I am a Visiting Researcher (Full-Time) at ServiceNow Research, Montreal and a PhD student at MILA-Quebec AI Institute and CERC-AAI, Université de Montréal advised by Irina Rish and Alexandre Drouin. My current research interests are in time series forecasting and decision-making, with a focus on designing scalable general-purpose models for time series prediction tasks (forecasting, interpolation, imputation etc).
My email address is arjun.ashok [at] servicenow [dot] com. I'd love to connect and chat with you if we have shared interests, be it in research or music or anything else. Please shoot me an email if you'd like to connect!
Sep '24 | Co-organizing the The first NeurIPS workshop on Time Series in the Age of Large Models at NeurIPS 2024 in December. Consider participating! |
July '24 | Gave an invited talk on Natural Language based Context-Aware Forecasting at the International Symposium on Forecasting (ISF) 2024. |
May '24 | Presented TACTiS-2 at ICLR 2024. TACTiS-2 is a highly flexible model for multivariate probabilistic time series prediction tasks. Check out the tweet thread and poster here! |
Feb '24 | The full version of Lag-Llama released with open-source model checkpoints! Check the announcement here! |
Jan '24 | I gave a talk on our efforts Towards General-Purpose Models for Time-Series Prediction at the Winter 2024 Montreal Time Series Meetup. |
Jan '24 | TACTiS-2 accepted at ICLR 2024! |
Dec '23 | I gave a talk on Building Foundation Models for Time Series Data at the 6th workshop on Neural Scaling Laws co-located with NeurIPS 2023. |
Oct '23 | TACTiS-2 is out on arXiv. |
Oct '23 | A preliminary version of Lag-Llama is out on arXiv. |
Jan '23 | One paper on out-of-distribution detection accepted to ICLR 2023. This is work in collaboration with folks at ML Collective mentored by Rosanne Liu. |
Jan '23 | Started as a Visiting Researcher (Full-Time) at ServiceNow Research, Montreal. Excited to continue working on problems in time series representation learning! |
Aug '22 | Preliminary work on self-supervised learning objectives for weather time series accepted at the AAAI 2022 Fall Symposium on Climate Change. |
Jul '22 | One paper on Class-Incremental Learning accepted as a full paper at ECCV 2022. |
Jun '22 | Started as a Research Intern at IBM Research, India. I'll be working on building self-supervised learning objectives and pre-trained models for geospatial weather time series. |
Jun '22 | One paper on cross-task generalization in NLP submitted to EMNLP 2022 (Update: Accepted). |
Apr '22 | One paper on Class-Incremental Learning accepted at the CLVISION Workshop at CVPR 2022 as a non-archival paper (Update: Accepted at ECCV 2022). |
Apr '22 | One reproducibility report on Self-Supervision and Few-shot Learning accepted at the ML Reproducibility Challenge 2021 (Fall Edition) and published at ReScience-C. |
Oct '21 | One paper on out-of-distribution generalization accepted as AAAI 2022 as a student abstract. |
Jun '21 | Started as a Research Assistant at IIT Hyderabad under Prof. Vineeth Balasubramanian. |
TL;DR Abstract arXiv Code OpenReview Tweet Poster Blog 15-min Video
TL;DR Abstract Paper Code Weights Demo Tweet 15-min Video
I am a Carnatic Vocalist and a student of Vidwan Bharat Sundar. I have performed Carnatic concerts in multiple venues in India, and continue to perform in and around Montréal regularly. Here is a recording of a concert of mine from July 2024. |