Career & Research Impact
Presentations & Conferences
(Highlight talks, conference papers, invited presentations)
Presented Optimizing Large Language Models (LLMs) for ICU Readmission Prediction, for Underrepresented Populations at Bristol Myers Squibb (BMS) Science Scholars Symposium (2024/25). project-presentation
Developed large-scale AI models leveraging NLP to improve predictive analytics for underrepresented populations in healthcare decision-making.
Led an industry-focused AI training session at BMS, introducing prompt engineering techniques for AI-driven healthcare analytics.
Presented Automated Regulatory Classification of Mobile Medical Apps at IEEE 38th CBMS Conference in Madrid, Spain (June 2025), showcasing NLP pipelines for detecting compliance issues in mobile apps. certificate-of-participation
Presented Automated Regulatory Classification of Mobile Medical Apps at Montclair State University symposium, highlighting AI-driven compliance frameworks for healthcare applications. (2024/25, with Prof. Raina Samuel) project-poster
Presented ML-GIS Research on Solar Panel Detection & Energy Estimation at New Jersey Big Data Alliance Symposium. (March 2024) project-poster
Presented Presented Findings on Virtual Reality in STEM Education at Clean Energy and Sustainability Analytics Center (CESAC) Symposium. (October 2023)
AI & Machine Learning Research
(research, methodologies, impact)
🔹 Graph Neural Networks & AI for Drug Discovery (Data Science Lab - AMIA 2025 Conference) paper
Used biomedical knowledge graphs & Graph Neural Networks (GNNs) to improve drug-drug interaction prediction.
Integrated biomedical ontologies & structured pharma datasets to enhance AI-driven clinical research.
🔹 Automated Regulatory Classification of Mobile Medical Apps (School of Computing, IEEE - CBMS Conference 2025 Paper Acceptance) paper
Built an NLP-based compliance framework that classifies mobile medical apps based on FDA & FTC regulatory risk, improving oversight of AI-driven health applications..
Integrated spatially aware feature representations to enhance generalization in ML models.
Defined a novel mathematical framework for integrating domain knowledge into ML pipelines, optimizing model explainability.
🔹 Machine Learning & GIS for Environmental Policy (EPA & CESAC Research, 2023) project-poster
Built ML & GIS models to analyze Brownfield funding allocation & clustering patterns.
Applied Random Forest (44% variance explained), Moran’s I, and Spatial Error Models (SEM) to study geographic disparities in environmental funding.
🔹 Virtual Reality & AI for STEM Education (Montclair State University – Virtual Reality for Education Lab, 2023) website
Contributed to “The Human Brain Time”, a fully immersive VR application for neuroanatomy education, now deployed on Meta Quest App Lab, expanding access to interactive STEM learning.
Career Experience - Applied Research & Data Science
Career Experience - Applied Research & Data Science
(Industry work, and real-world applications of AI)
🔹 Applied Machine Learning Researcher, Montclair State University (2024-Present) - Hao Liu Data Science Lab website
Improved diagnostic predictions by developing a multimodal healthcare analytics pipeline that integrated EHR records with clinical notes using NLP, and data mining techniques; featured on MSU’s Data Science Lab website.
Enabled scalable analysis and model deployment by structuring healthcare data pipelines across hybrid warehouse/lake architectures using SQL, NoSQL, and JSON
Accelerated data transformation and insight generation by orchestrating distributed processing workflows in Spark and Snowflake.
Achieved 94% accuracy in comorbidity risk classification using interpretable ML models (SHAP, LIME), supporting transparent, cross-functional decision-making for clinical stakeholders.
🔹 Graduate Researcher - School of Computing, Montclair State University (2023-Present)
Built automated data pipelines using Python and Airflow to ingest 1,400+ medical app descriptions and over 220,000 user reviews, powering large-scale regulatory compliance analysis.
Applied Spark-based classification workflows with Scala to process high-volume data; implemented drift detection scripts to track schema and metadata shifts as app ecosystems evolved.
Achieved 85% accuracy in app compliance prediction under HIPAA, FTC, and FDA standards by training NLP models with BERT, spaCy, and NLTK, reducing manual audit workload.
Enhanced monitoring precision by 30% through user sentiment analysis with VADER and TextBlob, surfacing latent regulatory red flags.
Integrated Snowflake and AWS Glue (including Glue Data Catalog) to automate metadata tagging and streamline schema tracking across classification runs.
🔹 Hu-Au Virtual Reality Lab (2023-2024) website
Guided students in VR development & AI integration, helping them understand 3D modeling, interactive simulation design, and AI-driven learning environments.
Led technical training sessions on Unity, C#, and Python for VR applications, bridging AI & virtual learning technology.
Collaborated with faculty to expand research initiatives, ensuring projects align with educational technology advancements and funding opportunities.
🔹 Clean Energy Sustainability and Analytics Center (2023-2024)
Mentored undergraduate students & new research assistants, guiding them through GIS data preprocessing, ML model development, and environmental policy applications.
Led team discussions & technical workshops on spatial machine learning, geostatistical modeling, and energy forecasting techniques.
Assisted in writing & reviewing research proposals, ensuring projects aligned with policy impact and scientific rigor.
🔹 Bristol Myers Squibb Science Scholars (2024-Present)
Led research on open language models for predictive healthcare analytics, mentoring students and collaborating with industry professionals.
Presented research findings to BMS leadership, healthcare researchers, and data science professionals.
🔹 Data Analyst - Port Authority of New York & New Jersey (2024)
Automated analytics for 250K+ EV charging records by developing robust ETL workflows in Python and SQL, integrating MySQL data with AWS S3 and Redshift for daily operational reporting.
Forecasted charging demand and detected anomaly-driven downtime spikes (>20%) using predictive models built with PySpark, informing proactive maintenance planning.
Developed interactive dashboards in Tableau visualizing station uptime, fault trends, and site-level reliability, used by infrastructure teams for performance reviews and supporting business strategies.
Improved pipeline robustness by 30% through SQL tuning and data validation checks that flagged missing values, schema drift, and integrity issues.
Supported scalable, event-driven reporting aligned with core business strategies by integrating REST APIs with AWS Lambda and Glue as the EV network expanded across New York and New Jersey operations.
🔹 Data Analyst - Dozie & Dozie’s Pharmaceuticals (2019-2023)
Analyzed 100K+ patient records using SQL to uncover patterns in treatment outcomes, regional disease trends, and demographics, informing outreach and strategy across 30+ partner institutions.
Recovered ~$1.3M in unpaid claims (~85% recovery) by deploying statistical recovery models in Python and visualizing receivables through dynamic Power BI dashboards hosted on AWS.
Designed and implemented claims reporting frameworks that improved transparency and process improvement across healthcare partners, driving a 27% increase in revenue while maintaining regulatory compliance.
Delivered actionable insights to executive and partner teams, aligning financial recovery, patient outcomes, and public health priorities into one data-driven strategy.
Awards & Achievements
(Competitive recognition, honor societies)
Winner, RAISE 2025 – "Our Future With AI: Utopian or Dystopian?" (AI ethics & policy challenge.) LinkedIn post
Alpha Epsilon Lambda Honor Society (Top 5% of Graduate Students at Montclair State University.)
President & Founder, NextGen Tech Thinkers Club (MSU), a student-led initiative fostering AI, data science, and emerging technologies discussions.
Featured, MSU Communications for exemplary internship and research
Tri-Alpha Honor Society (Delta Chi Chapter, MSU)
