• Grants

    1. NSF #2219614 (PI) Collaborative Research: CISE-MSI: DP: IIS: Event Detection and Knowledge Extraction via Learning and Causality Analysis for Resilience Emergency Response, $320,368(Meharry) / $600,000 (Total), 2023-2025, National Science Foundation
    2. NSF #2302274 (PI) Excellence in Research: Harnessing Big Data and Domain Knowledge to Advance Deep Learning for Interpretable Cell Quantitation, $599,995, 2023-2026, National Science Foundation
    3. Meharry (PI) Quantitating Biological Cells from Microscopy Images using Deep Learning, $15,000, 2023, Meharry Medical College
    4. NIH #3U54MD007586-37S3 (Co-PI) Supplement: Administrative Supplements for Ethical Considerations in Artificial Intelligence and Machine Learning (AI/ML) at NIMHD-Funded Research Centers in Minority Institutions (RCMI), $218,250, 2023-2024, National Institutes of Health
    5. NSF (PI) REU Supplement: CISE-MSI: DP: IIS: Event Detection and Knowledge Extraction via Learning and Causality Analysis for Resilience Emergency Response, $16,000, 2023-2024, National Science Foundation

Research

COVID-19 human-body response stages

We explore physiological signs in COVID-19 patients and see human responses in each symptom stage of COVID-19 such as mild, medium, or severe. This will lead to greatly resources saving for hospitals as they can hospitalize severe patients while the mild patients can still be taken care of remotely.

Opioid Relapse Prediction

Opioid addiction poses severe threats to public health, causing many deaths and massive social disruption. It is therefore critical to be able to predict whether or not a recovering opioid addict will relapse. Our goal is to model Opioid relapse prediction and then design a personalized intervention plan.

  • Publications

    Can be seen more completely at Google Scholar
    Below are some examples:
    • Long Nguyen, Muzhe Guo, Hongfei Du, and Fang Jin. When Patients Recover From COVID-19: Data-Driven Insights From Wearable Technologies, Frontiers in Big Data, 2022. Accepted. PDF

    • H Abu-gellban, L Nguyen, F Jin Gfdlecg: Pac classification for ecg signals using gradient features and deep learning, Advances in Data Science and Information Engineering

    • HL Nguyen, Z Pan, H Abu-Gellban, Y Zhang. Google trends analysis of covid-19 pandemic, 2020 IEEE International Conference on Big Data (Big Data)

    • Zhou Yang, Long Nguyen, and Fang Jin. Opioid Relapse Prediction with GAN, the 2019 IEEE/ACM International Conference on Social Networks Analysis and Mining, ASONAM 2019. August, 2019. Vancouver, Canada. Acceptance rate 14%.

CAREER Resources