Research portfolio

Projects that connect AI, sensing, and human behavior.

My work spans virtual sensor generation, multimodal learning, wearable computing, and inclusive human-centered systems. These projects share one goal: making behavioral AI more scalable, realistic, and useful.

AgentSense pipeline: an LLM generates personalities, schedules, and routines that embodied agents execute in simulated homes instrumented with motion, door, and object sensors
Embodied AIAAAI 2026

AgentSense

Smart-home sensor data, generated by agents that live there.

LLMs create diverse personas and routines; embodied agents execute them in an extended VirtualHome simulator instrumented with ambient sensors. Pretraining on this data improves recognition, especially when real data is limited.

5 real datasetsPrivacy by design
Paper Code
IMUGPT 2.0 language-to-sensor pipeline
Cross-modality generationIMWUT 2024

IMUGPT 2.0

Describe an activity; generate wearable motion data.

A language-based pipeline expands short activity names into diverse descriptions, synthesizes motion, and converts it into virtual on-body accelerometer signals for training HAR models.

Paper Code
Wearable IMU emotion recognition system diagram
Affective computingHASCA 2024

Emotion recognition on the go

Personalized emotion recognition using wearable IMUs, with virtual motion data supporting model pretraining and adaptation.

Paper
Smart rings used for fingerspelling recognition
Accessible interactionASSETS 2023

FingerSpeller

Camera-free American Sign Language fingerspelling recognition and text entry using instrumented smart rings.

Paper Data
Wheelchair transportation mode detection illustration
Inclusive sensingISWC 2024

Wheelchair transportation sensing

Comparing data-collection strategies for transportation-mode detection with wheelchair users, recognized with a Best Paper nomination.

Paper