Congratulations to our 2016 DAC Graduates!

As the dust settles from graduation, DAC would like to recognize the students who have graduated this year.  DAC is proud to have had eight graduate students complete their degrees this spring semester; seven of which received a Ph.D. and one receiving a Master’s of Science. Below we highlight our students who are now prepared to assume roles as faculty members, researchers, and data analysts. We look forward to their contribution to the field data science and cannot wait to see what they achieve from here. Congratulations!

Harsh Agrawal received a Master’s of Science in Electrical and Computer Engineering.  His thesis was titled ‘CloudCV: Deep Learning and Computer Vision on the Cloud.’ His research focuses on problems at the intersection of computer vision and machine learning.  Harsh built CloudCV which is a large scale cloud system with the aim to democratize computer vision and deep learning algorithms and make it accessible to anybody who wants to apply computer vision to their research or software applications. He will now be joining Snapchat as a research engineer where he hopes to apply computer vision and deep learning to build the next generation mobile communication app.

Marcos Carzolio received a Ph.D. in Statistics. His research is on a selection of Markov chain Monte Carlo methods for large scale inference and big data. Specifically, he is developing a new algorithm called weighted particle tempering, and applying it and another algorithm called reversible jump Markov chain Monte Carlo to average over free B-spline models for a dataset about child development in rural Mozambique. Marcos will be working at Goldman Sachs Asset Management in New York City as a strategist.

Pritwish Chakroborty received a Ph.D. in Computer Science.  His thesis focused on formalizing disease forecasting models using open source indicators.  Disease surveillance is often delayed an unstable; however, real time information about diseases could be obtained from sources such as news and weather. Pritwish built a number of statistical models borrowing principles from GLM, MCMC and Matrix Factorization methods to build forecasting models for endemic diseases such as Flu and CHIKV.  He also built and managed the endemic disease forecasting framework which was used to send continuous forecasts to IARPA and CDC. Pritwish will be joining IBM Watson Health, USA where he will shift focus to more micro level disease models towards personal health.

Andy Hoegh received a Ph.D. in Statistics.  His dissertation research focused on statistical algorithms for fusing predictions from a set of models with the primary goal of predicting instances of civil unrest. In the fall he will be starting as an assistant professor of statistics in the Department of Mathematical Sciences at Montana State University.

Fang Jin received a Ph.D. in Computer Science. Her dissertation is about mass movements and their adoptions in social media. Her work includes how to capture mass movements diffusion patterns across a wide geographical area, how to detect events based on group anomalies, how to distinguish real movements from rumors, etc.

Marjan Momtazpour received a Ph.D. in Computer Science.  Her thesis was titled the ‘Knowledge Discovery for Sustainable Urban Mobility’. She has published several papers in the areas of Energy Management, Urban Infrastructure Investment, Anomaly Detection in urban transportation, and Outlier Detection in time series of general cyber-physical systems. She plans to join Microsoft  Data Platform group located in Redmond,WA.

Jessica Zeitz Self received a Ph.D. in Computer Science. Her dissertation focused on designing and evaluating object-level interaction to support human-model communication in data analysis. She is joining the Computer Science Department at the University of Mary Washington as an Assistant Professor this fall.

Maoyuan Sun received a Ph.D. in Computer Science.  His research interests include Visual Analytics, Information Visualization, Human Computer Interaction, Human Centered Machine Learning and Usable Security. In his Ph.D. dissertation, Maoyuan explores the design space of bicluster visualizations to support coordinated relationship exploration. Maoyuan has accepted a tenure-track faculty position offer from the University of Massachusetts Dartmouth.  He will start working as an assistant professor in the Computer & Information Science Department, College of Engineering this coming fall.