2026
New NYS Center of Excellence grant
$50K for intelligent robotic solutions for soft-tissue processing in advanced biomanufacturing.
People · AI · Robots · Systems
Intelligent systems that understand, interact with, and adapt to humans and the physical world.
We integrate artificial intelligence, robotics, human behavior and physiology, and physics-based modeling to create autonomous and interactive systems that are adaptive, interpretable, and safe.
Research landscape from recent lab publications
Human–Robot Interaction
Human Performance
Machine Learning
Neuroergonomics
Robotics
Human–AI Teaming
Physiological Modeling
Variable Stiffness
Gaze
Human–Swarm Interaction
Rehabilitation
Motor Control
Autonomy
Wearable Sensing
Tactile Sensing
Fatigue
Reinforcement Learning
Soft-Tissue Interaction
Research
Five connected research directions
Our work spans human sensing and modeling, human-inspired intelligence, teaming with autonomous systems, and the design of intelligent robotic systems.
Neuroergonomics & Cognitive State Modeling
Neurophysiological sensing and computational models of workload, attention, situational awareness, trust, motor control, and cognitive state.
Explore →AI for Human Health & Performance Modeling
AI and physiological modeling for mobility, fatigue, rehabilitation, training, hiking and traversal performance, and health monitoring.
Explore →Human-Inspired AI & Human-in-the-Loop Learning
AI methods informed by human attention, gaze, behavior, physiological feedback, and context-aware assistance.
Explore →Human–AI & Human–Robot Teaming
Adaptive collaboration among people, robots, and autonomous agents—from human–swarm interaction to physical HRI.
Explore →Robotic Design & Industrial Automation
Compliant mechanisms, tactile sensing, manipulation, sim-to-real transfer, soft-body interaction, and intelligent automation.
Explore →Featured Work
Current research in action
Selected projects show how the lab connects fundamental modeling and learning with real human and robotic systems.
Highlights
Recent activity
2026
SUNY–IBM AI Research Alliance award
$100K to develop expressive foundation models for physiological time series using stochastic intrinsic-mode representations.
2026
New IEEE TBME publication
Adaptive Hiking-Time Prediction Through State-Dependent Energy Regulation.
2026
Congratulations Dr. Krushang Gabani
Krushang successfully defended his PhD in July 2026 and joined Amazon Frontier AI & Robotics.
Research Support
Supported by federal, state, and industry partners
Join HILS
Research opportunities are available.
We currently have a funded PhD opening, multiple M.S. research opportunities, and ongoing opportunities for undergraduate researchers.