Scholar
Bhavya Chopra
Google Scholar ID: uoGJY9MAAAAJ
University of California, Berkeley
Citations & Impact
Citations
205
H-index
7
i10-index
6
Publications
15
Co-authors
14
list available
Publications
Resume (English only)
Academic Achievements
- Published several papers, including 'Why do Multi-Agent LLM Systems Fail?' (NeurIPS 2025), 'Steering Semantic Data Processing with DocWrangler' (UIST 2025, Best Paper Honorable Mention), 'Rethinking Dataset Discovery with DataScout' (UIST 2025), 'Challenges in Using Conversational AI for Data Science' (HILDA, SIGMOD 2025), 'Let's Fix This Together: Conversational Debugging with GitHub Copilot' (VL/HCC 2024, Best Paper Award), 'Semantically Aligned Question and Code Generation for Automated Insight Generation' (LLM4Code Workshop, ICSE 2024, Best Paper Award), 'Detangler: Helping Data Scientists Explore, Understand, and Debug Data Wrangling Pipelines' (VL/HCC 2023, Best Paper Award), 'CoWrangler: Recommender System for Data Wrangling Scripts' (SIGMOD 2023 Demonstration), 'StoryBox: Independent Multi-modal Interactive Storytelling for Children with Visual Impairment' (CHI 2022 Late-Breaking Work), and 'Reality Tales: Facilitating User-Character Interaction with Immersive Storytelling' (CHI 2021 Student Research Competition, Second Position, undergraduate category).
Research Experience
- Interned at Tableau Research, mentored by Arjun Srinivasan. Previously, a Research Fellow with the PROSE Team at Microsoft, advised by Austin Z. Henley, Chris Parnin, and Anna Fariha. The work focused on identifying challenges in conversational and recommendation-based AI systems for data science and exploring agent-based frameworks to enable collaborative debugging with LLMs.
Education
- Completed a bachelor’s degree in Computer Science and Design engineering (with honors) from IIIT-Delhi in 2022. Currently pursuing a PhD at the EPIC Data Lab, University of California, Berkeley, advised by Prof. Aditya Parameswaran.
Background
- A second-year CS PhD student at UC Berkeley, designing and building mixed-initiative data systems that combine human insight with LLM capabilities to help end-users transform and interpret data at scale.
Miscellany
- Served as a Teaching Assistant at IIIT-Delhi, teaching Program Analysis (CSE503) and Introduction to Human-Computer Interaction (DES102). Reviewed for CHI 2026, UIST 2025, CHI 2024 Late-Breaking Work, CHI 2023, and CHI 2022 Late-Breaking Work. Volunteered as a student at CSCW 2022, CHI PLAY 2022, CSCW 2021, and IndiaHCI 2021.
