charvirastogi

Charvi Rastogi

I am a Ph.D. student in the Machine Learning Department at Carnegie Mellon University, where I am co-advised by Nihar Shah and Ken Holstein. I have been lucky to collaborate with Sivaraman Balakrishnan. I am interested in using tools in statistics, machine learning, and HCI towards effective human-AI collaboration for a variety of tasks, such as decision-making, auditing, crowdsourcing. I am deeply passionate about using my skills to address gaps in socio-technical systems to help make them useful in practice, when possible.

My research is generously supported by a J.P. Morgan AI Research Fellowship and a IBM PhD Fellowship.

I have spent some fun summers working at Microsoft Research Redmond, IBM TJ Watson Research Center and Syracuse University, NY. In a past life, I was a wide-eyed undergrad at Indian Institute of Technology Bombay.

CV. Google Scholar.

Preprints

Insights on Disagreement Patterns in Multimodal Safety Perception across Diverse Rater Groups
Charvi Rastogi, Tian Huey Teh, Pushkar Mishra, Roma Patel, Zoe Ashwood, Aida Mostafazadeh Davani, Mark Diaz, Michela Paganini, Alicia Parrish, Ding Wang, Vinodkumar Prabhakaran, Lora Aroyo, Verena Rieser
Safe Generative AI Workshop, NeurIPS'24; arXiv

Publications, Presentations, and Posters

Adversarial Nibbler: An Open Red-Teaming Method for Identifying Diverse Harms in Text-to-Image Generation
Jessica Quaye*, Alicia Parrish*, Oana Inel, Charvi Rastogi, Hannah Rose Kirk, Minsuk Kahng, Erin van Liemt, Max Bartolo, Jess Tsang, Justin White, Nathan Clement, Rafael Mosquera, Juan Ciro, Vijay Janapa Reddi, Lora Aroyo
ACM Proceedings of FAccT 2024; featured on the Google Research blog.
How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions?
Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, Zhenyu Xue, Hal Daumé III, Emma Pierson, and Nihar B. Shah
Published in PLOS ONE'24; featured on Communications of ACM blog and NeurIPS blog.
A Taxonomy of Human and ML Strengths in Decision-Making to Investigate Human-ML Complementarity
Charvi Rastogi*, Leqi Liu*, Ken Holstein, Hoda Heidari,
Poster presented at HMCAT Workshop (ICML 2022); EAAMO 2022; AAAI Proceedings of HCOMP 2023; featured on the CASMI blog
Supporting Human-AI Collaboration in Auditing LLMs with LLMs
Charvi Rastogi, Marco Tulio Ribeiro, Nicholas King, Harsha Nori, Saleema Amershi
ACM Proceedings of AIES 2023; featured on the Montreal AI Ethics Institute blog.
DataPerf: Benchmarks for data-centric AI development.
Mark Mazumder, [+43 authors].
Proceedings of the NeurIPS 2023 Datasets and Benchmarks Track; arXiv
To ArXiv or not to ArXiv: A Study Quantifying Pros and Cons of Posting Preprints Online
Charvi Rastogi*, Ivan Stelmakh*, Xinwei Shen, Marina Meila, Federico Echenique, Shuchi Chawla, Nihar B. Shah
Peer Review Congress (Abstract) 2022; arXiv.
Cite-seeing and Reviewing: A Study on Citation Bias in Peer Review
Charvi Rastogi*, Ivan Stelmakh*, Ryan Liu, Shuchi Chawla, Federico Echenique, Nihar B. Shah
Peer Review Congress (Abstract) 2022; Full version in PLOS ONE; arXiv
No Rose for MLE: Inadmissibility of MLE for Evaluation Aggregation Under Levels of Expertise
Charvi Rastogi, Ivan Stelmakh, Nihar B. Shah, Sivaraman Balakrishnan
IEEE ISIT 2022. Link to the full version.
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making.
Charvi Rastogi, Yunfeng Zhang, Dennis Wei, Kush R. Varshney, Amit Dhurandhar, Richard Tomsett
Proceedings of CSCW 2022. ACM. Video Presentation.
A Large Scale Randomized Controlled Trial on Herding in Peer-Review Discussions
Ivan Stelmakh, Charvi Rastogi, Nihar B. Shah, Aarti Singh, Hal Daumé III
Peer Review Congress (Abstract) 2022; Full version in PLOS ONE; arXiv
Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions.
Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh
Shorter version presented at IEEE ISIT 2020 - Slides, Video Presentation; Longer version published in JMLR 2022; arXiv

A spectral approach for the design of experiments: Design, analysis and algorithms
Bhavya Kailkhura, Jayaraman J. Thiagarajan, Charvi Rastogi, Pramod K. Varshney, Peer-Timo Bremer
The Journal of Machine Learning Research, 2019; arXiv
Winner of 2019 S&T Excellence in Publication award
Mobile Sensing of Two-Dimensional Bandlimited Fields on Random Paths
Charvi Rastogi, Animesh Kumar
arXiv
Non-bandlimited Field Estimation with Location Unaware Mobile Sensors
Charvi Rastogi, Animesh Kumar
Poster presented at CSCIT'17

Collected Resources for Grad Students

Here is a form designed to help facilitate students checking in with their advisors (it has been used by SCS PhD students and received positive reviews!)
Here is a blog post to help new (and old) grad students through the immensely difficult task of (re) choosing their advisor
Here is a piece of research with helpful guidelines (contextualized with grad students' lived experiences) to empower students in focusing on community and mental health

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