Vaibhav Balloli

AI Researcher · Computer Science Ph.D. Candidate, University of Michigan

👋 Hi, I'm an AI researcher and a Computer Science Ph.D. candidate at the University of Michigan. I design and deploy interactive AI systems that help solve specific societal challenges across healthcare, wildlife conservation, road safety, and education. My research focuses on topics around LLMs, Reinforcement Learning, Representation Learning, and human-AI interaction.

Previously, I have worked at Microsoft Research: once as a summer intern working on improving interactivity of LLM agents and then as a Research Fellow for two years working on scaling HAMS, Vasudha, and improving multilingual capabilities of LLMs at VeLLM.

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Research

I work on human-centered AI, designing interactive AI systems that collaborate with people, surface the right uncertainty, and remain reliable when deployed in high-stakes domains such as healthcare, wildlife conservation, road safety, and education. My research sits at the intersection of large language models, reinforcement learning, representation learning, and human-computer interaction, spanning:

Interactive AI Agents: models and systems that allow stakeholders to improve their decision making.
Reliable evaluations: curating and benchmarking datasets for trustworthy real-world AI deployment.
Responsible Deployments: working closely with stakeholders to responsibly deploy these systems in the real world.

Want to see the research in motion? Look here for cool demos →

KDD 2026Datasets and Benchmarks Track

RELIANCE: Curating and Evaluating Reproductive Health Information on Social Media

Vaibhav Balloli, Laura Peyton Ellis, Vishala Mishra, Alice M Chi, Alex Friedman Peahl, Elizabeth Bondi-Kelly

Devise data curation multi-modal agents to collect and curate reproductive health information from TikTok and work with clinicians to evaluate the accuracy of the content and how LLMs perform in evaluating the content for accuracy and harms.

Paper Project

@inproceedings{balloli2026reliance,
  title          = {{RELIANCE}: Curating and Evaluating Reproductive Health Information on Social Media},
  author         = {Balloli, Vaibhav and Ellis, Laura Peyton and Mishra, Vishala and Chi, Alice M and Friedman Peahl, Alex and Bondi-Kelly, Elizabeth},
  booktitle      = {Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  year           = {2026},
  eprint         = {2606.18285},
  archivePrefix  = {arXiv},
  primaryClass   = {cs.IR},
  url            = {https://arxiv.org/abs/2606.18285}
}

Interactive Health 2026

PATHFinder Agents for Tailored Prenatal Care

Vaibhav Balloli, Carissa Samuel, Samia Abdelnabi, Alex Peahl, Elizabeth Bondi-Kelly

Interactive LLM agents that converse with pregnant people to provide personalized prenatal care information, planning, and resources to patients, and to assist clinicians.

Project

@inproceedings{balloli2026pathfinder,
  title     = {PATHFinder Agents for Tailored Prenatal Care},
  author    = {Balloli, Vaibhav and Samuel, Carissa and Abdelnabi, Samia and Peahl, Alex and Bondi-Kelly, Elizabeth},
  booktitle = {ACM Interactive Health},
  year      = {2026}
}

FAccT 2026

"Where is this coming from?" Uncovering Trustworthiness Ideals in AI-powered Peripartum Information Seeking

Vaibhav Balloli, Julia Erickson, Xinyi Li, Erin MacMurray van Liemt, Alex Friedman Peahl, Elizabeth Bondi-Kelly

Conduct focus groups to understand the role of AI-enabled information provision in the current health ecosystem and the trustworthiness and governance expectations of stakeholders.

Paper Project

@inproceedings{balloli2026maternal,
  title          = {``Where is this coming from?'' Uncovering Trustworthiness Ideals in {AI}-powered Peripartum Information Seeking},
  author         = {Balloli, Vaibhav and Erickson, Julia and Li, Xinyi and MacMurray van Liemt, Erin and Friedman Peahl, Alex and Bondi-Kelly, Elizabeth},
  booktitle      = {Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency},
  year           = {2026},
  eprint         = {2606.10158},
  archivePrefix  = {arXiv},
  primaryClass   = {cs.HC}
}

CV4Animals @ CVPR 2026

SEEK-CBM: Editable and Interpretable Retrieval for Elephant Re-Identification

Antoine Salaün, Vaibhav Balloli, Timm Haucke, Elizabeth Bondi-Kelly, Sara Beery

SEEK-CBM upgrades CHAIR to modern vision architectures and self-supervised techniques to achieve a 497% improvement in performance.

Paper Project Code

@inproceedings{seekcbm2026salaun,
  title     = {{SEEK}-{CBM}: Editable and Interpretable Retrieval for Elephant Re-Identification},
  author    = {Sala{\"u}n, Antoine and Balloli, Vaibhav and Haucke, Timm and Bondi-Kelly, Elizabeth and Beery, Sara},
  booktitle = {6th Workshop on CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling, in conjunction with CVPR 2026},
  year      = {2026}
}

COLING 2025

Oral

Bridging the Gap: Dynamic Learning Strategies for Improving Multilingual Performance in LLMs

Somnath Kumar*, Vaibhav Balloli*, Mercy Ranjit, Tanuja Ganu, Kabir Ahuja, Sunayna Sitaraman, Kalika Bali

A dynamic strategy that selects, per query at run-time, the optimal prompt, LLM, and embedding model to maximize multilingual QA performance, improving non-Latin and low-resource language coverage without any extra training.

Paper

@inproceedings{kumar2025leap,
  title     = {Bridging the Gap: Dynamic Learning Strategies for Improving Multilingual Performance in LLMs},
  author    = {Kumar, Somnath and Balloli, Vaibhav and Ranjit, Mercy and Ganu, Tanuja and Ahuja, Kabir and Sitaraman, Sunayna and Bali, Kalika},
  booktitle = {Proceedings of the International Conference on Computational Linguistics (COLING)},
  year      = {2025},
  note      = {Oral}
}

IJCAI 2024Human-Centered AI track

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Are They the Same Picture? Adapting Concept Bottleneck Models for Human-AI Collaboration in Image Retrieval

Vaibhav Balloli, Sara Beery, Elizabeth Bondi-Kelly

CHAIR adapts Concept Bottleneck Models so experts can intervene on intermediate concepts during image retrieval, a setting that matters for wildlife re-identification platforms like ElephantBook. Flexible levels of intervention let domain experts spend effort where it's most useful, achieving genuine human-AI complementarity.

Project Code

@inproceedings{balloli2024chair,
  title     = {Are They the Same Picture? Adapting Concept Bottleneck Models for Human-AI Collaboration in Image Retrieval},
  author    = {Balloli, Vaibhav and Beery, Sara and Bondi-Kelly, Elizabeth},
  booktitle = {Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI)},
  year      = {2024}
}

NeurIPS 2023

Chanakya: Learning Runtime Decisions for Adaptive Real-Time Perception

Anurag Ghosh, Vaibhav Balloli, Akshay Nambi, Aditya Singh, Tanuja Ganu

A learned approximate-execution framework for streaming perception. Chanakya jointly considers scene content and system contention to pick run-time decisions (resolution, model, compute) that balance accuracy and latency, beating static and dynamic baselines on both server GPUs and edge devices.

Paper Code Project

@inproceedings{ghosh2023chanakya,
  title     = {Chanakya: Learning Runtime Decisions for Adaptive Real-Time Perception},
  author    = {Ghosh, Anurag and Balloli, Vaibhav and Nambi, Akshay and Singh, Aditya and Ganu, Tanuja},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year      = {2023}
}

Cool Demos

Interactive animations and visualizations from my research projects.

SEEK-CBM

Editable and interpretable retrieval for elephant re-identification.

Read the paper →

PATHFinder

Interactive agents for tailored prenatal care.

View the project →

Things I keep going back to

A short, evolving shelf of books and talks I find myself returning to.

📚 Reading

Project Hail Mary
Andy Weir
A problem-solving-as-survival sci-fi novel: first-principles reasoning under extreme constraints.
Deep Work
Cal Newport
On cultivating sustained, distraction-free focus as a competitive advantage for knowledge work.
Principles of Mixed-Initiative User Interfaces
Eric Horvitz (CHI 1999)
The foundational paper on designing systems where humans and automated agents collaborate fluidly.
The Bitter Lesson
Richard Sutton
Short essay arguing that general methods leveraging computation tend to win out over hand-crafted knowledge.

🎬 Talks & videos

The Last Lecture: Achieving Your Childhood Dreams
Randy Pausch
Prof. Randy Pausch's wise, funny lecture on living with intention.
How to Live an Asymmetric Life
Graham Weaver (Stanford GSB Last Lecture)
On doing hard things for decades and betting on outsized, asymmetric outcomes.