MIND Lab

Hello! This is Machine Intelligence and Data Lab (MIND Lab) in the Computer Science Department at Boise State University. Our research centers on machine learning and foundation models with and for real-world social impact, integrating data and human-centric methods to pursue intelligent futures where people and AI co-thrive.

We are recruiting — Interested in joining? Get in touch.

News

Grant·

Lab Received Boise State TRANSFORM Seed Grant

Thanks to Boise State University for its support, and congratulations to Xinyi as PI. Our lab will collaborate with the Idaho Policy Institute and the City of Meridian on human-centered AI for real-world impact.

Event·

Xinyi Presented at SocialLLM @ ICWSM 2026

Xinyi presented "Multimodal Large Language Models as Synthetic Participants in Video-Based Studies: An Evaluation" at the Large Language Models for Social Reasoning and Simulation Workshop at ICWSM 2026 in Los Angeles, CA. Check out our paper, slides, and poster. The data and code have also been released.

Event·

Xinyi Spoke at 2026 AI Institute for Teaching and Learning

Xinyi spoke as a panelist at Boise State University's 2026 AI Institute for Teaching and Learning Workshop, discussing ethics and integrity in an AI-enhanced campus.

Announcement·

Welcome Anh to the Lab

We're excited to welcome Anh Bui to the lab as a summer intern working on an AI safety project, in collaboration with the fantastic Dr. Casey Kennington!

Paper·

Paper Accepted to SocialLLM @ ICWSM 2026

The paper, "Multimodal Large Language Models as Synthetic Participants in Video-Based Studies: An Evaluation," by Prabal Shrestha, Bohan Jiang (ASU), Haoning Xue (Utah), Huan Liu (ASU), Xinyi Zhou, was accepted to the Large Language Models for Social Reasoning and Simulation Workshop at ICWSM 2026. Congratulations to Prabal on being the lead author, and many thanks to our wonderful collaborators!

Award·

Xinyi Received COEN Early Scholar Award

Congratulations to Xinyi, the sole recipient of the Early Career Scholar Award from the College of Engineering at Boise State University!

Research

🛡️

Trust and Safety

AI, especially generative AI, is increasingly used by millions to billions of people and is shaping high-stakes decisions, making trust and safety central concerns. We develop methods to evaluate these systems and make them more factually accurate, explainable, accountable, robust to manipulation, aligned with human values, and less biased or harmful across groups.

🤝

Human–AI Collaboration

Human and artificial intelligence are complementary, each offering distinct strengths. We study these differences and develop tools and systems that enable humans and AI to work together synergistically.

🌐

Multimodality

The web and the world are multimodal, spanning interconnected text, images, audio, and video. We extract actionable insights from these data, develop methods to learn from both content and relationships within and across modalities, and augment foundation models through effective multimodal retrieval.

🎯

Future of Work, Health, and Education

We develop use-inspired AI for high-stakes domains, with a special focus on improving workplaces, healthcare, and education.

Publications

Preprint

Correcting misinformation on social media with a large language model

Xinyi Zhou, Ashish Sharma, Amy X Zhang, Tim Althoff

arXiv preprint

PDFCodeARTT
Conference2026

Can Large Language Models Assess the Social Impact of Conspiracy Theories?

Bohan Jiang, Dawei Li, Zhen Tan, Xinyi Zhou, Ashwin Rao, Kristina Lerman, H. Russell Bernard, Huan Liu

Proceedings of the International AAAI Conference on Web and Social Media (ICWSM)

PDF
Workshop2026

Multimodal Large Language Models as Synthetic Participants in Video-Based Studies: An Evaluation

Prabal Shrestha, Bohan Jiang, Haoning Xue, Huan Liu, Xinyi Zhou

Workshop on Large Language Models for Social Reasoning and Simulation (SocialLLM) @ ICWSM

Journal2026

Users' prompting strategies and ChatGPT's contextual adaptation shape conversational information-seeking experiences

Haoning Xue, Yoo Jung Oh, Xinyi Zhou, Xinyu Zhang, Berit Oxley

Scientific Reports

PDF

Team

Xinyi Zhou

Xinyi Zhou

Assistant Professor

Xinyi Zhou is an Assistant Professor of Computer Science at Boise State University, where she directs the MIND Lab. She was previously a postdoctoral scholar at the University of Washington and earned her PhD from Syracuse University. Her research spans machine learning, data mining, and human-centered AI, with work published in leading venues, featured in the media, and cited 6,000+ times. She has collaborated broadly across academia and industry to drive real-world impact and has been recognized as an MIT EECS Rising Star and a UCSD/UChicago/Stanford Rising Star in Data Science.

Trust and SafetyHuman–AI CollaborationMultimodalityFuture of Work, Health, and Education
Benjamin Lee Peterson

Benjamin Lee Peterson

PhD Student

Ben Peterson is a PhD student in Computer Science in the School of Computing at Boise State University. His research centers on human-centered AI, with a particular focus on AI in education and the design of educational chatbots. He holds a bachelor's degree in Computer Engineering from Brigham Young University. Ben's work connects research, teaching, and service around a common thread: how people learn with and about AI. Alongside his doctoral studies, he serves as an IT Systems Administrator in the Computer Science department at Boise State and teaches as an adjunct professor, leading sections of CS 121 and CS 153. Beyond the university, he is Lead Coach for local FIRST Tech Challenge (FTC) and FIRST LEGO League teams, and he serves on the K-12 AI Standards writing committee for the State of Idaho, helping shape how students across the state learn about artificial intelligence.

Human–AI CollaborationFuture of Work, Health, and Education
Stephanie Grim

Stephanie Grim

PhD Student

Stephanie joins the lab as an incoming PhD student starting in Fall 2026 with over a decade of experience in human subjects and healthcare research. She has worked closely with patients, clinicians, and research teams, seeing firsthand how health technologies are used in practice. She hopes to draw on this experience in her work on machine learning and human-centered AI, particularly in understanding how tools such as large language models can be developed and implemented in ways that support patients, clinicians, and health systems. She is excited about combining rigorous yet responsible research methods with practical healthcare needs. Outside of research, Stephanie is an avid outdoorsperson who spends much of her free time snowboarding, trail running, and mountain biking. She also loves animals and frequently fosters rescue puppies while they wait for their "furever" homes.

Future of Work, Health, and Education
Anh Bui

Anh Bui

Summer Intern

Anh is an MSCS student at Boise State University, working on trustworthy and reliable AI. Her current research centers on memory in agentic AI: how it shapes AI safety in real-world scenarios, why those effects arise, and how we could build memory systems that not only improve performance but also keep agents safe. In her spare time, she enjoys climbing and bouldering - and is still learning how to trust her feet.

Trust and Safety
Prabal Shrestha

Prabal Shrestha

Master Student

MS CS student at Boise State University researching multimodal LLMs, video-based fact-checking, and LLM-powered human simulation. Interested in how AI systems perceive and reason about video content, and in building systems that leverage language and vision models for real-world information integrity.

Human–AI CollaborationMultimodality
Funding

Funding

Lab Mascot

Funding is a super-friendly Westie who was born on May 30, 2026 in Denver, Colorado. He loves people, food, and slippers.

Pumpkin

Pumpkin

Lab Mascot

Pumpkin is a six-year-old British Shorthair who believes dogs are bad and curiosity didn't kill the cat.

Interested in Joining?

We welcome self-motivated doctoral, master's, and undergraduate students who are passionate about AI, data science, and human-centered computing.

Please briefly tell us about yourself, your interests, and how your background aligns with our work, and send us your transcript and CV/resume.

Computer Science Department

Boise State University

City Center Plaza (CCP) 255, 777 W Main St

Boise, ID 83702

mindlab20250820@gmail.com

© 2026 MIND Lab