-
Senior Applied Scientist, Responsible AI; Salesforce - San Francisco, CA
January 2026 – Present
-
AI/ML Engineer; University of California, San Francisco - San Francisco, CA
September 2023 – December 2025
Architected and deployed clinical AI systems to save social workers 300+ hours/ week, identify patients at risk for readmission, and create simple, interpretable models from multimodal patient data
Drove end-to-end architecture of a GPT 4o powered clinical summarization pilot to condense patient charts (20K+ tokens) into actionable summaries, co-developed with 5+ clinicians to improve patient care
Established and led human and automated annotation pipelines with active learning to ensure 90%+ accuracy on 1000+ GPT 4o clinical summaries
Designed and deployed a scalable ETL pipeline to process health record data, enabling ML training and evaluation for 3000+ patient records and 30000+ patient visits
Engineered, deployed, and evaluated a custom readmission risk prediction model, adopted by 10+ clinics, with 12% higher accuracy than the general model
Created and presented a hybrid LLM-empirical framework to reconcile clinical LLM hallucinations, achieving 40% interpretability improvement (validated by clinical experts) while matching top predictive performance and enabling production deployment
Developed and authored a publication for a scalable agentic pipeline using GPT-4 with statistical learning to generate interpretable clinical features from multimodal data, outperforming black-box models while maintaining interpretability for decision support
-
ML Engineer; University of California, SD; CA
June 2022 – Mar 2024
Developed a model-agnostic bias auditing framework surfacing bias in up to 30% of lending datasets across 5+ models and 3+ datasets with 25+ real-world constraints
Collaborated with a lending expert to define real-world constraints on lending datasets to identify individuals subject to preclusion
Authored a publication that received an ICLR Spotlight (Top 5% among submissions)
-
Software Engineer; Edovo - Chicago, IL
Jan 2020 – May 2021
Led the re-architecture and deployment of a scalable educational platform, handling the full lifecycle from leading product requirement sessions to engineering a data backend
Architected, tested, and deployed a content platform using Elasticsearch to handle 700K+ requests per day to thousands of users
Led 10+ requirement gathering sessions with Product owners to re-build a platform
Created a data pipeline and job to merge 4B rows of user event data in PostgreSQL
-
Lead Software Engineer; 8th Light - Chicago, IL
Aug 2017 – March 2019
Built high-performance technical systems from inception to production, including load testing platforms, API integrations, and patient-facing healthcare applications
Implemented and deployed a scalable load testing platform simulating 1000+ RPS
Deployed API integrations to sync 1000+ interactions/ minute in different timezones
Developed a diabetes management iOS app to connect 60+ patients with diabetic nurses
Mentored peers and residents through pair programming sessions and code reviews
-
MAStrike: Shapley-Guided Collusive Red-Teaming on Multi-Agent Systems
Chejian Xu, Zhaorun Chen, Jingyang Zhang, Freddy Lecue, Avni Kothari, et al
pre print, 2026
Human-AI Co-design for Clinical Prediction Models
Jean Feng*, Avni Kothari*, et al
* denotes equal contribution
NPJ Digitial Medicine, 2026; Article
When the Domain Expert Has No Time and the LLM Developer Has No Clinical
Expertise: Real-World Lessons from LLM Co-Design in a Safety-Net Hospital
Avni Kothari, et al
AAAI - Social Impact Track - Oral Presentation, 2026
Concept Bottleneck Models with LLM Priors
Jean Feng, Avni Kothari, et al
NeurIPS , 2025
Prediction without Preclusion: Recourse Verification with Reachable Sets
Avni Kothari, et al
ICLR – Top 5% among submissions , 2024
Bayesian Priors From Large Language Models Make Clinical Prediction Models More Interpretable
Avni Kothari, et al
AMIA - American Medical Informatics Association, Podium Abstract, 2024
Implementing a Predictive Model to Reduce Hospital Readmissions in a Safety Net Healthcare System
Arturo Gasga, Avni Kothari, et al
ML4H - Machine Learning for Health, Oral Spotlight , 2024
-
NeurIPS Workshop Statistical Foundations of LLMs and Foundation Models
December 2024
-
ICML Workshop on Data-centric Machine Learning Research
July 2023
-
ICML Workshop on Spurious Correlations, Invariance and Stability
July 2023
-
ICML Workshop on Artificial Intelligence & Human Computer Interaction
July 2023
