padma, T. (2019). Synthesis score level fusion based multifarious classifier for multi-biometrics applications. Journal of Medical Imaging and Health Informatics, 9(8), 1673–1680.

BADDAM ANIL KUMAR | Artificial Intelligence | Research Innovation Award

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Dr. BADDAM ANIL KUMAR | Artificial Intelligence | Research Innovation Award

VIT-AP UNIVERSITY, ANDHRA PRADESH- India

Author Profile

Early Academic Pursuits

Mr. B. Anil Kumar began his academic journey with a Bachelor’s degree in Electronics and Communications Engineering from JNTU College of Engineering, Hyderabad, Telangana. This foundational education provided him with the necessary skills and knowledge in electronics and communication systems, laying the groundwork for his future pursuits in advanced studies.

Professional Endeavors

Building on his undergraduate education, Mr. Anil Kumar pursued and successfully completed a Master’s degree in VLSI System Design from Aurora College of Engineering, JNTUH, Hyderabad, Telangana. This specialization equipped him with expertise in Very Large Scale Integration (VLSI) technologies, enhancing his proficiency in designing complex integrated circuits and systems.

Currently, Mr. Anil Kumar is engaged in pursuing a Ph.D. in the School of Electronics Engineering (SENSE) at VIT-AP University in Amaravati, AP, India. His doctoral research focuses on the intersection of Image Processing, Machine Learning, and Deep Learning, reflecting his commitment to advancing the field of electronics and computational intelligence.

Contributions and Research Focus

Mr. Anil Kumar’s research interests primarily revolve around Image Processing, Machine Learning, and Deep Learning. These areas represent critical domains within the broader spectrum of artificial intelligence and computational intelligence, aimed at developing algorithms and systems that can analyze, interpret, and extract meaningful information from digital images. His contributions in these fields are expected to contribute significantly to applications ranging from healthcare diagnostics to industrial automation and beyond.

Accolades and Recognition

Mr. Anil Kumar has garnered recognition for his scholarly contributions and expertise in electronics and computational intelligence. His role as a reviewer for well-known reputed journals underscores his standing within the academic community, where his insights and evaluations help shape the discourse and quality of research publications.

Impact and Influence

Through his academic pursuits and professional endeavors, Mr. Anil Kumar has already begun to make a notable impact on the fields of electronics engineering and computational intelligence. His research outputs and contributions are anticipated to influence the development of advanced technologies and methodologies in image processing and machine learning, thereby shaping future innovations in these domains.

Legacy and Future Contributions

Looking ahead, Mr. Anil Kumar’s legacy is poised to encompass significant advancements in image processing and machine learning technologies. His future contributions are expected to extend beyond academic research to practical applications, potentially impacting various industries and sectors. By continuing to explore new avenues in computational intelligence and fostering interdisciplinary collaborations, Mr. Anil Kumar aims to leave a lasting imprint on the field, advancing both theoretical knowledge and practical implementations in electronics engineering.

Citations

A total of 32 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations         32
  • h-index           2
  • i10-index        1

Notable Publications 

Implementation of 64-Bits Radix – 8 IFFT for Computation Speed by IDIF using Verilog

B.Anil Kumar, M. Naveen Reddy, Vamshi Kollipara, B. Rajesh,International Journal of Recent Technology and Engineering (IJRTE)

Caffe-MobileNetV2 based Tomato Leaf Disease Detection

B.Anil Kumar, Mohan Bansal, Rajeev Sharma
2023 3rd International conference on Artificial Intelligence and Signal …

Hardware Implementation of 64-Bits Data by Radix-8 FFT/IFFT for High Speed Applications

B.Anil Kumar, Mohan Bansal
2022 8th International Conference on Signal Processing and Communication …