Hi! I’m currently a Ph.D. candidate at Worcester Polytechnic Institute in our Data Science program, a part of the Computer Science department. Broadly, I am interested in sequence modeling and so my research often involves designing Recurrent Neural Networks to solve problems on a variety of sequential data. So far, I have enjoyed developing and applying my representation learning methods to clinical sequences (e.g., vital signs, lab results, and free-hand notes) and look forward to expanding my horizons in new directions.
I am advised by Prof. Elke Rundensteiner and Prof. Xiangnan Kong.
Specific Research Interests
I am interested in sequence modeling, or building vector representations that capture relevant temporal dynamics in sequential data such as time series or text. So far, I have studied early classification, clinical note classification, meta word embeddings, and representation learning for irregularly-sampled time series. Additionally, I have some conditional computing in RNNs work in submission with an extension on the way! I have also had the pleasure of advising many NSF-funded REU students over the summers on some research involving missing values in clinical time series and sequential diagnosis prediction using RNNs.
Please feel free to contact me with questions regarding my research or our program at WPI at twhartvigsen ‘at’ wpi ‘dot’ edu. I would be happy to go into much more detail on my research one-on-one.
- [KDD] Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke Rundensteiner. Adaptive-Halting Policy Network for Early Classification. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019. [ACM Paper Link][pdf][code].
- [BHI] Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke Rundensteiner. Comparing General and Locally-Learned Word Embeddings for Clinical Text Mining. IEEE International Conference on Biomedical and Health Informatics (BHI), 2019. [pdf].
- [CCIS] Thomas Hartvigsen, Cansu Sen, Elke Rundensteiner. Detecting MRSA Infections by Fusing Structured and Unstructured Electronic Health Record Data. Communications in Computer and Information Science. [pdf]
- [HEALTHINF] Thomas Hartvigsen, Cansu Sen, Sarah Brownell, Erin Teeple, Xiangnan Kong, Elke Rundensteiner. Early Prediction of MRSA Infections using Electronic Health Records. International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 5: HEALTHINF, pages 156-167, ISBN: 978-989-758-281-3. Shortlisted for Best Student Paper. [pdf]
- [ECML/PKDD] Cansu Sen, Thomas Hartvigsen, Kajal Claypool, Elke Rundensteiner. CREST - Risk Prediction for Clostridium Difficile Infection Using Multimodal Data Mining. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD) 2017. [pdf]
In my spare time, I enjoy rock climbing, cycling, reading (fantasy, science fiction, science fact), and playing guitar.
- September 16, 2019: Talk at University of Minnesota - Presenting our KDD paper at the University of Minnesota Workshop: Recent Progress in Foundational Data Science.
- August 19-20, 2019: Conference - Attending Big Data 2019 at Harvard University.
- August 3-8, 2019: Talk at ACM SIGKDD - I am happy to be attending KDD 2019 and presenting my paper this week!
- May 10, 2019: Talk at New England Machine Learning Day - Presented a poster titled “Adaptive-Halting Policy Network for Early Classification” at the New England Machine Learning Day at Northeastern University.
- April 29, 2019: Paper Accepted to ACM SIGKDD! - Our paper titled “Adaptive-Halting Policy Network for Early Classification” was accepted to KDD 2019, research track, acceptance 14%.
- April 16, 2019: Passed Research Qualifier - Passed my research qualifier, studying irregular multivariate time series classification.
- April 9, 2019: Best Poster Award - I was awarded first place in WPI’s annual interdisciplinary graduate research showcase.
- March 5, 2019: Paper Accepted to BHI - Our paper titled “Comparing General and Locally-Learned Word Embeddings for Clinical Text Mining” was accepted to the IEEE International Conference on Biomedical and Health Informatics.
- January 18, 2019: Workshop - Attended the Geometric Analysis Approach to AI Workshop at Harvard University.
- November 15, 2018: Defended Master’s Thesis - I successfully defended my Master’s Thesis: Adaptively-Halting RNN for Tunable Early Classification of Time Series.
- September 1, 2018: Machine Learning Research Internship - Beginning a part-time internship with UMass Medical School in the quantitative sciences department.
- August 02, 2018: REU Project Complete - Mentored two undergraduate REU students. Their research manifested into a paper at the MIT URTC and their poster was presented at the REU Symposium in Washington, D.C.
- May 30, 2018: Mentoring REU students - I am working with 2 undergraduate Research Experience for Undergraduates (REU) students this summer to develop a state-of-the-art model for classifying time series with missing values.
- April 30, 2018: AWARD - I was awarded the WPI Data Science Citizen Award for involvement and participation in the growth of the department.
- April 24, 2018: Poster Presentation - Poster presentation at the WPI Graduate Research and Innovation Exchange. We had three posters at this event, one of which won the People’s Choice Award.
- January 19, 2018: Talk at BIOSTEC - I presented our paper “Early Prediction of MRSA Infections Using Electronic Health Records” at HEALTHINF 2018 in Madeira, Funchal.
- December 12, 2017: Paper award - Our paper, “Early Prediction of MRSA Infections Using Electronic Health Records”, was nominated for the HEALTHINF 2018 best student paper award.
- October 16, 2017: Paper Accepted to HEALTHINF - Our paper, “Early Prediction of MRSA Infections Using Electronic Health Records”, was accepted to HEALTHINF 2018 as a full paper.
- August 19, 2017: Conference - Attended Machine Learning for Healthcare (MLHC) 2017 at Northeastern University.
- June 23, 2017: Paper Accepted to ECML - Our paper, “CREST - Risk Prediction for Clostridium Difficile Infection Using Multimodal Data Mining”, was accepted to ECML-PKDD 2017 as a full paper.
- May 2, 2017: AWARD - I was awarded the WPI Data Science Citizen Award for involvement and participation in the growth of the department.
- February 8, 2017: AWARD - Poster presentation with Cansu Sen at the WPI Graduate Research and Innovation Exchange, received the People’s Choice award.
- August 25, 2016 - Began Ph.D. at Worcester Polytechnic Institute, Worcester, Massachusetts.