MIDAS has organized the first Consortium for Data Scientists in Training in the country. This is one of many steps to build collaboration with academic data science institutes across the nation. MIDAS facilitates this activity to build a network for these students and postdoctoral fellows, allowing them to receive feedback about their research, and nurturing them to become the next generation of academic leaders in data science.

2020 Consortium for Data Scientists in Training

The 2020 cohort comes from 28 universities, and will meet virtually on Oct. 29th-30th to participate in research talk presentations, networking sessions, and mentoring opportunities. The full agenda and cohort will be released soon.

The research talk presentations will take place from 12:00pm – 2:00pm EST each day and are open to the public.

Register to attend the research talk sessions

Mentoring session speakers:

  • Dr. Jeffrey Fessler, Professor of the Department of Electrical and Computer Engineering, University of Michigan
  • Dr. Margaret Levenstein, Director of the Inter-university Consortium for Political and Social Research, University of Michigan
  • Dr. Bhramar Mukherjee, Professor and Chair of the Department of Biostatistics, University of Michigan
  • Dr. Michael Wellman, Professor and Chair of the Department of Computer Science and Engineering, University of Michigan
  • One representative from Google will discuss industry careers for data scientists

See Full 2020 Cohort

2020 Cohort to be released soon!

2019 Consortium for Data Scientists in Training

See Full 2019 Cohort

Name University Department Abstract Title
Dhivya Eswaran Carnegie Mellon University Computer Science “SedanSpot: Detecting Anomalies in Edge Streams”
Otilia Stretcu Carnegie Mellon University Machine Learning “Graph Agreement Models for Semi-Supervised Learning”
William Dula Clark Atlanta University Mathematical Sciences “Application of a Contour Theory Method to Load Profiling in a Power Utility”
Ipek Ensar Columbia University Data Science Institute “Exercise as medicine: Can exercise behavior predict endometriosis disease symptom severity?”
Sandrine Muller Columbia University Data Science Institute “Everyday Mobility Behaviors Predict Psychological Well-Being Among Young Adults”
Marko Angjelichinoski Duke University Electrical and Computer Engineering “Robust Estimation and Classification for Brain-Computer Interfaces”
Didong Li Duke University Mathematics “Density Estimation on Manifolds with Fisher-Gaussian Kernels”
Robert Ravier Duke University Electrical Engineering “Foundational Issues in Computational Evolutionary Biology and Political Science”
Shan Shan Duke University Mathematics “Probabilistic Models on Fibre Bundles”
Daniel Ruiz-Perez Florida International University Computing and Information Sciences “Predicting microbe-microbe interactions from time series metagenomic data”
Thinh Doan Georgia Institute of Technology Electrical and Computer Engineering & Industrial and Systems Engineering “Distributed Decision Making on Multi-Agent Systems”
Michelle Ntampaka Harvard University Harvard Data Science Initiative “A Deep Learning Approach to Galaxy Cluster X-ray Masses”
Dakota Murray  Indiana University Bloomington Informatics “Making sense of scientific systems”
Lanmiao He Iowa State University Psychology “Being aware helps: how mindfulness and data analytics benefit students and an educational NPO”
Gianina Alin Negoita Iowa State University Animal Science “Face2Face: Facial Expression Transfer”
Tuhin Sarkar Massachusetts Institute of Technology Electrical Engineering “Learning Structure from Unstructured Data”
Anastasios Noulas New York University Center for Data Science “Wiki-Atlas: Rendering Wikipedia Content through Cartographic and Augmented Reality Mediums”
Nan Wu New York University Center for Data Science “Towards solving breast cancer screening diagnosis with deep learning”
Asmamaw Gebrehiwot North Carolina A&T State University Applied Science and Technology “Flood Extent Mapping using Unmanned Aerial Vehicle Imagery”
Luiz G. A. Alves Northwestern University Chemical & Biological Engineering “Reconstructing commuters network using machine learning and urban indicators”
Yian Yin Northwestern University Industrial Engineering and Management Science “Quantifying dynamics of failure across science, startups, and security”
Lige Gan Oakland University Computer Science and Engineering “Attention-based Multi-Source Representation Learning” 
Arunima Srivastava The Ohio State University Computer Science and Engineering “Interpretable and Context Based Neural Network Modeling of Histology Images”
Andrew Polasky Penn State Meteorology and Atmospheric Science “Statistical Downscaling of Climate Models using self-organizing maps”
Yi-Yu Lai Purdue University Computer Science “Relational Representation Learning Incorporating Textual Communication for Social Networks”
Ye Emma Zohner Rice University Statistics “Bayesian Functional Regression on Manifold via Spherical Wavelets”
Baharan Mirzasoleiman Stanford University Computer Science “Large-scale Combinatorial Optimization for Data Summarization and Resource-efficient Machine Learning”
Stuart Geiger UC-Berkeley Berkeley Institute for Data Science “Operationalizing Conflict and Cooperation Between Automated Software Agents in Wikipedia: A Replication, Refutation, and Expansion of ‘Even Good Bots Fight.’”
Yang Junwen University of Chicago Computer Science “Improving Performance and Quality of Database-Backed Software”
Yushen Dong University of Illinois at Chicago  Mathematics, Statistics, and Computer Science “Nonparametric interaction selection for additive model”
Oluwagbemiga Ajayi University of Maryland Baltimore County Information Systems “Diagnosis Of Type II Diabetes Using Machine Learning Techniques”
Ronak Razavisousan University of Maryland Baltimore County Information Systems “Two Layer Clustering Analysis of Student Migration from Twitter Posts”
Srinivas Rallapalli University of Minnesota Bioproducts and Biosystems Engineering “Developing an optimized decision support framework for sustainable field-scale assessment by integrating ACPF, PTMApp, and HSPF-SAM”
Tony Cannistra University of Washington Biology “Data Science Methods and Climate Change Ecology: A Scientific Imperative”
Erin Wilson University of Washington Computer Science and Engineering “Using microorganisms to solve macro problems: untangling the genetic circuitry of methane-eating bacteria”
Mina Karzand UW Madison Wisconsin Institute for Discovery “Active Learning in the Overparameterized and Interpolating Regime”
Najibesadat Sadati Wayne State University Industrial and Systems Engineering “Dynamic Resource Allocation for Coordination of Inpatient Operations in Hospitals”