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Hello! Welcome to my page.
I am currently working as a postdoctoral research associate with Prof. Ram Ramamoorthy at Institute of Perception, Action and Behaviour in School of Informatics and College of Science and Engineering at the University of Edinburgh. I am developing computational methods for generative modeling of human behavior towards building AI for Assistive Autonomy. Previously, I worked as postdoctoral research associate at the University of Manchester where I worked on human-in-the-loop modeling for multi-objective Bayesian optimization under the supervision of Prof. Samuel Kaski. Prior to that, I earned my Ph.D. from the Department of Computer Science at Indian Institute of Technology, Hyderabad, under the supervision of Dr P.K Srijith and Dr. Maunendra Sankar Desakar where I investigated towards modeling of event sequences using temporal point processes and neural networks. You can find my CV here for more details.
My research focuses on developing algorithms for machine learning and demonstrating the practical impact of these innovations in diverse applications such as event sequences, time-series analysis, natural language processing, social network analysis, and scientific discovery. I have worked on a variety of methods like Bayesian techniques, deep learning, stochastic processes and graph neural networks. My research interests and experiences include multi-objective optimization, Human-AI collaboration, survival analysis, temporal point processes, sequential modeling and spatio-temporal modeling. I am interested in working in interdisciplinary research areas as well, where I can utilize my research knowledge of machine learning models for solving real-world challenges.
News
Serving as PC Member for ICDCIT, 2025.
Our paper titled "Drift-aware Neural Hawkes Process for Time-to-Event Modelling" is accepted at CODS-COMAD, 2024. Congratulations to Vaibhav and Vishnu.
Gave a talk at LMU Munich under DAAD fellowship.
Honored to receive DAAD Postdoc Net-AI fellowship, 2023.
Our work "Bayesian Neural Hawkes Process" is accepted at JDSA, 2023.
"Time-to-Event Modeling with Hypernetwork based Hawkes Process" accepted at KDD 2023.
Attended ELLIS Summer School on ML for Healthcare at Manchester.
Attended London Symposium on Information Theory at UCL.
Joined as postdoctoral associate at the University of Manchester.
Successfully defended thesis titled "Improving Temporal and Spatial Event Modeling using Hawkes Process and Neural Networks".
Presented a talk on 'Continual Learning for Time-to-Event Modeling' in Workshop on Continual Lifelong Learning in ACML 2022.
Our work on Hawkes Process for discriminative classification is accepted at IJCNN, 2022. Arxiv is available here.
Honored to serve as Web Chair at ACML, 2022
Awarded Intel India Research Fellowship, 2021
Multi-view Hypergraph Convolution Network for Semantic Annotation in LBSNs accepted at ASONAM 2021
Presenting poster at WiML, NeurIPS, 2020
Work on semantic annotations in LBSNs using spatio-temporal Hawkes process accepted at SIGSPATIAL, 2020. The Arxiv version of paper is here.
Attended Microsoft Academic Research Summit 2020 and Amazon Research Days, 2019
Grateful to attend ACM India Grad Cohort, 2019 at IIT Delhi
Won second prize in Honeywell AI and ML Hackathon, 2019.
ML for social cause: During Kerala floods, we used our expertise to extract information regarding need and availability of various resources. For more details, please visit here.
Work on predicting best answerers in community question answering sites accepted at RecSys, 2018.
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