Pandarasamy Arjunan (Samy)

I am an Assistant Professor at the Robert Bosch Centre for Cyber-Physical Systems (RBCCPS), Indian Institute of Science, Bangalore, India. Previously, I worked as a postdoctoral scholar at the Berkeley Education Alliance for Research in Singapore(BEARS) Limited, a research center of the University of California, Berkeley, located in Singapore. I worked for the SinBerBEST 2 program (Theme D: Data Analytics for the Built Environment) under Prof. Kameshwar Poolla. I completed my Ph.D. in Computer Science and Engineering at Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), India, under the guidance of Dr. Amarjeet Singh and Prof. Pushpendra Singh. Before that, I received my Master’s degree in computer applications from Madurai Kamaraj University, Tamilnadu, India.

My current research interests lie in the intersection of Cyber-Physical Systems and Data Science and their applications pertaining to smart built environments and energy sustainability. Specifically, I focus on developing systems and techniques for energy monitoring, benchmarking, prediction, anomaly detection, and fault detection and diagnosis by leveraging smart meter time series and other opportunistic data sources. I have recently started investigating how to leverage Infrared Thermography (IRT) for city-scale building diagnostics and energy auditing.

My CV can be found here!

Hiring Alert: I am actively looking for highly motivated candidates for various positions, including Project Assistant, M.Tech/PhD Research, and Postdoc. If you are interested, please get in touch with me through email.


May 11, 2022
Our dataset description article titled LEAD1.0: A Large-scale Annotated Dataset for Energy Anomaly Detection in Commercial Buildings got accepted to the International Workshop on Energy Data and Analytics workshop co-located with the 13th ACM International Conference on Future Energy Systems (ACM e-Energy).
Jan 18, 2022
Our research article titled BEEM: Data-driven Building Energy bEnchMarking for Singapore got accepted to the Energy and Buildings journal.
Oct 10, 2021
Our research article titled Operational characteristics of residential air conditioners with temporally granular remote thermographic imaging got accepted at ACM BuildSys 2021.
Mar 31, 2021
Our research article titled Explainable AI for Chiller Fault-Detection Systems: Gaining Trust and Human Connect got accepted to the IEEE Computer magazine’s special issue on “Explainable AI and Machine Learning” to be publicized in October 2021.
Sep 29, 2020
The Building Data Genome Project 2 paper got accepted to the Nature’s Scientific Data journal. We have released an open data set of 3,053 energy meter data from 1,636 non-residential buildings.