Chaitanya Devaguptapu bio photo

Chaitanya Devaguptapu

AI Researcher
Fujitsu Research
Bangalore, India

Hi,

I’m a Researcher at Fujitsu Research India, focusing on Generative AI and related applications. I gravitate towards problems at opposite ends of the spectrum - either those with clear practical applications or purely exploratory endeavors that spark curiosity. I completed my Master’s by Research (M.Tech-RA) in Computer Science from IIT-Hyderabad, where I was fortunate to be advised by Prof. Vineeth N Balasubramanian. During my graduate studies, I also had the opportunity to work as a visiting researcher at the University of Toronto and Vector Institute with Prof. Animesh Garg.

My research journey began in computer vision and deep learning during my Master’s, where I explored Data-efficient learning techniques including active learning, transfer learning, and multi-modal learning. Currently, my work spans the broader spectrum of Generative AI, where I combine research insights with engineering to deliver useful solutions. Throughout my academic career, I’ve maintained a strong connection to education and teaching, serving as a Teaching Assistant for various courses at IIT-Hyderabad and serving as mentor and coach with platforms like Udacity and UpGrad.


News

[Jan 2025] Our work on Hybrid Graphs for Table-Text QA is accepted at NAACL-2025
[Jan 2025] My Team has won the Fujistu Research India's grand award for our work on Knowledge Graphs
[Oct 2024] Our work on developing a training free approach for 3D Scene Editing is accepted at WACV-2025
[May 2024] Our work on leveraging 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 Assistant 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 Hyderabad. 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!.