Srinivaas Ashok Kumar

About

ML/AI architect with a Ph.D. in Mechanical Engineering and 10+ years of experience across IT, academia and automotive R&D, specializing in machine-learning and deep-learning architecture (classical ML, CNN, DNN, transformers) with transfer, federated and federated transfer learning for time-series and multi-sensor data. Strong background in automotive and intelligent systems (IC engines, ADAS/SDV) and practical expertise in Python, TensorFlow/PyTorch, scikit-learn and MATLAB, supported by 21+ peer-reviewed publications and extensive project and mentoring experience. Actively bridges industry–academia collaboration and university–corporate partnerships to deliver socially impactful, technology-driven solutions.

Employment

• Amrita Vishwa Vidyapeetham Assistant Professor
  2013 - Present
• Cognizant (India) Trainee Engineer
  2012 - 2013

Education

• Amrita Vishwa Vidyapeetham Doctor of Philosophy(PhD)
  2021 - 2026
• Madras Institute of Technology Master of Engineering in Automobile Engineering
  2010 - 2012
• KLN College of Engineering Bachelor of Engineering in Mechanical Engineering
  2006 - 2010

Projects & Funding

Projects & funding information is unavailable.

Publications (21)

• Experimental and data-driven investigation of dry sliding wear behaviour in Al 6061–graphite composites
  Canadian Metallurgical Quarterly 2026 DOI: 10.1080/00084433.2026.2662795
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• Analysis of Regenerative Braking for Electric Vehicle with Rear-Wheel Drive
  2026 DOI: 10.1007/978-981-96-9374-0_46
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• LLM-guided expert feature extraction with fusion-based complementary learning network for fish freshness classification using eye images
  Scientific Reports 2026 DOI: 10.1038/s41598-026-55139-y
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• Real-Time Road Surface Classification Using MobileNetV2 and Vision Transformers: A Smartphone-Based Edge AI Framework
  2025 DOI: 10.1109/STPEC66316.2025.11490898
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• Cross domain fault diagnosis in internal combustion engines using multisensor data with transfer federated and transformer based federated transfer learning
  Scientific Reports 2025 DOI: 10.1038/s41598-025-20692-5
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• A Review on Hybrid Vehicle Technologies and Strategies
  Journal of Environmental Nanotechnology 2025 DOI: 10.13074/jent.2025.06.2441142
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• Machine Learning Approaches for Fault Detection in Internal Combustion Engines: A Review and Experimental Investigation
  Informatics 2025 DOI: 10.3390/informatics12010025
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• Adaptive Navigation in Collaborative Robots: A Reinforcement Learning and Sensor Fusion Approach
  Applied System Innovation 2025 DOI: 10.3390/asi8010009
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• Simulation Study on the Influence of the Traffic Conditions on Vehicle Performance and Emission
  Journal of Environmental Nanotechnology 2024 DOI: 10.13074/jent.2024.06.241527
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• Advancements and Applications of LiDAR Technology in the Modern World: A Comprehensive Review
  2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) 2023 DOI: 10.1109/iceccme57830.2023.10252481
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