RESEARCH AREAS

RESEARCH INTERESTS

• Machine learning and other technologies for Theatre Arts and Cultural Heritage

• EdgeAI - Machine Learning and AI at the edge of the networks for healthcare

• Software Engineering Education

RESEARCH PROJECTS

Using Machine Learning to reconstruct historical objects in culturally-situated ways

The aim is to use ML to explore how historical artefacts might have been used in their original cultural contexts. Our goal is to generate movable 3D objects from static 2D images. These can be used in many digital environments such as videos and AR/VR settings to enable scholars/general public to explore the usage of such objects and deepen their understanding of their context and function.

• Artificial Intelligence

RESEARCH GROUPS

TEACHING INNOVATIONS

SELECTED PUBLICATIONS

• Ganesh Neelakanta Iyer, B Veeravalli, SG Krishnamoorthy, On handling large-scale polynomial multiplications in compute cloud environments using divisible load paradigm, IEEE Transactions on Aerospace and Electronic Systems 48 (1), 820-831
• Lakshmi Tulasi Bhavanam, Ganesh Neelakanta Iyer, On the Classification of Kathakali Hand Gestures Using Support Vector Machines and Convolutional Neural Networks, 2020 International Conference on Artificial Intelligence and Signal Processing (AISP), 1-6
• Agrawal Naman, Ridwan Shariffdeen, Guanlin Wang, Sanka Rasnayaka and Ganesh Neelakanta Iyer, “Analysis of Student-LLM Interaction in a Software Engineering Project”, At the International Conference in Software Engineering (ICSE 2025), LLM4Code Workshop
• [BEST PAPER AWARD] Li Xue Pua, Rushil Ramesh, Prabhu Natarajan, Ganesh Neelakanta Iyer, “CustomAIzEd: Bridging Interdisciplinary Gaps in AI Education With Customized Content”, IEEE EDUCON, London, April 2025
• [BEST PAPER AWARD] Li Xue Pua, Rushil Ramesh, Prabhu Natarajan, Ganesh Neelakanta Iyer, “CustomAIzEd: Bridging Interdisciplinary Gaps in AI Education With Customized Content”, IEEE EDUCON, London, April 2025
• S. S. Vidhya, S. Mathi, V. Ananthanarayanan and G. Neelakanta Iyer, “IP-RPL: An Intelligent Power-Aware Routing Protocol for Next-Generation Low-Power Networks,” in IEEE Sensors Journal, vol. 25, no. 2, pp. 3640-3648, 15 Jan.15, 2025
• Ganesh Neelakanta Iyer and Sachit Bhardwaj. 2024 Kathakali character identification–using deep learning techniques and web technologies for Indian cultural heritage. Digital Applications in Archaeology and Cultural Heritage, 32:e00300
• Ganesh Neelakanta Iyer, Lim Bing Sen, Wong Zhi, Chester, Kelvin Chua, “TROFOS - Agile Project Management Platform for Software Engineering Education”, International Conference on Teaching, Assessment and Learning for Engineering, IEEE TALE, December 2024, India
• Sanka Rasnayaka, Wang Guanlin, Ridwan Shariffdeen, Ganesh Neelakanta Iyer, “An Empirical Study on Usage and Perceptions of LLMs in a Software Engineering Project”, At the International Conference in Software Engineering (ICSE 2024), LLM4Code Workshop
• Vidhya, S.S.; Mathi, Senthilkumar; Anantha Narayanan, V.; Neelakanta Iyer, Ganesh, ‘An Intelligent Fuzzy Enabled Parent Node Selection Approach in Low Power Networks’. Journal of intelligent and fuzzy-systems, 2024 Pages 1-11, IOS Pres
• [BEST PAPER AWARD] Wu Zhenhan, Ganesh Neelakanta Iyer, “Improved BCoop, A Cooperation-Promoting Reward Scheme in Heterogeneous Federated Learning”, 2024 4th International Conference on Data Engineering and Communication systems -ICDECS-2024 [March 22nd & 23rd 2024, RNSIT Bangalore
• Guoxin Wang, Member, Qingyuan Wang, Ganesh Neelakanta Iyer, Avishek Nag and Deepu John, “Unsupervised Pre-Training Using Masked Autoencoders for ECG Analysis”, Biomedical circuits and systems conference, IEEE BiOCAS, October 2023
• Sangeetha, Rakseda Keerthi Alagarsamy, Senthilkumar Mathi, Akibu Mahmoud Abdullahi and Ganesh Neelakanta Iyer. “Federated Learning-Based Parent Selection in Low Power and Lossy Networks to Enhance Energy Efficiency.” IEEE Open Journal of the Communications Society 6 (2025): 10123-10138.
• Mathi, S., Rohan Lal, G., Madala, L. C., Reddy, K. A., Jagadhabhiram, P., & Neelakanta Iyer, G. (2025). FedBHAD: Energy-Efficient Federated Learning for Black Hole Attack Detection in RPL-Based Low-Power IoT Networks. Emerging Science Journal, 9(6), 2884–2898. https://doi.org/10.28991/ESJ-2025-09-06-01
• Qingyuan Wang, Ganesh Neelakanta Iyer, Deepu John, Dynamic Model Mixtures for Efficient AI Inference in Real-Time Biomedical Applications, IEEE Transactions on Instrumentation & Measurement, Accepted for publication in 2026
• Jhoan Sebastian Tenjo Garcia, Alejandro Adorjan and Ganesh Neelakanta Iyer, Towards an Explainable Dropout Prediction Model: A Hybrid Neural Network Approach, IEEE EDUNINE 2026, Mexico, March 2026
• Gerald Ng Jun Xiang, Zong Xian Kang, Ganesh Neelakanta Iyer, “MLOPs, GenAI and Indian Cultural Heritage - A case study on employing technological advancements for Kathakali”, IEEE IMCOM, 20th International Conference on Ubiquitous Information Management and Communication, Hanoi 2026
• Lim Song Yang, Samuel, Tang Bo Kuan, Tham Rui Cong, Julian Rosas Scull, Alejandro Adorjan, Ganesh Neelakanta Iyer, AI Enabled Agile Project Management Platform for Learning and Assessment in Software Engineering Education, IEEE EDUCON 2026 Egypt

AWARDS & HONOURS

• University Topper (First Rank) for the undergraduate degree examination in 2004

• National University of Singapore, Postgraduate Research Scholarship, 2009-2012

• Certified Kubernetes Administrator (CKA)

• School of Computing, Faculty Teaching Excellence Award 2024

COURSES TAUGHT