1. Nojan Sheybani, Zahra Ghodsi, Ritvik Kapila, and Farinaz Koushanfar. "Zero Knowledge Right of Ownership for Neural Networks (ZKROWNN)", To appear at Design Automation Conference [paper][patent] (DAC 2023)

-- out-of-date: for most recent papers, please visit my Google Scholar profile. --

1. Rethinking Reflection in Pre-training [paper]

2. Ranak Roy Chowdhury, Ritvik Kapila, Ameya Panse, Xiyuan Zhang, Diyan Teng, Rashmi Kulkarni, Dezhi Hong, Rajesh K. Gupta, Jingbo Shang. ZeroHAR: Sensor Context Augments Zero-Shot Wearable Action Recognition (AAAI 2025)

3. Abhishek Singh, Gauri Gupta, Yichuan Shi, Alex Dang, Ritvik Kapila, Sheshank Shankar, Mohammed Ehab, Ramesh Raskar. Co-Dream: Collaborative dream synthesis over decentralized models [website] (AAAI 2025)

4. Gauri Gupta, Ritvik Kapila, Ayush Chopra, Ramesh Raskar. First 100 days of pandemic; an interplay of pharmaceutical, behavioral and digital interventions -- A study using agent based modeling [paper] [poster] (Oral Presentation and Best Student Paper Runners Up Award) (AAMAS 2024)

5. Gauri Gupta, Ritvik Kapila, Keshav Gupta, and Ramesh Raskar. "Domain Generalization in Robust Invariant Representation", presented at International Conference on Learning Representations workshop [paper] [code] [slides] (ICLR 2023) 

6. Nojan Sheybani, Zahra Ghodsi, Ritvik Kapila, and Farinaz Koushanfar. "Zero Knowledge Right of Ownership for Neural Networks (ZKROWNN)", To appear at Design Automation Conference [paper][patent] (DAC 2023)

Research Experience at UC San Diego:

At UC San Diego, I worked as a Graduate Student Researcher on deep learning and time-series zero-shot learning with the Microelectronic Embedded Systems Laboratory, guided by Prof. Rajesh Gupta at UCSD. I have also previously worked on privacy-preserving ML with the Adaptive Computing and Embedded Systems (ACES) research group, guided by Prof. Farinaz Koushanfar at UCSD. My research involved designing a non-interactive zero-knowledge proof system for neural network watermarking. The research has been accepted at the Design and Automation Conference (DAC 2023) and we've also published a patent for the same.

Research Experience in collaboration with Camera Culture group, MIT Media Lab:

I worked on “Domain Generalization in Robust Invariant Representation” in collaboration with Camera Culture Group, MIT Media Lab in Winter 2023. The project explored the generalization of invariant representations to out-of-distribution data, investigating whether models invariant to transformations in one domain remain invariant in unseen domains. Our work was accepted in the PML4DC workshop at the International Conference on Learning Representations (ICLR) 2023.