Qi Li

Qi Li (pronouns as Chee Li, or you can use Chinese style called me lychee, one of my favorite fruits) am an Assistant Professor in the School of Business, SUNY New Paltz. She joined the New Paltz faculty in the fall of 2020. Her teaching focuses on Business Analytics, including Data Analysis, Data Visualization, and Database system. Before she jointed SUNY, she worked in Norther Kentucky University as a Data Science Program Associate Director, teaching Data Science sequential courses, including, Data Wrangling, Data Mining, Big Data, and Data Science Capstone. She also worked in Cincinnati Children's Hospital Medical Center as a researcher to study health care information. She graduated from University of Pittsburgh and studied on Information Science.

My research interests include:

  • Business Analytics
  • Machine Learning
  • Information Extraction
  • Big Data
  • Information Retrieval
  • Natural Language Processing
  • Medical Informatics

Here is my last CV



These are selected publications. You may also refer to my Google Scholar Profile.

Journal   |   Conference   |    Poster   |
  • McGuffee J, Li Q, and Rubleske J. A Transdisciplinarity Approach to an Undergraduate Degree in Data Science, Big Data & Analytics EDCON 2014, October 25, 2014. (DOI: 10.13140/2.1.2189.5363)
  • Zhai H, Iyer S, Ni Y, Lingren T, Li Q, Tang T, Solt I, Mining a large-scale EHR with machine learning methods to predict all-cause 30-day unplanned readmissions, 2014 Bigdata/Socialcom/Cybersecurity, Stanford, CA, May 2014
  • Li Q, Zhai H, Deleger L, Lingren T, Solt I, Linking medications and their attributes in clinical notes and clinical trial announcements for information extraction: a sequence labeling approach. Healthcare Informatics, Imaging and Systems Biology (HISB), 2012 IEEE Second International Conference on, San Diego, CA, Sept. 2012. Best Paper Award.
  • Lingren T, Zhai H, Li Q, Deleger L, Solt I, Pre-annotating clinical notes and clinical trial announcements for gold standard corpus development: Evaluating the impact on annotation speed and potential bias. Healthcare Informatics, Imaging and Systems Biology (HISB), 2012 IEEE Second International Conference on, San Diego, CA, Sept. 2012.
  • Zhai H, Deleger L, Lingren T, Li Q, Solt I, Cheap, fast, and good enough for the nonbiomedical domain but is it usable for clinical Natural Language Processing? Evaluating crowdsourcing for clinical trial announcement named entity annotations. Healthcare Informatics, Imaging and Systems Biology (HISB), 2012 IEEE Second International Conference on, San Diego, CA, Sept. 2012
  • Deleger L, Brodzinski H, Zhai H, Li Q, Lingren T, Solt I, Using natural language processing and the electronic health record for appendicitis risk stratification. Healthcare Informatics, Imaging and Systems Biology (HISB), 2012 IEEE Second International Conference on, San Diego, CA, Sept. 2012. Best Paper Nomination.
  • Deleger L, Li Q, Lingren T, Kaiser M, Molnar K, Stoutenborough L, Kouril M, Marsolo K, Solt I, Building gold standard corpora for medical natural language processing tasks. AMIA Annual Symposium. 2012.
  • Li Q, He D, Facilitating image exploratory search with relations, Proceedings of the American Society for Information Science and Technology, 2011.
  • Li Q, He D, Finding support documents with a logistic regression approach, Proceedings of the First International Workshop on Entity-Oriented Search (EOS), 2011.
  • Li Q, He D, Towards classifying exploratory search results with Wikipedia, eCASE & eTech 2010.
  • Li Q, He D, Mao M, A study of relation annotation in business environments using web mining, In the Proceedings of the Third IEEE International Conference on Semantic Computing (ICSC09) 2009.
  • Mao M, Heinzel T, Klemba K, Li Q, A sensemaking-based information foraging and summarization system in business environments, In the Proceedings of the 2009 International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government (EEE’09) 2009.
  • Hsiao I, Lin Y, Li Q, Wang H. Educational mashup in example authoring. The 16th International Conference on Computers in Education (ICCE2008) 2008.
  • Ahn J, Brusilovsky P, He D, Grady J, Li Q. Personalized web exploration with task models. In World Wide Web Conference 2008. Under 12% acceptance rate.
  • He D, Brusilovsky P, Grady J, Li Q. How up-to-date should it be? The value of instant profiling and adaptation in information filtering. In Proceeding of 2007 International Conference on Web Intelligence, WI ’07, Silicon Valley, CA, USA, November 2-5, 2007,
  • Zhai H, Brady P, Li Q, Lingren T, Ni Y, Wheeler D, Solti I. Predicting the need for Pediatric Intensive Care Unit (PICU) transfer for newly hospitalized children with machine learning. AMIA Annual Symposium, Washington DC, 2013. (Abstract presented in AMIA 2013)
  • Li Q, Solt I, AutoMCExtractor: a method for automatic medical condition extraction, NIH Workshop: Natural Language Processing: State of the Art, Future Directions and Applications for Enhancing Clinical Decision-Making, Rockville, MD, 2012. (Posters)
  • Chapman W, Conway M, Dowling J, Tsui R, Li Q, Christensen L, Harkema H, Sriburadej T, Espino JU. Challenges in Adapting an NLP System for Real-time Surveillance. 9th Annual Conference of the International Society for Disease Surveillance. Park City, UT. 2010.
  • Hsiao I, Li Q and Lin Y. Educational social linking in example authoring, In Proceedings of 18th conference on Hypertext and hypermedia, HT ’08, Pittsburgh, USA, 19-21 June, 2008, ACM Press. (Posters)

Contact me.

My email: liq11@newpaltz.edu

Office: VH208