Technical Intern @Cisco | Prev. Multimodal AI Research @IISc | Final Year CSE student @PES University
I'm a final-year Computer Science undergraduate at PES University, advised by Dr. Gowri Srinivasa, with a strong research focus on Deep Learning and Generative AI Applications. My interests revolve around building scalable and efficient AI systems, with particular emphasis on representation learning, multimodal alignment, contrastive learning, and fine-tuning strategies for foundation models.
I've worked on methods like UnoLoRA for efficient multitask adaptation, explored grounding information better in vision-language models, and developed cross-lingual sparse Mixture of Experts architectures. My broader goal is to make foundation models more aligned, interpretable, and adaptable across tasks and modalities.
In addition to research, I've applied these ideas in real-world settings through roles at IISc, Swiggy, Nokia, and Cisco, where I worked on applying generative AI across practical domains such as finance and healthcare, building conversational recommender systems for personalized item suggestions, solving graph network problems, and designing automated pipelines for data center maintenance and monitoring.
Publications
UnoLoRA: Single Low-Rank Adaptation for Efficient Multitask Fine-tuning
NeurIPS 2024 Workshop on Fine-Tuning in Modern Machine Learning
View Paper →Analysis of Sampling Strategies for Multi-Task Learning in Transformer Models
2025 15th International Conference on Electrical Engineering (ICEENG)
View Paper →Finding Potential On-street Parking Spots: An Object Detection and Segmentation Approach
8th International Conference on Smart Trends in Computing and Communications
View Paper →Latest Achievements
Hasgeek Open Source AI Hackathon Winners
January 2024 - April 2024
Winners of the National Level Open Source AI Hackathon (Winter Edition) hosted by Hasgeek, sponsored by Microsoft and Meta.
View Announcement →