Career & Research Impact

Presentations & Conferences

(Highlight talks, conference papers, invited presentations)

  • Presented Leveraging Open Language Models to Improve Healthcare Predictive Analytics for Underrepresented Populations at Bristol Myers Squibb (BMS) Science Scholars Symposium (2024). 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 Montclair State University symposium, highlighting AI-driven compliance frameworks for healthcare applications. (2025, with Prof. Raina Samuel) project-poster

  • Presented at New Jersey Big Data Alliance Symposium, 2024 – ML-GIS Research on Solar Panel Detection & Energy Estimation project-poster

  • Presented at CESAC Symposium 2023 – Presented Findings on Virtual Reality in STEM Education


AI & Machine Learning Research

(research, methodologies, impact)

🔹 Graph Neural Networks & AI for Drug Discovery (Data Science Lab - AMIA 2025 Submission)

  • 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)

Graduate Research Assistant, Montclair State University (2023-Present)

🔹 School of Computing

  • Developed NLP-driven entity harmonization & knowledge graphs, improving pharma research data processing.

  • Worked on topic modeling & trend analytics, processing millions of records from scientific literature, vendor reports, and internal R&D data.

  • Improved document retrieval efficiency by 40%, enhancing AI-driven insights in pharmaceutical R&D

🔹 Data Science Team website

  • Developed NLP-driven entity harmonization & knowledge graphs, improving pharma research data processing.

  • Worked on topic modeling & trend analytics, processing millions of records from scientific literature, vendor reports, and internal R&D data.

  • Improved document retrieval efficiency by 40%, enhancing AI-driven insights in pharmaceutical R&D

🔹 Hu-Au Virtual Reality Lab 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 Research (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.

🔹 Port Authority of NY & NJ – Data Analyst Intern (2024)

  • Developed real-time data visualization dashboards for infrastructure analytics, enhancing operational efficiency.

  • Conducted predictive modeling to optimize transportation and logistics planning.

🔹 Dozie & Dozie’s Pharmaceuticals – Data Analyst (2019-2023)

  • Led healthcare data analysis, optimizing inventory management and operational efficiency using AI-driven insights.

  • Designed business intelligence dashboards, streamlining reporting and strategic decision-making.


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)