Hao Liu
Assistant Professor
School of Computing
Montclair State University
liuha at montclair dot edu
CCIS 227E
School of Computing
Montclair State University
Montclair, NJ 07043
My work seeks to leverage innovations in artificial intelligence into knowledge discovery, representation, and computation from biomedical/clinical literature and Electronic Health Records(EHRs). My research interests include clinical informatics, natural language processing, machine learning, data mining, knowledge representation, and ontology engineering. I am passionate about AI in Healthcare research.
I was a Postdoc Research Scientist in the Department of Biomedical Informatics at Columbia University. I received my Ph.D. degree in Computer Science from New Jersey Institute of Technology (NJIT), co-advised by Dr. Yehoshua Perl and Dr. James Geller. My PhD research focused on developing machine learning algorithms for biomedical ontology engineering, mainly focused on ontology enrichment and quality assurance. I graduated with a M.S. degree in Electrical Engineering from Columbia University, NY. I have a B.S. degree in Electrical & Computer Engineering from New York Institute of Technology, NY.
News
Nov 5, 2024 | Our paper was accepted to the IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2024 workshop! |
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Oct 22, 2024 | I am happy to share that my advisee, Shibbir Ahmed Arif, has been awarded a Student-Led Research, Scholarship, and Creative Activities (SL-RSCA) Grant for his innovative research project, “Accelerating Patient Screening for Clinical Trials using Large Language Model Prompting.”
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Sep 12, 2024 | We are delighted to kick off the first meeting of Data Science Lab for Fall 2024 semester at Montclair State University! Our lab attracted a diverse group of students, all eager to contribute to cutting-edge research at the intersection of data science and healthcare. Students will work on projects that explore the intricate relationships within Social Determinants of Health (SoDH), aiming to uncover insights that could reshape public health strategies. The team will also delve into advanced medical image classification techniques, potentially revolutionizing diagnostic processes. Furthermore, the lab plans to harness the power of knowledge graphs to enhance healthcare ontologies, and investigate innovative applications of Large Language Models (LLMs) in clinical trial patient matching. This blend of artificial intelligence, data analytics, and healthcare expertise positions Montclair State University at the forefront of data-driven medical research, with the potential to improve patient outcomes and streamline healthcare processes. |
Jul 23, 2024 | Our paper won the best student paper award in the 15th International Conference on Information, Intelligence, Systems and Applications (IISA2024)! |
Jun 17, 2024 | Our paper was accepted to the 15th International Conference on Information, Intelligence, Systems and Applications (IISA2024)! |
Jun 5, 2024 | I serve on the Program Committee for The 2024 International Workshop on AI Applications in Public Health and Social Services (AI-PHSS 2024) for AIME 2024. |
May 24, 2024 | I am admitted as a member of the Association for Computing Machinery (ACM)! |
May 15, 2024 | I will serve on the Graduate Council of Montclair State University for AY24-25! |
Apr 23, 2024 | I am delighted to announce that my student Ernest Chianumba was invited to join the BMS Science Scholars program at Montclair State University. This program aims to benefit scholars through supporting the development of their research skills and professional development in the pharmaceutical industry.
Please join me in congratulating Ernest Chianumba! Happy to share this announcement with all of you! |
Apr 19, 2024 | We are delighted to announce that our students Isabele, Anand, Ramy and Ola of Team Machine Minds won the 1st Prize in the Graduate Track at the nationwide RAISE-2024 competition hosted by Rutgers University, NJ. Details are as follows.
Our students put in immense efforts on this project & we were happy to guide them through their journey. Please join us in congratulating Team Machine Minds! |
Mar 22, 2024 | Our software demo was accepted to IEEE/ACM CHASE 2024! |
Mar 14, 2024 | Our paper was accepted to IEEE ICHI 2024! |
Dec 5, 2023 | Our paper was accepted to HEALTHINF 2024! |
Nov 10, 2023 | Our paper was accepted to AIBH@IEEE BIBM2023! |
Oct 18, 2023 | I will serve as a publicity chair of IEEE/ACM CHASE 2024. |
Oct 13, 2023 | I will serve on the program committee of IEEE ICHI'2024 (The 12th IEEE International Conference on Healthcare Informatics). |
Feb 20, 2023 | Our paper “How Good is ChatGPT for Medication Evidence Synthesis?” was accepted by Medical Informatics Europe 2023! |
Jan 11, 2023 | I will serve as a program committee of IEEE ICHI'2023 (The Eleventh IEEE International Conference on Healthcare Informatics). |
Dec 17, 2022 | Our paper “Can Race-sensitive Biomedical Embeddings Improve Healthcare Predictive Models?” was accepted in AMIA 2023 Informatics Summit! |
Nov 1, 2022 | Our paper “Ontology-based categorization of clinical studies by their conditions” was published in Journal of Biomedical Informatics(IF: 8.0)! |
Oct 7, 2022 | Congratulations to Bridget Zelin, a high school student I mentored, for her acceptance in AMIA 2022 High School Scholar Submission |
Apr 12, 2022 | The LitCoin Natural Language Processing (NLP) Challenge
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Mar 29, 2022 | I was invited to give a seminar talk titled “NLP-based knowledge sharing and evidence retrieval of clinical studies” at the College of Engineering & Computing Sciences in New York Institute of Technology, March 29, 2022 |
Mar 9, 2022 | I was invited to give a guest lecture titled “NLP-based quality assurance of ontologies and knowledge sharing of clinical trials” for HINF 5016: Natural Language Processing in Health at Weill Cornell Medicine, March 9, 2022 |
May 13, 2021 | Congratulations to Jane Pan, an undergraduate student I co-mentored, for winning the First Place in the Inaugural COVID Information Commons (CIC) Undergraduate Student Paper Challenge for her paper "Contradiction Detection of COVID-19 Randomized Controlled Trials via BERT Language Models." |