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Ph.D. positions available in the area of Robotics, Control, and Deep and Reinforcement learning , and energy storage.
Avimanyu Sahoo
Assistant ProfessorDepartment of Electrical and Computer EngineeringUniversity of Alabama in Huntsville
Welcome to ACCL!
Welcome to ACCL!
Our group focuses on research at the convergence of control theory and artificial intelligence and their applications in robotics, energy storage, and fault diagnostics and prognostics. We aim to develop resource-aware control, computationally efficient real-time learning, and smart battery management systems for health-conscious decision-making.
Control of Cyber-Physical Systems: With the recent development of spatially distributed systems, the spatiotemporal behavior, significant communication requirements, inevitable network constraints, and exposure to vulnerabilities (privacy and security) added another layer of complexity to developing control algorithms. Autonomous systems connected over communication networks must learn uncertain dynamics and environments, detect impending failure or attacks, swiftly isolate the compromised component, modify control, and resume stable operation.
Artificial Intelligence (AI) for Control: AI is a broad area of research. Real-time learning for control is notoriously challenging. The resource constraints of the edge devices, lack of dependable, high-confidence, or provable behaviors, safety, security, and verification in human-in- or human-on-the-loop systems make it more difficult to implement.
ACCL Research on Fox54 News
Upcoming Events/News
Upcoming Events/News
Cyber-Physical Systems and its chalenges
Application Areas
Lithium-ion batteries are the workhorse of electric vehicles. A battery management system is required for their safe operation, power, energy, and thermal management. Some of the primary challenges in battery management systems research are accurate state of health estimation, real-time learning of battery models, internal faults detection, and vulnerability to thermal runaway.
Electric Machinery Health Management is critical to avoid unprecedented downtime and cost. Our goal is to embed machines with advanced and intelligent fault diagnostics and prognostics algorithms to self-detect faults and predict remaining life.
Intelligent Battery Management Systems
Control
Control
Autonomous cognition for inference and filtering
Security and privacy of learning-based controllers
Resource-aware optimal control
Artificial Intelligence
Artificial Intelligence
Real-time learning for control
Event-based reinforcement learning
Deep learning for visual inspection
Safe deep reinforcement learning for navigation and path planning
Energy Storage
Energy Storage
Lithium-ion cell/pack modeling
Smart battery management systems
Fault detection of Li-ion cells
Health-conscious fast charging
Recent Highlights
Recent Highlights
July 2024: Our research group received funding from the National Science Foundation (NSF) for collaborative research on Vulnerability Characterization of Learning-Based Controllers in Networked Cyber-Physical Systems
July 2024: Sazzad presented his paper on multi-label defect classification using graph neural networks in IEEE WCCI on July 06, 2024.
Apr 2024: News article on our research
Oct 2023: Dr. Sahoo is invited to serve as a panelist in the National Science Foundation proposal review.
Sep 2023: Dr. Sahoo presented his student Geetika's research on "Embedding Self-learning Capability in Electric Vehicle Battery Management Systems for Health-Conscious Decision Making" at the International Mechatronics Conference at Oklahoma City, OK
Sep 2023: Sazzad presented his research on Graph Neural Networks for Defect Classification at the International Mechatronics Conference in Oklahoma City, OK
Sep 2023: Dr. Sahoo is invited to join as an Associate Editor at the IEEE Transaction on Neural Network and Learning Systems (TNNLS).
Aug 2023: Sophia Lopez (UG Research Assistant) joined our research group. Welcome to ACCL, Sophia!
Aug 2023: Tiffany Lodge (Ph.D. Student) joined our research group. Welcome to ACCL, Tiffany!
Aug 2023: Jessica Hamer (M.S. Student) joined our research group. Welcome to ACCL, Jessica!
Aug 2023: Mahtab Noor Shan (M.S. Student) joined our research group. Welcome to ACCL and UAH Mahtab!
Aug 2023: Saima Alam (Ph.D. Student) joined our research group. Welcome to ACCL and UAH, Saima!
Aug 2023: Presented our research results on "Core Temperature Estimation of Lithium-ion Batteries Under Internal Thermal Faults Using Neural Networks" at CCTA, Bridgetown, Barbados, 2023.
Jun. 2023: Our research group received funding from the National Science Foundation (NSF) for a collaborative REU Site on "Smart Personal Protective Equipment."
Jun. 2023: Our research group received funding from the Naval Surface Warfare Center (NSWC), DOD, for the project "Towards Autonomy in Uncertain Environments: Exploring Vistas Beyond Consensus."
May 2023: Our paper on "Learning-based Faulty State Estimation Using SOH-coupled Model Under Internal Thermal Faults in Lithium-ion Batteries " is accepted for publication in IEEE Transactions on Transportation Electrification, doi: 10.1109/TTE.2023.3278305 .
May 2023: Our paper on "Core Temperature Estimation of Lithium-ion Batteries Under Internal Thermal Faults Using Neural Networks" is accepted for presentation at CCTA2023.
Feb. 2023: Our research group received funding from the Department of Energy (DOE) for the project "AI-enabled Autonomy of Robotic Inspection Platforms for Sustainability of Energy Infrastructure."
Jan 2023: Md. Sazzad Hossen (Ph.D. Student) joined ACCL in the spring 2023. Welcome to ACCL and UAH!
Jan. 2023: Our research group received funding from the Oklahoma Center for Advancement of Science and Technology (OCAST) to develop "Meta and Multimodal Learning for Smart Visual Borescope Inspection" for the second year.
Nov. 2022: Contratulations Geetika Vennam, on defending her Ph.D. Dissertation. She will join Idaho National Laboratory as a Post Doctoral Fellow.
Oct. 2022: Our article “A dynamic SOH-coupled lithium-ion cell model for state and parameter estimation” is accepted for publication in IEEE Transactions on Energy Conversion.
Aug. 2022: Our survey article "A survey on lithium-ion battery internal and external degradation modeling and state of health estimation" is accepted for publication in the Journal of Energy Storage.
Dec. 2021: Our research group received funding from the Oklahoma Center for Advancement of Science and Technology (OCAST) to develop "Meta and Multimodal Learning for Smart Visual Borescope Inspection."
Aug. 2021: Our research group received funding from the Transportation Consortium of South-Central States (TranSET) for the US DOT to develop "Intelligent Incipient Fault Detection System for Electric Vehicle Battery."
Aug. 2020: Our research group received funding from the Transportation Consortium of South-Central States (TranSET) for the US DOT to develop "Smart Battery Management Systems for Electric Vehicles."
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