About Me
Hello! I’m Thao, currently a first-year Ph.D. student in the Department of Computer Science at the University of Illinois at Urbana Champaign (UIUC). I am fortunate to be advised by Prof. Heng Ji.
I completed my B.S. degree in Biomedical Engineering at Hanoi University of Science and Technology (HUST) in late 2020. After graduating, I spent a year interning at VinBigdata’s Medical Image Processing Department. Following this, I joined the VinUni-Illinois Smart Health Center (VISHC), where my focus lies in deep learning-based biosignal processing. I am passionate about leveraging advanced computational techniques to accelerate applications in healthcare.
Research interests
My research interests revolve around the application of natural language processing (NLP) and graph neural networks (GNN) to accelerate advancements in AI for drug discovery. Specifically, I am drawn to the following areas:
- Foundation model for molecular representation
- Synthesizable molecule generation
- Molecular structure-properties relationship mining
- Physic-informed AI for drug discovery
- Interpretable AI for high fidelity molecular property prediction
- Autonomous molecular design and synthesis
News
Ph.D. student @ UIUC
Aug - 2023 Present
Started Ph.D in CS at UIUC, joined BLENDER lab.
RA @ VISHC
Jan 2022 - Jun 2023
Started working at VISHC as a research assistant on the ECG signal analysis project.
Internship @ VinBidata
Jan 2021 - Dec 2022
Started working at Medical Image Processing Department - VinBigdata JSC.
Undergrad
Sep 20216 - Dec 2020
Received BSc degree in Biomedical Engineering from HUST.
Publications
[8] Thao Nguyen, Kuan-Hao Huang, Ge Liu, Martin D. Burke, Ying Diao, Heng Ji. FARM: Functional Group-Aware Representations for Small Molecules. preprint arXiv:2410.02082, 2024.
[7] Thao Nguyen, Tiara Torres-Flores, Changhyun Hwang, Carl Edwards, Ying Diao, Heng Ji. GLaD: Synergizing Molecular Graphs and Language Descriptors for Enhanced Power Conversion Efficiency Prediction in Organic Photovoltaic Devices. The 33rd ACM International Conference on Information and Knowledge Management, 2024.
[6] Dat T. Ngo, Thao Nguyen, Hieu T. Nguyen, Dung B. Nguyen, Ha Q. Nguyen, Hieu H. Pham. Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices. 2023 IEEE Statistical Signal Processing Workshop (SSP), 2023.
[5] Thao Nguyen, Hieu H. Pham, Khiem H. Le, Anh Tu Nguyen, Tien Thanh, Cuong Do. Detecting COVID-19 from digitized ECG printouts using 1D convolutional neural networks. PLOS ONE, 2022.
[4] Thao Nguyen, Tam M. Vo, Thang V. Nguyen, Hieu H. Pham, Ha Q. Nguyen. Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese. PLOS ONE, 2022.
[3] Thao Nguyen, Anh Tu Nguyen, Khiem H. Le, Hieu H. Pham, Cuong Do. A novel deep learning-based approach for sleep apnea detection using single-lead ECG signals. APSIPA ASC - 2022, 2022.
[2] Khiem H. Le, Hieu H. Pham, Thao Nguyen, Tu A. Nguyen, Tien N. Thanh, Cuong Do. LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification. Biomedical Signal Processing and Control, 2022.
[1] Khiem H. Le, Hieu H. Pham, Thao Nguyen, Tu A. Nguyen, Cuong Do. Enhancing deep learning based 3-lead ECG classification with heartbeat counting and demographic data integration. IECBES 2022, 2022.
A Little More About Me
Alongside my interests in research work some of my other interests and hobbies are:
- Table tennis
- Traveling
- Photography
- Drawing
- Graphic design