About

Ina has completed a PhD in Machine Learning at Carnegie Mellon University in Fall 2015, where she was a member of the Auton Lab. Between Fall 2015 and Fall 2018, she was a Postdoctoral Fellow in the Mobilize Center at Stanford University. She has joined the College of Information and Computer Sciences at UMass in September 2018. 

Ina aims to build hybrid systems that learn expressive representations of multimodal, heterogeneous data for predictive models designed to interact with human users. My current research revolves around hybrid methods for multimodal data, especially data from the healthcare domain. Ongoing projects: (1) Modeling disease trajectories and forecasting clinical outcomes by integrating multi-resolution, irregularly-sampled time series and images; (2) Weakly-supervised Transfer Learning of Models and Representations; (3) Online Adaptive Policies for Representation Learning.

Ina is the recipient of the Marr Prize for Best Paper at ICCV 2015 and of Star Research Award at the Annual Congress of the Society of Critical Care Medicine 2016. Madalina has co-organized NIPS workshops on the topic of Machine Learning in Healthcare in 2013, 2014, 2016, 2017 and 2018.