In my research, I study data mining and machine learning for time series and text. With robust methods in hand, I aim to advance healthcare and environmental data science.
My work has appeared at several top venues (KDD, AAAI, ACL, CIKM) and I spent a year collaborating with the UMass Medical School using machine learning to help doctors write clinical trials faster.
Please feel free to contact me with questions about my research or our program at WPI. I am always happy to chat!
- Sequential learning in time-sensitive domains (see our KDD 2019 and KDD 2020 papers)
- Recurrent Neural Networks (see our AAAI 2021 and CIKM 2020 papers)
- Explainable Deep Learning (see our ACL 2020 paper)
- Learning from systems with partial observations or missing values.
- Healthcare applications (see our ECML 2017, HEALTHINF 2018, BIGDATA 2019, and BIGDATA 2019 papers)
- June 7: Interning with Microsoft this summer.
- May 16: New KDD paper on spike train classification.
- Dec 2: New AAAI paper on combining knowledge from multiple RNNs.
- Oct 20: New IEEE BigData paper on Meta Word-Embeddings.
- Oct 18: Talk at Computational Sustainability Doctoral Consortium.
- Sept 17: Talk at Harvard.