People

Ben is an associate professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst and director of the REML lab

Erik is a research fellow working across multiple labs including REML, the Sensors lab, and the Institute for Applied Life Sciences. He designs, implements, deploys, and runs evaluation studies of machine learning and sensor systems.

Colin is an PhD student. His current research focuses on the development of deep learning for multi-modal detection, localization and tracking. He earned his BS at University of Wisconsin-Madison.

Karine is a PhD student. Her research focuses on Bayesian time series modeling and reinforcement learning with applications to longitudinal behavioral data analysis and just-in-time adaptive interventions.

Hui is a PhD student. He is working on modeling incomplete wearable sensor data using deep time series models. He completed an MS at New York University and BS at Bejing University of Posts and Telecommunications.

Erin joined the lab in Spring 2022 as a freshman CS major and worked as a study coordinator and programmer until Spring 2023.

Benjamin joined the lab for Spring 2023 and worked as a programmer on the HeartSteps project. He was a CS undergrad at UMass Amherst and joined the MS program starting in Fall 2023.

Meghan worked in the lab as a study coordinator in the 2021-2022 academic year. She graduated from UMass Amherst with a BS in Biochemistry and Neuroscience in 2022.

Meet completed his PhD in Summer 2022. His research focused on computationally efficient Bayesian deep learning methods. Meet joined Amazon in summer 2022.

Alan worked in the lab during the 2022-2023 academic year supporting data entry for a MassAITC research project. He completed a BS in Informatics in Spring 2023.

Satya completed his PhD on deep learning methods for multi-modal clinical data including irregularly sampled time series in 2021 and joined Facebook AI Research.

Conrad completed an MS on active learning methods including streaming active learning for mobile and real-time systems.

Steve completed his PhD in spring 2020. His doctoral research focused on methods for modeling incomplete and irregularly sampled data using deep probabilistic models. He joined Google in summer 2020.

Roy completed his PhD in summer 2018 on the topic of structured prediction for event detection and activity segmentation with applications to mobile health. He joined Johns Hopkins as a Post Doc in fall 2018 and is now a faculty member in the Johns Hopkins School of Medicine.

Malai completed his PhD in Fall 2018. He was jointly advised by Profs. Deepak Ganesan and Ben Marlin. His research focused on the application of structured prediction, domain adaptation, and and active learning to problems in mobile health. He joined Philips Research North America in Cambridge, MA. as a Research Scientist in Fall 2018.

Hamid is an ECE PhD graduate from the UMass High Dimensional Signal Processing Group. He simultaneously completed  a Computer Science MS working with Prof. Marlin. His MS research focused on cascaded classification for networks of devices. Hamid re-joined Prof. Marlin's group as a Post Doc from Fall 2017 to Summer 2018. He has since worked at IBM Research, Amazon, and Google.

Sid completed his MS project on recurrent neural networks with attention for arrhythmia detection under Prof. Marlin. He graduated in spring 2016. He is currently a computer vision engineer at Hivemapper.

Oliver was a computer science honors undergraduate research student. His honors research project focused on the implementation of the firm cascade model in TensorFlow for deployment on Android. He graduated in Spring 2019.

Andrew was a computer science honors undergraduate research student. His undergraduate thesis focused on the development of methods for aligning video and wireless sensor data. He graduated in Spring 2019 and started an MS in CS at Stanford in Fall 2019.

Alex was a computer science honors undergraduate research student. His undergraduate thesis focused on the development of a cross-modal active learning system for video and wireless sensor data. He graduated in Spring 2018 and joined MathWorks.

Andrew was an NSF-funded REU student in Summer 2017. He worked on automated feature extraction from time series data using deep learning with applications to mobile health. He graduated from Yale in Spring 2018 and currently works at Apple as a software engineer on the Siri team.

Thai was a computer science honors undergraduate research student. His undergraduate thesis focused on CRF CFG models for parsing noisy wireless ECG data. He graduated in Spring 2016 and joined Airbnb as a software engineer.

Laura was an NSF REU student in summer 2016. She worked on evaluating methods for segmenting and featurizing time series with applications to smoking puff detection from wireless sensor data. She graduated from Davidson College in Spring 2018 and works at Independence Consulting.

Esther was a student in the NSF-funded REUMass data science program under Prof. Marlin in summer 2015. Her research focused on investigating the effect of signal noise on structured prediction methods for ECG data analysis. She was a student at the University of Puerto Rico-Mayaguez and now works as an algorithm design engineer at General Motors.

Gregory was an NSF Research Experience for Undergraduate student working with Prof. Marlin in summer 2012 working on methods for irregularly sampled time series analysis. He joined the University of Toronto CS graduate program after completing his undergraduate degree at Austin College.