Chaitanya Devaguptapu bio photo

Chaitanya Devaguptapu

AI Researcher
Fujitsu Research
Bangalore, India

Hi,

I’m a Researcher at Fujitsu Research India, working on Generative AI, particularly the intersection of LLMs and Knowledge Graphs for enterprise applications. I hold a Master’s by Research (M.Tech-RA) in Computer Science from IIT-Hyderabad, advised by Vineeth N Balasubramanian. I also had the opportunity to be a visiting researcher at the University of Toronto and Vector Institute with Animesh Garg.

My research interests are diverse but converge around computer vision and deep learning. Specifically, my previous works have been focused on data-efficient learning techniques such as active learning, transfer learning, and multi-modal learning. I have also explored topics such as adversarial robustness and Neural Architecture Search. Beyond solving research problems, I am also keen on applying machine learning to address real-world, industry-specific challenges.


News

[May 2024] Our working on levergaing Knowledge Graph for answering multi-hop questions is accepted at ACL-2024 🌟
[June 2024] Work done by my team at Fujitsu Research India is featured in a recent press release
[Apr 2024] Got promoted to a Senior Researcher 🌟
[Oct 2023] I have started leading a small team that works on GenAI research at Fujitsu Research India!
[Sep 2023] Serving as a reviewer for ICLR
[Aug 2023] One paper accepted at WACV 2024 🌟 (Update: Accepted as an Oral -- Top 6% of the accepted papers)
[July 2023] Got promoted to Researcher II (in a span of 11 months) 🌟
[July 2023] Serving as a reviewer for AAAI, WACV
[July 2023] Paper on improving annotation efficiency accepted at ICML workshops
[June 2023] Serving as a reviewer for NeurIPS-2023
[Aug 2022] Serving as a reviewer for AAAI-2023
[Aug 2022] After four wonderful years (1 year as a RA and 3 years as a Masters with Research student) at IIT Hyderabad, I am joining Fujitsu Research of India as an Applied Researcher-I
[July 2022] Serving as a reviewer for WACV-23 and ACCV-2022
[June 2022] Serving as a reviewer for NeurIPS-2022
[May 2022] Serving as a (emergency) reviewer for ECCV-2022
[Apr 2022] Received Appreciation in Research award from IIT-Hyderabad 🌟
[Feb 2022] Selected to attend Research week with Google organised by Google Research India
[Jan 2022] Serving as a reviewer for IEEE Pattern Recognition Journal
[Oct 2021] Serving as a reviewer for ICLR-2022
[Sep 2021] Updated and the final version of On Adversarial Robustness: A Neural Architecture Search Perspective is accepted at the Adversarial Robustness in the Real World workshop at ICCV-21
[Aug 2021] I am working as a Teaching Assitant for the Reinforcement Learning course offered at IIT-H.
[July 2021] Our final paper with results, On Initial Pools for Deep Active Learning is accepted to be included in the Proceedings of Machine Learning Research (PMLR), a sister publication to the Journal of Machine Learning Research (JMLR). This was made possible by the NeurIPS 2020 Preregistration Workshop which encourages an alternative publication model for machine learning research.
[Jun 2021] Selected (again) for CIFAR 2021 DLRL summer school 🌟
[Mar 2021] Our work On Adversarial Robustness: A Neural Architecture Search perspective is accepted at 4 ICLR-21 workshops! Contributed talk at Responsible AI workshop 🌟
[Feb 2021] I am working as a Teaching Assitant for the Deep Learning for Computer Vision course at IIT-H. (Instructor: Vineeth N Balasubramanian). Online version of the course is also available open through NPTEL, India
[Jan 2021] Excited to visit (virtually) PAIR lab, University of Toronto as a graduate visiting researcher! 🌟
[Dec 2020] Selected for Shastri Research Student fellowship; one among the eight students selected in India! 🌟
[Nov. 2020] Our proposal, On Initial Pools for Deep Active Learning is accepted at Preregistration Workshop at Neural Information Processing Systems conference (NeurIPS'20).
[Oct. 2020] Started an ACM student chapter at IIT-Hyderabad with my peers; I will be serving as a Vice-chair for this chapter.
[Aug 2020] Served as a reviewer for MFI-2020
[July 2020] Served as a sub-reviewer for NeurIPS-2020
[Apr. 2019] Selected to attend DLRL summer school organised by CIFAR and MILA 🌟
[Jun. 2020] Served as sub-reviewer for BMVC-2020!
[Jun. 2020] Started working a Small group Coach for upGrad’s PG diploma programs in Machine Learning and Data Science.
[Apr. 2020] Completed a project with DRDO (Defence RnD), Government of India. 🌟
[Jan. 2020] Selected to intern at AIST, Japan this summer. (update: postponed due to COVID-19 outbreak)
[Oct 2019] Served as sub-reviewer for ICLR-2020, AAAI-2020!.
[July 2019] Started my Masters with Research Assistantship at IIT Hyderbad. Fortunate to have Dr. Vineeth Balasubramanian as my advisor. 🌟
[Jun 2019] Released code for Borrow from Anywhere paper
[May 2019] Served as sub-reviewer for ICCV-2019
[Apr 2019] Our work on Borrowing features from RGB to improve detection in Thermal domain is accepted at the PBVS workshop, CVPR 2019 (Spotlight Talk). 🌟
[Jan 2019] Served as sub-reviewer for CVPR-2019!.