Hien Van Nguyen

Short Bio

Dr. Hien Van Nguyen is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Houston. His research lies at the intersection of artificial intelligence, computer vision, and biomedical image analysis. Dr. Nguyen has published over 100 peer-reviewed articles and received 12 U.S. patents. Before his tenure at the University of Houston, Dr. Nguyen served as a research scientist at Siemens Corporate Research in Princeton and later as a senior scientist at UberATG's autonomous driving department. His work has been recognized with research awards from prestigious institutions such as the National Science Foundation and the National Institutes of Health. Dr. Nguyen’s research has received the Best Poster Paper award at the 2023 International Renal Pathology Conference and a nomination for the best poster award at the 2024 International Symposium on Biomedical Imaging. He is a senior membership in the National Academy of Inventors and an associate editor for Elsevier’s journal, Computerized Medical Imaging and Graphics.

Hien Van Nguyen

Associate Professor

Phone:

713-743-8615

Email:

hvnguy35@central.uh.edu

Address:

4226 Martin Luther King Boulevard
Houston, TX 77204-4005

Google Scholar:

https://tinyurl.com/2a8crzvn

EDUCATION

2008-2013

Ph.D.

UNIVERSITY OF MARYLAND, COLLEGE PARK

My doctoral thesis focused on learning sparse and adaptive representations for multimodal classification, under the guidance of Dr. Rama Chellappa. I received the Goldhaber Award from UMD Graduate School, an ECCV travel grant, and participated in the CVPR Doctoral Consortium Program.

2003-2007

NATIONAL UNIVERSITY OF SINGAPORE

I received the prestigious four-year Singapore Ministry of Foreign Affairs Scholarship, presented by Singapore's current Prime Minister Lawrence Wong. Additionally, I was awarded scholarships from the Japanese Business Association and the University of Miyazaki for my excellent academic performance.

Bachelor's Degree

1999-2002

High School Diploma

LE QUY DON HIGH SCHOOL FOR THE GIFTED

I majored in Math and Physics and won first prize in the Physics Competition of Danang City, Vietnam.

EXPERIENCE

2016-Present

UNIVERSITY OF HOUSTON

Associate Professor

Lead diverse teams, including international students and physicians, to develop advanced AI models for kidney and lung disease diagnostics and treatments. Instrumental in securing over $12 million in research grants, playing a critical role in proposal writing, budget management, and project execution. Delivered high-impact publications, planned and supervised AI workshops at major conferences, and managed events hosting over 200 attendees.

2015-2016

Senior Scientist

UBER ADVANCED TECHNOLOGIES GROUP

Worked with a team of talented engineers to develop deep learning algorithms for Uber Advanced Technologies' autonomous driving, enabling vehicles to navigate highways at speeds up to 65 mph. Ensured effective communication and synergy between computer vision and machine learning teams.

2013-2015

Scientist

SIEMENS CORPORATE RESEARCH

Spearheaded deep learning initiatives at Siemens, co-holding its earliest deep learning patents, and invented network sparsification algorithms to reduce 3D computed tomography landmark detection error and improve runtime speed. Developed methods for predicting cardiac stent types and modeling aorta shapes.

FUNDED BY

FUNDING

National Institute of Diabetes and Digestive and Kidney Diseases

National Institute of Neurological Disorders and Stroke

National Institute of General Medical Sciences

RESEARCH HIGHLIGHTS

Doctor-AI Collaborative Diagnosis

This project, “AI-Doctor Collaborative Medical Diagnosis,” began receiving NCI funds in 2022. It combines novel AI algorithms, gaze monitoring software, and design principles to help doctors minimize diagnostic errors due to cognitive and perceptual biases. The project aims to increase diagnostic accuracy, save lives, reduce missed cancer diagnoses, and improve public health.

Convergent AI for Breast Cancer

Breast cancer remains a leading cause of death among women in the US, with inconsistent biopsy rates due to variability in mammographic reporting. This project aims to develop iBRISK, an AI-based risk assessment system integrating imaging and clinical data to improve cancer risk evaluation. If successful, this tool will help radiologists and oncologists make more informed biopsy decisions, reducing unnecessary procedures and patient anxiety.

Objective Diagnosis of Lupus Nephritis

Up to 80% of children and 60% of adults with systemic lupus erythematosus develop nephritis, with a significant percentage progressing to end-stage renal disease. To improve diagnosis, this project uses computer vision and deep learning to create a neural network that matches expert renal pathologists in identifying and classifying lupus nephritis. This system aims to provide reliable, reproducible classifications to enhance patient management and outcomes.

Quantitative Profiling of Cellular Alterations

This project aims to develop a Comprehensive Brain Cellular Alteration Profiling Toolkit (CBAT) to enable simultaneous, detailed profiling of brain cell types and their pathological states across whole brain sections. CBAT aims to provide deeper insights into cellular alterations, reduce experimental costs, and support systems-level investigations for better treatment of brain pathologies such as traumatic brain injuries.

Integration of Cellular Function and Molecular Profiles

This project aims to address the variability in patient responses to immunotherapy by mapping the complexity of T-cell products, linking function to molecular profiles at single-cell resolution. This platform will enhance the biomanufacturing of T-cell infusion products and the engineering of more potent immune cells, significantly impacting immunotherapy.

MEET THE TEAM

Ph.D. Student

Samira Zare

Ph.D. Student

Akash Awasthi

Ph.D. Student

Huy Quoc Vo

Ph.D. Student

Mai-Anh Vu

Ph.D. Student

Son Thai Ly

Ph.D. Student

Hung Quoc Vo

Ph.D. Student

Mohammad Daouk

SERVICES

NEWS

ISBI BEST POSTER FINALIST

$3 MILLION NIH FUNDING

Our paper entitled "Decoding Radiologists' Intentions: A Novel System for Accurate Region Identification in Chest X-ray Image Analysis", authored by Akash Awasthi, was nominated for best poster award at 2024 IEEE International Symposium on Biomedical Imaging.

Our project entitled "Objective Classification of Lupus Nephritis" was funded by the National Institute of Diabetes and Digestive and Kidney Diseases. The project goal is to provide accurate and objective lupus nephritis diagnosis using AI.

SUMMER RESEARCH FELLOWS

Three students from our lab won UH Summer Undergraduate Research Fellowships to work on virtual reality, large language models, and AI-powered medical diagnosis.

LOCATION