Department of Computer Science & Engineering (Emerging Technologies)
Degree
Specialization
University/Institute Name, Year
Ph.D.
Power systems
Anna University, CEG, Chennai,
2016
M.Tech.
Power Systems Engineering
Thiagarajar college of Engineering,
2005
B.Tech.
EEE
Thiagarajar college of Engineering,
2003
Diploma
Data Science
IIT Madras,
2024
Renewable energy
Machine learning
Deep Learning
Large language models
Prompt Engineering
Machine learning
Python programming
Large Language Models
Soft computing techniques
Microcontroller programming
Renewable Energy
Since July 2025 – Till Date, Associate Professor, SRM Institute of Science and Technology (SRMIST), Vadapalani Campus, Chennai
June 2024 – May 2025, Professor, Saveetha Engineering College, Chennai
June 2016 – May 2024, Associate Professor, Saveetha Engineering College, Chennai
June 2010 – June 2016, Assistant Professor (Senior Grade), Saveetha Engineering College, Chennai
June 2007 – May 2010, Lecturer, Saveetha Engineering College, Chennai
June 2005 – May 2007, Lecturer, KLN College of Engineering, Madurai
Completed Diploma in Data Science in IIT Madras, Chennai in May 2024 with CGPA 7.69
Completed Masters in Artificial intelligence course (8 months) from Inside AIML
Completed online certification course on Machine Learning Specialization with Python from IIT Rourkee
Completed a real time project on BANKING CHATBOT using NLP
University Ambassador - certified to deliver NVIDIA instructor-led workshop for
academia
Certified instructor to deliver Building AI Agents with Multimodal models
Completed Online Certification on LLM by NVIDIA, Prompt Engineering by Coursera
Completed online course on Python Core and Data science from Sololearn
Completed Ph.D in Renewable energy systems from Anna University in March 2016
Received twice a grant of Rs.3,50,000/- for conduction of FDP from AICTE-ATAL scheme - Dec 2026 & Dec 2024
Guided several projects in modelling, design and simulation of Machine Learning, IOT and Distributed generation.
Anna university recognized Supervisor – Ph.D Completed -1
21 years of Teaching experience in Core competence in all phases of engineering projects from concept and feasibility studies through to detailed design, documentation, construction and commissioning.
Gold Medalist in PG in Thiagarajar College of Engineering in 2005
Familiar with Power systems operation and control, design of machines, embedded systems and design of Microgrids and Energy storage, Machine learning, Microcontroller programming
Currently working as Professor in Saveetha Engineering College, Chennai handling Subjects like Machine learning, Deep learning, Prompt Engineering, Python programming
Patent published on “ Design of Supercapacitor” in Sep 2022
Patent granted on “ELECTRIC CYCLE”, August 2023(Design No. : 393622-001)
Patent granted on “Autonomous electric truck integrated with solar power”, Sep 2024
Patent published on “ AI-BASED COGNITIVE FUNCTION MONITORING SYSTEM FOR ENHANCING PERFORMANCE AND EARLY DETECTION OF NEUROLOGICAL DISORDERS” – January 2026
Patent Published on “Adaptivault : An Adaptive Quantum Resistant Cryptocurrency wallet with Autonomous Post Quantum Cryptographic Switching” on 8-05-2026
M. Sumithra, M. Ulagammai, K. Tamilarasi et al., “SiaCon-DetNet with HySHO: A cutting-edge transformer-based deep learning framework for emotion-aware facial recognition,” Scientific Reports, vol. 16, Art. no. 14131, 2026, doi: 10.1038/s41598-026-41890-9.
N. K. Thakre, C. V. K. Reddy, B. Lal, J. A. Alkrimi, M. Ulagammai, D. Shrivastava, and N. Sharma, “Environmental DNA metabarcoding for assessing freshwater alien species invasions in under-monitored tropical river basins,” Natural and Engineering Sciences, vol. 11, no. 1, pp. 221–232, 2026, doi: 10.28978/nesciences.261016.
Ulagammai Meyyappan, E. Sujatha, A. B. Philips, et al., “JusticeBot—A virtual legal assistant,” in Lecture Notes in Networks and Systems, vol. 1506, 2026.
Ulagammai Meyyappan, R. Vinifa, M. J. Krishnan, et al., “Leveraging machine learning for advanced security systems,” in Lecture Notes in Networks and Systems, vol. 1452, 2026
Ulagammai Meyyappan, J. S. Sylvia Grace, R. Saini, et al., “A novel algorithm for respiration rate detection using deep learning and real-time sensor data,” Journal of Wireless Mobile Networks, Ubiquitous Computing and Dependable Applications, vol. 16, no. 3, Dec 2025
Ulagammai Meyyappan, K. Balaji, V. Kaushik, et al., “Blockchain integrated cloud security: Novel AI-based traffic record transaction for financial sectors,” Journal of Internet Services and Information Security, vol. 15, no. 3, Dec 2025
Ulagammai, M., Parthasarathy, S,” Harnessing Artificial Intelligence for Improved Harmonic Reduction in Rectifier Systems: A Hybrid Power Filter Approach”,Ssrg International Journal of Electrical and Electronics Engineering,12(8), pp. 140-153, 2025
Optimal Placement of Renewable Based DG and DSTATCOM in Distribution Systems to Alleviate the Effects of EVCS, TD Suresh, M Thirumalai, M Ulagammai, R Hemalatha, Power Energy and Secure Smart Technologies, 2025
Optimization of Power Loss Mitigation in Distribution Systems Using Hunter-Prey Optimization Algorithm for Multiple Types of DFACTS, M Thirumalai, M Ulagammai, TD Suresh, C John De Britto, Power Energy and Secure Smart Technologies, 2025
Reliability Analysis of Distribution Systems with Solar-Based DG and Capacitor Integration Using the Water Cycle Optimization Algorithm, R Hemalatha, C John De Britto, T Yuvaraj, M Ulagammai, TD Suresh, Power Energy and Secure Smart Technologies, 2025
Reliability Analysis of Distribution Systems with Solar-Based DG and Capacitor Integration Using the Water Cycle Optimization Algorithm , R. Hemalatha, Britto C. John De, T. Yuvaraj, M. Ulagammai, T. D. Suresh, M. Thirumalai, Power Energy and Secure Smart Technologies, 2025
Intelligent Residential Energy Control with Demand Response Incorporating Renewable Power Sources and Electric Vehicle Integration, M Ulagammai, R Hemalatha, C John De Britto, TD Suresh, Power Energy and Secure Smart Technologies, 2025
Muthusamy, T., Meyyappan, U., Thanikanti, S.B. et al. “Enhancing distribution system performance by optimizing electric vehicle charging station integration in smart grids using the honey badger algorithm”. Scientific Reports -Nature 14, 27341 (2024)
Ulagammai Meyyappan , “A Novel approach on early detection of heart failure using sensor data and Machine Learning” – Under Review, Measurements: Sensor, Elsevier
Ulagammai, “Supercapacitor Based Electric Vehicle’ IEEE 4th International Conference on Sustainable Energy and Future, 2024
Ulagammai, “Smart Electric Vehicle Charging Station using Solar Power” IEEE 4th International Conference on Sustainable Energy and Future, 2024
Yuvaraj T,Suresh T, Ulagammai Meyyappan ,”Optimizing the allocation of renewable DGs, DSTATCOM, and BESS to mitigate the impact of electric vehicle charging stations on radial distribution systems”, Heliyon,Elseveir, Vol. 9,Issue 12Published online: November 28, 2023
J. Shanmuga Kani & M. Ulagammai (2023) Integrated Renewable Energy Storage System with Enhanced Self-Adaptive Differential Evolution Algorithm on Profit Maximization, Electric Power Components and Systems, August 2023
Ulagammai M, Kavitha D, Differential Evolution Algorithm Based Optimization of networked microgrids”- Lecture notes in networks and systems, Springer Nature, July 2023
Ulagammai M, “Security Camera with AI voice assistant and face recognition” – Springer , August 2023
Ulagammai M,Narayanamoorthy, “ An AR based intelligent precision agriculture using cascade advancement deep learning technique” – IEEE XPLORE, May 2023
M. Ulagammai, "Short Term Load Forecasting Using ANN and WNN," 2023 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), Bengaluru, India, 2023, pp. 612-616, doi: 10.1109/IITCEE57236.2023.10091081.
corporated energy storage systems”, - Intelligent Automation and Soft computing, Techscience press, June 2022, Vol 35, pp:399-413
Ulagammai.M, Joyal Isac.S, “Solar Power Forecasting Incorporated Energy Management Scheduling in a Microgrid:”,Design Engineering - 0011- 9342 Vol 2021: Issue 08, 4243-4249
Shanmugakani, Ulagammai Meyyappan, Joyal Isac, “A review on Optimal sizing of Battery storage technologies”, Solid state Technology, Vol no 63, 2s ,November 2020, ISSN: 0038-111X
Joyal Isac, Ulagammai Meyyappan, Shanmugakani, “Child Safety Wearable Device Using Raspberry Pi”, Solid state Technology, Vol no 63, 2s ,November 2020, ISSN: 0038-111X
Ulagammai Meyyappan, “Optimal Sizing and Allocation of Energy Storage in Wind Power Incorporated Optimal Power Flow”, - International Journal of Wind Engineering – June 2019
Ulagammai Meyyappan, “Wavelet neural network–based wind speed forecasting and application of shuffled frog leap algorithm for economic dispatch with prohibited zones incorporating wind power”, International journal of Wind Engineering, Sage Publications, August 2017
Ulagammai Meyyappan&Kumudini Devi RaguruPandu, ‘Wavelet Neural Network-based Wind-power Forecasting in Economic Dispatch: A Differential Evolution, Bacterial Foraging Technology, and PrimalDual-interior Point Approach’, Electric Power Components and Systems, Taylor and Francis, vol.43, no.13, pp.1–12, 2015
UlagammaiMeyyappan & KumudiniDevi,RP, ‘Wavelet Neural Network Based Wind Speed Forecasting and Wind Power Incorporated Economic Dispatch With Losses’,International journal of Wind Engineering, vol.39, no. 3, pp.237-252, 2015
Dhivya, S, Ulagammai, M&Kumudini Devi, RP, ‘Performance Evaluation Of Different Ann Models for Medium Term Wind Speed Forecasting’,International journal of Wind Engineering,vol.35, no.4,pp.433-444,2011
Ulagammai M , ‘Short Term Load Forecasting Using ANN and WNN’ InternationalJournal of Computer Trends and Technology (IJCTT) – March to April Issue , ISSN: 2231-2803, pp 179- 183, 2011
Ulagammai M, ‘Load Flow Analysis Using Particle Swarm Optimization Trained Neural Networks’, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 1, Issue 6, December 2012,pp 582-586
Ulagammai, M, Venkatesh, P, Kannan, PS & Narayana Prasad Padhy, ‘Application of Bacterial Foraging Tehnique Trained Artificial and Wavelet Neural Network in Load Forecasting’,Elseveir Science Direct, Journal of Neurocomputing, vol. 70, pp. 2659-2667, 2007.
SRMIST Vadapalani
Welcome to the academic hub of SRMIST Vadapalani, where excellence meets opportunity and where students, faculty and staff collaborate to create an environment of intellectual curiosity, personal growth and academic excellence.
