In my research, I am intersecting and advancing data mining and machine learning for time series and text. With robust methods in hand, I aim to advance healthcare.
My work has appeared at several top conferences (KDD, AAAI, ACL) 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 regarding my research or our program at WPI. I am always looking to chat about research!
- Sequential Learning in Time-Sensitive Domains (see [KDD'19][KDD'20])
- Recurrent Neural Networks (see [AAAI'21][CIKM'20])
- Explainable Deep Learning (see [ACL'20])
- Learning from systems with partial observations or missing values.
- Healthcare applications (see [ECML'17][HEALTHINF'18][BIGDATA'19a][BIGDATA'19b])
- Dec 2: New AAAI paper on combining knowledge from multiple RNNs.
- Dec 1: I will be joining Microsoft next year as a PhD intern.
- Oct 20: New IEEE BigData paper on Meta Word-Embeddings.
- Oct 18: Talk at Computational Sustainability Doctoral Consortium.
- Sept 17: Talk at Harvard.
- July 17: New CIKM paper on conditional computation in RNNs.
- June 4: Talk at FSU.
- May 15: New KDD paper on Early Multi-label Classification.
- April 4: New ACL paper on the interpretability of attention mechanisms for text classification.