Ph. D - Ongoing

1.  Anju M (January 2021 Admission)

Topic: Stability and performance analysis of DFIG based wind energy systems

2.  Deepak V Dev (January 2021 Admission)

Topic: Robust control of Nonlinear time delay systems

3. Jyothish Sebastian (January 2022 Admission)

Topic: Adaptive Intelligent control of Nonlinear systems

4. Simi Raj (August 2023 Admission)

Topic: AI-Based Consensus Control of Multi Agent Systems

5. Shyamchand G (August 2023 Admission)

Topic: Computer Vision for food safety inspection

6. Mubaris P ( November 2023 Admission)

Topic: AI-based fault diagnostics of transformer

M.Tech - Ongoing

1. Annie Jose  (2023-2024), Topic: Intelligent control of Multi-agent systems

2. Chandresh Sharma  (2023-2024), Topic:  Adaptive Neural Control of Helicopter System

3. Divya Isaac (2023-2024), Topic: Design of hybrid predictive controller for UAV system

4. Rohit AP (2023-2024), Topic: Two-loop Predictive Control of DC-DC converter system

M.Tech - Completed

10. Albin  (2022-2023), Topic: Adaptive Neural Network Feedback Linearizable Control

9. Bharti Yadav (2022-2023), Topic:  Predictive Control of DC-DC converter system

8. Anik Mitra (2022-2023), Topic: Fault Detection using Deep Learning

7. Daisy Monica Roy (2021-2022), Topic: 3D Object detection using Deep learning

6.  Pradnya Uttamrao Moon (2021-2022), Topic: Design of model prediction controller for DFIG system

5. Priyanshu Raj (2021-2022), Topic: Intelligent Control of DC-DC converter systems

4. Kavyasree Raj S (2020-2021), Topic: Intelligent control of feedback linearizable systems

3.  Sunidhi Gupta (2020-2021), Topic: Detection of Faults using Machine Learning Techniques

2. Gopakumar K (2020-2021), Topic: Control of Distributed Multi-agent systems

1. Vennela Thamminaidu (2020-2021), Topic: Model Predictive Control of Nonliear Systems

1. Nonlinear and Intelligent control systems

2. Soft computing and hybrid system

3. Renewable energy harvesting and control

4. Machine learning and deep learning

5. Robotics

6. Microgrid control

• Gold medal Award for top rank holder,Department of Electrical Engineering, National Institute of Technology, Calicut
• Best paper award for system conference NSC-2015

• Best paper award for IEEE 6th ICCCA 2021.

International Journals (SCI)

• Jyothis Sebastian and K. V. Shihabudheen. "Adaptive control of a nonaffine nonlinear system using self-organising kernel extreme learning machine." ISA Transactions, 2023, https://doi.org/10.1016/j.isatra.2023.12.025.
• Shihabudheen, K. V., & Gupta, S. "Detection of High Impedance Faults in Power Lines using Empirical Mode Decomposition with Intelligent Classification Techniques." Computers and Electrical Engineering, vol. 109, pp. 108770, 2023, https://doi.org/10.1016/j.compeleceng.2023.108770
• J. B. Thomas, S. G. Chaudhari, Shihabudheen K. V. and N. K. Verma, "CNN-Based Transformer Model for Fault Detection in Power System Networks," IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-10, 2023, Art no. 2504210, doi: 10.1109/TIM.2023.3238059
• J. B. Thomas and Shihabudheen K.V., “Neural architecture search algorithm to optimize deep Transformer model for fault detection in electrical power distribution systems,” Engineering Applications of Artificial Intelligence, vol. 120, p. 105890, 2023, doi: https://doi.org/10.1016/j.engappai.2023.105890.
• J. B. Thomas, Shihabudheen K. V., S. M. Sulthan, and A. Al-Jumaily, “Deep Feature Meta-Learners Ensemble Models for COVID-19 CT Scan Classification,” Electronics, vol. 12, no. 3, 2023, doi: 10.3390/electronics12030684.
• S. M. Sulaiman, P. A. Jeyanthy, D. Devaraj, and K. V Shihabudheen, “A novel hybrid short-term electricity forecasting technique for residential loads using Empirical Mode Decomposition and Extreme Learning Machines,” Comput. Electr. Eng., vol. 98, p. 107663, 2022, doi: https://doi.org/10.1016/j.compeleceng.2021.107663.
• B. Peethambaran, R. Anbalagan, D.P. Kanungo, A. Goswami, K.V. Shihabudheen,"A comparative evaluation of supervised machine learning algorithms for township level landslide susceptibility zonation in parts of Indian Himalayas,” CATENA, vol. 195, pp. 104751, 2020.
• B. Peethambaran, R. Anbalagan, and K. V. Shihabudheen. "Landslide susceptibility mapping in and around Mussoorie Township using fuzzy set procedure, MamLand and improved fuzzy expert system-A comparative study." Natural Hazards, vol. 96, no. 1 ,pp. 121-147, 2019.
• B. Peethambaran, R. Anbalagan, K. V. Shihabudheen, and A. Goswami. "Robustness evaluation of fuzzy expert system and extreme learning machine for geographic information system-based landslide susceptibility zonation: A case study from Indian Himalaya." Environmental Earth Sciences, 78, no. 6, pp. 231, 2019
• K.V. Shihabudheen and G.N. Pillai, “Recent advances in Neuro-fuzzy system: A survey,” Knowledge-Based Systems, vol-152, pp.136-162, 2018
• K.V. Shihabudheen, M. Mahesh and G.N. Pillai, “Particle swarm optimization based extreme learning neuro-fuzzy system for regression and classification,”Expert Systems with Applications, vol. 92, pp. 474-484, 2018. 
• Shihabudheen, K. V., G. N. Pillai, and S. KrishnamaRaju. "Neuro-Fuzzy Control of DFIG Wind Energy System with Distribution Network." Electric Power Components and Systems, vol. 46, no. 13, pp. 1416-1431,2018 
• K.V. Shihabudheen, S. K. Raju and G. N. Pillai, “Control for Grid connected DFIG based wind energy system using adaptive neuro-fuzzy technique,”International Transactions on Electrical Energy Systems, vol.28, no.5, pp. e2526, 2018
• K.V. Shihabudheen and G.N. Pillai, “Regularized extreme learning adaptive neuro-fuzzy algorithm for regression and classification,”Knowledge-Based Systems, vol. 127, pp. 100-113, 2017. 
• K.V. Shihabudheen, G.N. Pillai and B. Peethambaran, “Prediction of landslide displacement with controlling factors using extreme learning adaptive neuro-fuzzy inference system (ELANFIS),”Applied Soft Computing, vol. 61, pp. 892-904, 2017. 
• K.V. Shihabudheen and B. Peethambaran, “Landslide displacement prediction technique using improved neuro-fuzzy system,” Arabian Journal of Geosciences, vol.10, pp. 502, 2017.

Book Chapter

• Shihabudheen, K. V., and S. M Sheik. "Review and Analysis of Machine Learning Based Techniques for Load Forecasting in Smart Grid System." In Hybrid Intelligent Approaches for Smart Energy: Practical Applications, pp. 1-26, Wiley Online, 2022 
• S. M. Sheik, and K. V. Shihabudheen. "Performance analysis of a DC stand-alone microgrid with an efficient energy management system." In Residential Microgrids and Rural Electrifications, pp. 233-253. Academic Press, 2022.

International Conferences

• V.Dev. Deepak, N.K. Arun, K.V. Shihabudheen,"Time-delay systems: Recent trends and advancements",IFAC-PapersOnLine, vol. 55,no.1, Pages 290-297, 2022.
• Shihabudheen, K.V., "Detection of High Impedance Fault Using Advanced ELM-based Neuro-fuzzy Inference System." In: Suhag, S., Mahanta, C., Mishra, S. (eds) Control and Measurement Applications for Smart Grid. Lecture Notes in Electrical Engineering, vol 822. Springer, Singapore, 2022
• A. M, Shihabudheen. K. V and M. S. J, "LVRT Capability Enhancement of DFIG with FACT Device and Superconducting Technology," 2022 IEEE 19th India Council International Conference (INDICON), Kochi, India, 2022, pp. 1-7
• D. M. Roy, Shihabudheen K. V., S. Singh and A. Navada, "Deep Learning Based 3D Object Detection with Time-of-Flight," 2022 International Conference on Emerging Techniques in Computational Intelligence (ICETCI), Hyderabad, India, 2022, pp. 13-20
• P. U. Moon and Shihabudheen K. V, "Laguerre Function based Model Predictive Control Strategy for Feedback Linearizable Doubly Fed Induction Generator System," 2022 IEEE IAS Global Conference on Emerging Technologies (GlobConET), Arad, Romania, 2022, pp. 680-686
• Manjunath, V., Shihabudheen, K.V, "Comparative Study of Abalone Age Prediction Using Classical Machine Learning Algorithms and Extreme Learning Machine". In: Gandhi, T.K., Konar, D., Sen, B., Sharma, K. (eds) Advanced Computational Paradigms and Hybrid Intelligent Computing . Advances in Intelligent Systems and Computing, vol 1373. Springer, Singapore, 2022
• V. Thamminaidu and Shihabudheen K V, "Model Predictive Control (MPC) of System Identified Continuous Stirred Tank Reactor (CSTR) with Constraints," 2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA), Arad, Romania, 2021, pp. 195-201,
• S. Gupta, Shihabudheen. K. V, A. M and B. Kunju, "Intelligent Detection of High Impedance Fault using Extreme Learning Machine," 2021 13th IEEE PES Asia Pacific Power & Energy Engineering Conference (APPEEC), Thiruvananthapuram, India, 2021, pp. 1-6
• J. B. Thomas, M. Devvarma and K. V. Shihabudheen, "Deep Ensemble Approaches for Classification of COVID-19 in Chest X-Ray Images," 2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT), Zallaq, Bahrain, 2021, pp. 463-468
• K. Gopakumar and K. V. Shihabudheen, "Leader Follower Distributed Consensus Control of Heterogeneous Multi-agent System with Model Predictive Control," 2021 International Symposium of Asian Control Association on Intelligent Robotics and Industrial Automation (IRIA), Goa, India, 2021, pp. 25-30
• K. R. S and K. V. Shihabudheen, "Gradient based Optimal State Feedback Control design for Feedback Linearizable Nonlinear Nonaffine system," 2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies, Shillong, Meghalaya, India, 2021, pp. 1-6
• R. Roshin and K. V. Shihabudheen, "Tip Point Control Of A Flexible Beam Using Robust Mu Synthesis Controller," 2020 International Conference on Futuristic Technologies in Control Systems & Renewable Energy (ICFCR), India, 2020, pp. 1-6
• O. Babu P., C. C. Sobin, K. V. Shihabudheen and J. Ali, "An Investigation on IoT-based Applications and Experimental Analysis of Biomedical Data," 2020 International Conference on Futuristic Technologies in Control Systems & Renewable Energy (ICFCR), India, 2020, pp. 1-6, 
• Sheik Mohammed, KV Shihabudheen, et all " Simulation and Analysis of Solar Powered Induction Motor Drive with V/f Control for Electric Vehicle Applications" Journal of Physics: Conference Series, Volume-1355, Issue-1, Pages-012-023, 2019
• S. M. Sulaiman, P. Aruna Jeyanthy, D. Devaraj, S. S. Mohammed and K. V. Shihabudheen, "Smart Meter Data Analytics for Load Prediction using Extreme Learning Machines and Artificial Neural Networks," 2019 IEEE International Conference on Clean Energy and Energy Efficient Electronics Circuit for Sustainable Development (INCCES), Krishnankoil, India, 2019, pp. 1-4,
• Shihabudheen KV, Bijuna Kunju, Imthias Ahammed et all, "Detection of High Impedance Fault using Machine Learning Techniques" IEEE Region 10 conference TENCON 2019, pp. 2117-2122, Kochi, Kerala, 2019
• Shiny S, Shihabudheen K V and Anish Gopinath, "Modelling of Biological Lower Extremity", IEEE International Conference on Intelligent Computing, Instrumentation & Control Technologies (ICICICT-2019),  Kerala, India, 2019
• Gowri Balachandran, Nafeesa.K, Shihabudheen KV, "Fuzzy Controller based Energy Management of Hybrid System " IEEE Sponsored 4TH International Conference for Convergence in Technology (I2CT), Mangalore, India,  2018
• K. V. Shihabudheen and G. N. Pillai, "Wind and solar irradiance prediction using improved neuro-fuzzy systems," IEEE World Congress on Computational Intelligence, Rio de Janeiro, Brazil, pp. 1-7, 2018
• G. N. Pillai and K. V. Shihabudheen,  “Wind Speed Forecasting Using Empirical Mode Decomposition and Regularized ELANFIS,” IEEE Symposium Series on Computational Intelligence (SSCI), (IEEE SSCI 2017), Hawaii, USA, pp. 1-7, 2017.
• K. V. Shihabudheen and G. N. Pillai, “Extreme Learning ANFIS Control of a Flexible Link Manipulator,” 14th IEEE India Council International Conference (INDICON), IIT Roorkee, pp. 1-6, 2017.
• Biju G. M., Shihabudheen K V and G. N. Pillai, “Chaotic Time Series Prediction Using ELANFIS,” 6th International Conference On Computer Applications in Electrical Engineering-Recent Advances (CERA), IIT Roorkee , pp. 473-478, 2017
• Shihabudheen KV, Biju G M "Performance analysis of extreme learning adaptive neuro-fuzzy inference system (ELANFIS)", IEEE 41^st National System conference, NSC-2017, Agra, Delhi, 2017 
• Shihabudheen KV, Nimmi George, Chinmaya K A, Jose Thankachan "Stability Control and Trajectory Tracking of Two Wheeled Mobile Manipulator" 12th IEEE India international conference INDICON, Delhi,pp. 1-6,  2015
• K. V. Shihabudheen and G. N. Pillai, "Internal model control based on extreme learning ANFIS for nonlinear application," IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES),NIT Calicut, 2015, pp. 1-5.
• K. V. Shihabudheen and G. N. Pillai, "Evolutionary fuzzy extreme learning machine for inverse kinematic modeling of robotic arms," 39th IEEE National Systems Conference (NSC), New Delhi, 2015, pp. 1-6. 
• Shihabudheen KV, Nimmi George, Dileep G "Applying H-infinity for Stability Control in Two Wheeled Mobile Manipulator," IEEE International Conference on Soft Computing Techniques & Implementations, Dadri, UP, India, pp. 46-51, 2015
• Shihabudheen KV, Jose Thankachan, Chinmaya K A "SDRE Control of Flexible Beam Manipulator" " IEEE International Conference on Soft Computing Techniques & Implementations, Dadri, UP, India, pp.148-154, 2015
• Roshin R, Shihabudheen K V “Mathematical Modeling of Flexible Beam- A Comparative Study” IEEE International Conference of Control Communication and Computing (ICCC), Page(s):325 - 330, Dec. 2013
• Shihabudheen KV, Jeevamma Jacob “ Composite Control of Flexible Link Flexible Joint Manipulator” IEEE International Conference INDICON, Kochi, Kerala, pp. 827- 831, 2012

• SERB sponsored High-end workshops on "Data Analytics in Electrical Energy Systems", 22nd-28th March 2023
• SERB Karyashala sponsored High-end workshop on  "Application of Computational Intelligence in Modelling and Control  " from 23rd-29th January 2023. 
• SERB-sponsored High-end workshops on "Application of Artificial Intelligence in Power System Operation & Control", 2022
• IEEE sponsored FDP "Recent advances in Intelligent System & Nonlinear Control" 2020
• Special track on “Machine Learning for Power Systems and Power Electronics" in TENCON 2019 
• TEQIP Sponsored 5 day FDP on “Electric Vehicle: Development, Integration and Challenges”, 2019