Gilchan Park
Research Staff 3 Computational, Computation and Data Driven Discovery, Computational Science Initiative
Brookhaven National Laboratory
Computational Science Initiative
Bldg. 725
P.O. Box 5000
Upton, NY 11973-5000
(631) 344-6113
gpark@bnl.gov
Preferred Gender Pronouns (PGPs): He/Him
Gilchan Park’s primary research interests are computational semantics, and computational semantics and information extraction using natural language technologies. More specifically, he has been investigating how to improve machines’ understanding of text data by leveraging semantic relations in text. The research domains have ranged from information security and medical transcripts, and my current research focuses on information extraction from scientific literature via meaning-based models.
Expertise | Research | Education | Appointments | Publications
Expertise
- Natural Language Processing
- Ontological Semantic Processing
- Machine Learning
Research Activities
- Biological Information Extraction
- Q&A System Design for COVID-19
- Scientific Literature Mining for X-ray Absorption Spectroscopy (XAS)
Education
- Ph.D., Computer & Information Technology, Purdue University, West Lafayette, IN
- M.S., Computer & Information Technology, Purdue University, West Lafayette, IN
Professional Appointments
- 2018 - present, Research Staff 3, Center for Data-Driven Discovery, Computational Science Initiative, BNL
- 2018 - 2020, Postdoctoral Research Associate, Center for Data-Driven Discovery, Computational Science Initiative, BNL
- 2010 - 2012, Software Engineer, Mobile Communications Division, LG Electronics
Selected Publications
- Park G, Yoon B-J, Luo X, et al (2023) Automated Extraction of Molecular Interactions and Pathway Knowledge using Large Language Model, Galactica: Opportunities and Challenges. The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks. https://doi.org/10.18653/v1/2023.bionlp-1.22
- Park G, McCorkle S, Soto C, et al (2022) Extracting Protein-Protein Interactions (PPIs) from Biomedical Literature using Attention-based Relational Context Information. 2022 IEEE International Conference on Big Data (Big Data). https://doi.org/10.1109/bigdata55660.2022.10021099
- Park G, Pouchard L (2021) Advances in Scientific Literature Mining for Interpreting Materials Characterization. Machine Learning: Science and Technology. doi: 10.1088/2632-2153/abf751
- Acharya A, Agarwal R, Baker MB, Baudry J, Bhowmik D, et al. (2020) Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. Journal of Chemical Information and Modeling 60:5832–5852. doi: 10.1021/acs.jcim.0c01010
- Park G, Rayz J, Pouchard L (2020) Figure Descriptive Text Extraction using Ontological Representation. In The Thirty-Third International Flairs Conference. doi: 10.48550/arXiv.2208.06040
- Pouchard L, Juhas P, Park G, Van Dam H, Campbell SI, Stavitski E, Billinge S, Wright CJ (2020) Provenance Infrastructure for Multi-modal X-ray Experiments and Reproducible Analysis. Handbook on Big Data and Machine Learning in the Physical Sciences 307–331. doi: 10.1142/9789811204579_0015
- Park G, Pouchard L (2019) Scientific Literature Mining for Experiment Information in Materials Design. 2019 New York Scientific Data Summit (NYSDS). doi: 10.1109/nysds.2019.8909726
- Park G, Rayz J (2018) Ontological Detection of Phishing Emails. 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC). doi: 10.1109/smc.2018.00486
- Park G, Stuart LM, Taylor JM, Raskin V (2014) Comparing machine and human ability to detect phishing emails. 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC). doi: 10.1109/smc.2014.6974273
Brookhaven National Laboratory
Computational Science Initiative
Bldg. 725
P.O. Box 5000
Upton, NY 11973-5000
(631) 344-6113
gpark@bnl.gov
