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Ming Huang, PhD

Associate Professor

Department of Health Data Science and Artificial Intelligence

Contact

[email protected]

Ming Huang, PhD is an Associate Professor at the Center of Translational AI Excellence and Applications in Medicine (TEAM-AI) within McWilliams School of Biomedical Informatics at UTHealth Houston. Prior to joining UTHealth Houston on June 30, 2023, Dr. Huang held the position of Assistant Professor of Biomedical Informatics in the Department of Artificial Intelligence and Informatics at Mayo Clinic.

Dr. Huang's versatile background spans across computer science, health data science, and health science, endowing him with a wealth of educational training and extensive research experiences. Dr. Huang boasts profound expertise in the development and application of Artificial Intelligence (AI) and Data Mining methods to tackle significant and challenging problems in biomedicine.

Dr. Huang's primary research interest involves advancing Clinical and Translational Research in multiple healthcare domains, for example, mental health, consumer health, and telehealth. He is driven by a strong passion to contribute to healthcare, and his work has made contributions to multiple NIH-funded projects. Notably, he has led the AI and Natural Language Processing (NLP) efforts in an NIH R01 project focused on computational phenotyping and exploring the Social Determinants of Health (SDoH) related to mental health disorders. Additionally, Dr. Huang is serving as a site Principal Investigator (PI) in an NIH R34 project aimed at identifying social media users with vaping-related negative outcomes and the intention of quitting vaping for digital interventions.

Beyond his research pursuits, Dr. Huang actively engages in review and/or editorial services for federal institutions, prestigious journals, national and international conferences, and workshops such as NSF review panel, Lancet – Reg Health, JAMIA, JBI, AMIA, and ACL. He also served as the guest associate editor for Frontiers in AI and Frontiers in Big Data, and the publication chair for IEEE ICHI. Through his dedicated efforts and expertise, Dr. Huang intends to drive progress in the field of AI and healthcare, making a meaningful impact on the advancement of healthcare.

  • Tell us about your research center and/or what research you are currently working on?
    Our TEAM-AI center is dedicated to advancing the frontiers of translational AI and its transformative applications in medicine. My current research focuses on developing and deploying advanced AI, health data science, NLP, and informatics methods to revolutionize the conversion of complex clinical data into tangible, actionable insights and healthcare applications.
  • What type of student or Postdoctoral Fellow are you looking for to work in your center?
    We are looking for highly motivated Graduate Students and Postdoctoral Fellows with strong interests in AI and Health Informatics to join our center. The students and fellows will work closely with us to perform high-quality publishable research to develop innovative technological solutions and address challenging real-world problems in healthcare.

Education

  • PhD, Scientific Computation, University of Minnesota – Twin Cities, 2014
  • Graduate trainee, Biomedical Informatics and Computational Biology, University of Minnesota, 2008-2010
  • Graduate studies, Theoretical Physical Chemistry, Beijing Normal University, 2004-2007
  • Dual BSc, Computer Science and Applied Chemistry, Beijing Normal University, 2004

Areas of Expertise

  • Machine Learning and Deep Learning
  • Natural Language Processing and Large Language Models
  • Data Mining
  • Clinical and Translational Research
  • Patient-centered Care

Staff Support

Blanca Torres | 713-486-0114

 

Selected Publications:

  1. Ren Y, Wu Y, Fan JW, Khurana A, Fu S, Wu D, Liu H, Huang M*. Automatic uncovering of patient primary concerns in portal messages using a fusion framework of pretrained language models. Journal of the American Medical Informatics Association. 2024 Aug;31(8):1714-24
  2. Chen Z, Yang R, Fu S, Zong N, Liu H, Huang M*, Detecting reddit users with depression using a hybrid neural network SBERT-CNN, in IEEE 11th International Conference on Healthcare Informatics (ICHI), 2023 Jun 26
  3. Miller K, Kshatriya BS, Nunez NA, Resendez MG, Ryu E, Coombes BJ, Fu S, Frye MA, Biernacka JM, Huang M*, Wang Y*. Neural language models with distant supervision to identify major depressive disorder from clinical notes. in IEEE 11th International Conference on Healthcare Informatics (ICHI), 2023 Jun 26
  4. Wu D, Kasson E, Singh AK, Ren Y, Kaiser N, Huang M*, Cavazos-Rehg PA. Topics and sentiment surrounding vaping on Twitter and Reddit during the 2019 e-cigarette and vaping use–associated lung injury outbreak: comparative study. Journal of Medical Internet Research. 2022 Dec 13;24(12):e39460.
  5. Huang M, Fan J, Prigge J, Shah ND, Costello BA, Yao L. Characterizing patient-clinician communication in secure medical messages: retrospective study. Journal of Medical Internet Research. 2022 Jan 11;24(1):e17273.
  6. De A, Huang M, Feng T, Yue X, Yao L. Analyzing patient secure messages using a fast health care interoperability resources (FIHR)–based data model: development and topic modeling study. Journal of Medical Internet Research. 2021 Jul 30;23(7):e26770.
  7. Huang M, Zolnoori M, Balls-Berry JE, Brockman TA, Patten CA, Yao L. Technological innovations in disease management: Text mining US patent data from 1995 to 2017. Journal of Medical Internet Research. 2019 Apr 30;21(4):e13316.
  8. Li D, Huang M, Li X, Ruan Y, Yao L. MfeCNN: mixture feature embedding convolutional neural network for data mapping. IEEE Transactions on Nanobioscience. 2018 May 28;17(3):165-71.