Geetha Mani

About

Dr. Geetha Mani joined the School of Electrical Engineering as an Associate Professor and has over 15 years of teaching experience. She was a Gold medallist in both UG and PG. She was awarded Doctor of Philosophy for the thesis titled “Development of Knowledge-based State Estimation techniques and their application to Advanced Process Control” from Anna University, Chennai in the field of Electrical Engineering. Her area of research interest includes Advanced Process Control, Machine Learning, Soft Computing, Industrial Automation, and the Internet of Things. She completed a funded research project in 2013 sponsored by UGC major research grant, titled “Investigation on the application of state estimation in CSTR Control”. She also completed a funded research project in 2018 sponsored by VIT SEED grant, titled “Wireless Wearable ECG Prototype development with Fuzzy Inference System”. She was a recipient of IEI Young Engineers Award to recognize her contribution in the field of Electrical Engineering, 2016 from the Institution of Engineers, India. She also authored and published several research articles in peer-reviewed international journals, conferences and book chapters. She received travel grants from DST, CICS, IEEE/IFIP for presenting her research work in reputed International conferences namely 21st iFuzzy 2013, IEEE VLSI-SoC-2015, 7th ICIAS-2018 and SocProS’18. She was awarded for best paper and PhD poster presentation in 23rd VLSI SoC-2015 conference held in Daejeon, South Korea. She visited few countries like Taiwan, Daejeon and Malaysia to present her research findings and also for collaborate with other universities. She successfully guided and produced two PhD candidates. She is an active professional member in SCRS and IEEE.

Employment

• Vellore Institute of Technology University

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (57)

• Optimal PID control using Black-winged Kite Algorithm to minimize current stress in dual active bridge converters
  Engineering Research Express 2026 DOI: 10.1088/2631-8695/ae37d1
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• Harmony Search Optimization Tuned LQR Controller for Vehicle Active Suspension System
  IEEE Access 2026 DOI: 10.1109/ACCESS.2026.3674677
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• Optimization Status Sensing and Failure Detection in MPC and Virtual Feedback MPC Applied to a Tank System
  2026 DOI: 10.1007/978-3-031-99939-0_25
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• A data-driven review of lithium-ion battery performance improvement and management techniques
  Engineering Research Express 2026 DOI: 10.1088/2631-8695/ae63a7
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• A Portrayal of Sliding Mode Control Through Adaptive Neuro Fuzzy Inference System With Optimization Perspective
  IEEE Access 2024 DOI: 10.1109/ACCESS.2023.3348836
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• An extensive critique on expert system control in solar photovoltaic dominated microgrids
  IET Renewable Power Generation 2023 DOI: 10.1049/rpg2.12875
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• AI‐Based Predictive Modeling of Delamination Factor for Carbon Fiber–Reinforced Polymer (CFRP) Drilling Process
  Optimization Techniques in Engineering 2023 DOI: 10.1002/9781119906391.ch8
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• IIoT based level monitoring and pre-alarm system using ultrasonic sensor
  IV INTERNATIONAL SCIENTIFIC FORUM ON COMPUTER AND ENERGY SCIENCES (WFCES II 2022) 2023 DOI: 10.1063/5.0178094
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• Intelligent EMS For Multi-Objective Reserve And Demand Allocation Using Multi-Threaded SVR-LSTM Model
  International Journal of Computing and Digital Systems 2022 DOI: 10.12785/ijcds/110140
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• Ant Colony Optimization Tuned Closed-Loop Optimal Control Intended for Vehicle Active Suspension System
  IEEE Access 2022 DOI: 10.1109/ACCESS.2022.3164522
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