Mithil Guru

I'm a data analyst at Fighting Illini Athletics and a researcher with the Human-Computer Integration Lab at the University of Chicago.

Through my work, I explore how to integrate new sensing and feedback modalities to enhance daily living. My research interests lie in human-computer interaction, health sensing, and haptics.

Experience

Research Collaborator

Human Computer Integration Lab - University of Chicago

Exploring novel sensing and feedback systems with muscle stimulation for physical skill acquisition and assistance. Advisor: Professor Pedro Lopes.

Data Analyst

Fighting Illini Athletics

Unifying athlete performance, health, and operations into systems that help teams make better decisions.

Research Assistant

Center for Health Informatics - University of Illinois at Urbana-Champaign

Mapped public health information spread across World Health Organization social media networks to advise on communication strategy. Advisors: Dr. Ian Brooks, WHO Communications.

Data Analyst Intern

SHIELD Illinois

Used epidemiological modeling to support campus testing frequency decisions for COVID-19 response.

Research Assistant

Kinesmetrics Lab - University of Illinois at Urbana-Champaign

Modeled clinical health data to classify osteoporosis risk and surface predictors of skeletal decline in underrepresented populations.

Publications

Modeling Perceived Force of Electrical Muscle Stimulation to Improve User's Recall

Mithil Guruvugari, Romain Nith, and Pedro Lopes

In Proceedings of CHI 2026

Demonstrating Adaptive Electrical Muscle Stimulation for Improved Muscle Memory

Siya Choudhary, Romain Nith, Jas Brooks, Yun Ho, Mithil Guruvugari, and Pedro Lopes

In Proceedings of CHI 2025

Projects

Intervention with Electrical Muscle Stimulation

Developed an Apple Watch application with on-device ML to detect dermatillomania behavior. Deliver and evaluate real-time electrical muscle stimulation intervention in a participatory study.

Personal Informatics

Logged biometric data from fitness tracker (activity, sleep, vitals), meal data (macronutrients, micronutrients), mood data (RULER mood meter), and productivity data (task completion, time blocking). Trained a regressor to predict mood and energy levels, enabling behavior change for improved focus.

Athlete Strength Test Analysis

Analyzed Illinois Olympic Sports strength test data collected on the Hawkin Dynamics Platform. Performed correlation and regression analysis using scikit-learn in Python to select key variables influencing test performance, helping identify overtraining in athletes