Surya Prakash Mishra | Robotics | Research Excellence Award

Published-on by Indian Scientist

Mr. Surya Prakash Mishra | Robotics | Research Excellence Award

National Institute of Technology, Rourkela | India

Surya Prakash Mishra is a motivated mechanical engineering researcher with strong expertise in intelligent robotic systems, mechanical design, and control engineering. Currently pursuing advanced doctoral research at a premier national institute, he holds a postgraduate specialization in Machine Design and Analysis and a foundational degree in Mechanical Engineering. His academic and research journey reflects a blend of theoretical depth and practical competence in robotics, CAD/CAE, optimization algorithms, and control strategies. His research work focuses on autonomous and intelligent robotic platforms, particularly autonomous underwater vehicles, integrating hybrid PID control with metaheuristic optimization techniques such as nature-inspired algorithms. He has also contributed to advanced mechanical system design, including high-load bearing systems, sustainable engineering solutions like refuse-derived fuel from municipal waste, and multiple CAD-driven design projects. With extensive experience as a CAD engineer, product design engineer, technical trainer, faculty member, and project consultant, he has actively contributed to industry-oriented training and academic mentoring. His technical proficiency spans robotics simulation, mechanical analysis, CNC manufacturing, and reverse engineering. Recognized for academic excellence, innovation activities, and competitive achievements, his work reflects interdisciplinary thinking and problem-solving ability. Overall, his profile represents a committed researcher and educator dedicated to advancing intelligent systems, sustainable engineering solutions, and next-generation mechanical and robotic technologies.

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Featured Publication

Mishra, S. P., Parhi, D. R., & Sahoo, A. K. (2025). Integration of white shark algorithm with PID in U-ROV navigation for enhanced obstacle avoidance. Ocean Engineering. Advance online publication. https://doi.org/10.1016/j.oceaneng.2025.122501

Priyanka Upadhyay | Robust Navigation | Best Researcher Award

Published-on by Indian Scientist

Ms. Priyanka Upadhyay | Robust Navigation | Best Researcher Award

Netaji Subhas University of Technology | India

Priyanka Upadhyay is a researcher in Electrical Engineering with growing contributions in autonomous robotics, intelligent navigation, and control systems. She is pursuing a doctoral degree focused on robust navigation of autonomous robots and holds postgraduate and undergraduate qualifications in Electrical Power Systems and Electrical & Electronics Engineering. Her research record includes publications on hybrid path-planning algorithms, enhanced Bezier-based trajectory modeling, autonomous mobile robot navigation, and control strategies for multi-link manipulators. Her work has gained academic attention, reflected in 16 citations, an h-index of 2, and i10-index of 0, demonstrating steadily increasing scholarly visibility with 8 citations since 2020. She has prior teaching experience as a faculty member in Electrical Engineering and has participated in several conferences, faculty development programs, and short-term courses related to artificial intelligence, optimization, robotics, renewable integration, and power electronics. Her technical expertise is strengthened by hands-on training in tools such as MATLAB and experience in industrial settings. She has earned recognition including a Silver Medal for an NPTEL Robotics certification and reviewer certification from an international robotics journal. Her research interests include electrical machines, robotic navigation, path planning, and intelligent control. She continues to advance her academic profile with a commitment to innovation, learning, and collaborative research.

Profile: Google Scholar

Featured Publications

Upadhyay, P., Rajesh, N., Garg, N., & Singh, A. (2015). Evaluating seed germination monitoring system by application of wireless sensor networks: A survey. In Computational Intelligence in Data Mining—Volume 2: Proceedings of the … (Cited by: 3).

Upadhyay, P., Singh, A., & Garg, N. (2014). Modeling software maintainability and quality assurance in the agile environment. International Journal of Database Theory and Application, 7(3), 83–90. (Cited by: 3).

Singh, P., Upadhyay, P., & Singh, S. K. (2025). Unlocking the economic potential of potato cultivars for mini-tuber production under aeroponic culture. Potato Research, 1–24. (Cited by: 2).

Upadhyay, P., Singh, R., & Rani, A. (2023). Reliable autonomous navigation of mobile robot in unconstrained environment. In 2023 10th International Conference on Signal Processing and Integrated Networks (SPIN) (pp. 531–537). IEEE. (Cited by: 2).

Upadhyay, P., Patil, K. U., Kuber, R., Kulkarni, V., & Singh, A. (2014). Evaluation of hypoxic-ischaemic events in preterm neonates using trans cranial ultrasound. International Journal of Healthcare and Biomedical Research, 3, 67–72. (Cited by: 2).

Subhodeep Moitra | Artificial Intelligence | Young Researcher Award

Published-on by Indian Scientist

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.