Exploring Health Through Data, Science and Innovation

Health Digital Twin Mobile App | 2 IEEE Publications | IEEE ICHI Presenter | Awards

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— Lead Research Project

Bio360AI: Health Digital Twin Framework

Bio360AI is a comprehensive Health Digital Twin architecture that unifies longitudinal multi-modal datasets with predictive computational engines.

Multimodal Cohort & Domain Integration

Predictive Modeling & Clinical Impact

Integrates wearable, laboratory, lifestyle, family-history, and clinical data across MIMIC-IV cohorts to evaluate six physiological domains: cardiovascular, respiratory, metabolic, strength and functional health, lifestyle balance, and cognitive wellness.

Generates personalized health scores, risk factors, lifestyle simulations, treatment-response comparisons, and physiological projections at 5, 10, 15, and 20 years. Supported by two IEEE publications, workshop/poster presentations, a mobile app, and 100+ waitlist sign-ups.

• 5 Research Projects • Project Output

Bio360AI Health Digital Twin

Bio360AI integrates wearable, laboratory, lifestyle, family-history, and longitudinal clinical data into a personalized health model. The framework uses MIMIC-IV data to develop comparable patient cohorts and evaluate six health domains:

Cardiovascular Health

Respiratory Health

Metabolic Health

Longitudinal tracking of hemodynamic stability, microvascular parameters, and cardiac strain profiles over extended clinical horizons.

Continuous pulmonary response modeling evaluating gas exchange, oxygenation dynamics, and ventilator cohort outcomes.

Integration of laboratory panel series, glycemic control signals, and multi-system energetic biomarker trajectories.

Strength & Functional Health

Lifestyle Balance

Cognitive Wellness

Objective mobility monitoring, musculoskeletal endurance indices, and recovery velocity analysis across age cohorts.

Harmonization of wearable activity telemetry, sleep architecture metrics, and self-reported stress indicators.

Assessment of neuro-cognitive trends, longitudinal reaction variability, and early degenerative risk signature extraction.

+ Investigative Work

Featured Research Projects

UMD School of Medicine

UMBC RISE Lab

Sun2Water Purification

Analysis of tacrolimus, prednisone, mycophenolate mofetil, fingolimod, and rapamycin at Days 3, 7, and 30 using microbiome, metabolomic, transcriptomic, and immune data via PCA, SparCC, heatmaps, mixOmics, longitudinal comparisons, and untreated controls.

Contribution to LLM workflows that detect software vulnerabilities, identify root causes, generate targeted code fixes, and rigorously evaluate whether automated fixes resolve defect patterns.

Solar-powered purification system using multi-stage filtration, UV disinfection, water-quality monitoring, and automated dispensing producing 300 to 800 L/day. Recognized in National Top 50 from 1,200+ submissions with $2,000+ funding.

BrainBoost Alzheimer's Study

/ Research in Progress

Early Sepsis and AKI Modeling

A 30-day study with 20+ participants living with Alzheimer’s disease using Muse EEG to monitor alpha and theta brainwave activity alongside cognitive testing, exercise comparisons, and individualized reports.

Analysis of respiratory-rate increases, tachycardia, mean arterial pressure drift, narrowing pulse pressure, oxygen saturation, and delayed creatinine changes using PhysioNet and MIMIC-IV datasets.

Read on IEEE Xplore

■ Peer-Reviewed Literature

IEEE Publications

Bio360: A Multimodal Framework for Health Digital Twin Modeling and Early Physiological Drift Detection

Bio360: From Multimodal Data to Next-Generation Health Analytics

Presents computational methodologies for continuous multimodal integration, evaluating subtle multi-system drift signals to predict health trajectories early.

Details the data pipeline, clinical feature extraction, and analytical algorithms transforming physiological streams into actionable health risk projections.

✱ Conference Symposia

▸ Technical Competencies

Presentations & Speeches

Research Methods & Tools

Selected as an IEEE ICHI 2026 presenter. Featured workshop speaker and poster presenter for Bio360AI health digital twin modeling across regional and national conferences.

Multi-omics analytics (PCA, SparCC, mixOmics, heatmaps), EHR cohort modeling (MIMIC-IV, PhysioNet), Muse EEG analysis, LLM defect detection workflows, and sustainable UV engineering.