We are always interested in hearing from MS/PhD and PhD students who would like to join the lab. The desired educational background includes calculus, linear algebra, probability and statistics, artificial intelligence, algorithms, and programming. Prior experience with machine learning, numerical optimization or Bayesian statistics is a plus. Relevant prior research experience is highly valued. Candidates should apply directly to the College of Information and Computer Sciences and should clearly indicate their interest in the MLDS lab in their personal statement. Information about the UMass CS graduate program is available here.
Assessing the Limits of Program-Specific Garbage Collection Performance Conference
Programming Language Design and Implementation, 2016, (<p>Distinguished Paper Award</p>).
Journal of Medical Internet Research, 18 , 2016, (<p>n/a</p>).
Detecting Divisions of the Autonomic Nervous System Using Wearables Proceeding
Florida, USA, 2016.
Domain Adaptation Methods for Improving Lab-to-field Generalization of Cocaine Detection using Wearable ECG Proceeding
Heidelberg, Germany, 2016.
Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams Conference
International Conference on Machine Learning, 2016, (<p>n/a</p>).