MSSISS 2022 – MSSISS 2025

MSSISS 2022

MSSISS 2022

About


The Michigan Student Symposium for Interdisciplinary Statistical Sciences (MSSISS) is an annual event organized by graduate students in the Biostatistics, Electrical Engineering & Computer Science (EECS), Industrial & Operations Engineering (IOE), Statistics and Survey and Data Science (MPSDS) departments at the University of Michigan.

The goal of this symposium is to create an environment that allows communication across related fields of statistical sciences and promotes interdisciplinary research among graduate students and faculty. It encourages graduate students to present their work, share insights, and exposes them to diverse applications of statistical sciences. Though hosted by five departments we extend our invitation to graduate students from all departments across the University to present their statistical research in the form of an oral paper presentation or a poster presentation. It also provides an excellent environment for interacting with students and faculty from other areas of statistical research on campus.

MSSISS is an opportunity for interdisciplinary research and discussion across the fields of statistical sciences. Calling all graduate students (as well as talented undergraduates)! Come along, present your work, share insights, and learn about the diverse applications of statistical sciences.


Awards

Best Presentation

Best Application Presentation

Best Theory/Methodology Presentation

Jinming Li

PhD Student, Statistics

Network Latent Space Model with Hyperbolic Geometry

Ai Rene Ong

PhD Student, MPSDS

Respondent Driven Sampling Design Considerations

Dan Kessler

PhD Student, Statistics

Inference for Canonical Directions in Canonical Correlation Analysis

Honorable Mention

Honorable Mention

Kyle Gilman

PhD Student, EECS

Streaming Probabilistic PCA for Missing Data with Heteroscedastic Noise

Timothy Baker

PhD Student, EECS

Leveraging Correlation to Improve Accuracy in Stochastic Computing

Best Speed Presentation

Best Application Speed Presentation

Best Theory/Methodology Speed Presentation

Madeline Abbott

PhD Student, Biostatistics

Modeling cigarette use with mobile health data from a study on smoking cessation

Alicia Dominguez

PhD Student, Biostatistics

Bias accumulates in polygenic risk scores constructed with larger sets of markers in multiple complex traits. 

Fatema Shafie Khorassani

PhD Student, Biostatistics

Data Fusion for Time-to-Event Outcomes

Best Poster Presentation

Best Application Poster Presentation

Best Theory/Methodology Poster Presentation

Subha Maity

PhD Student, Statistics

Modeling cigarette use with mobile health data from a study on smoking cessation

Dylan Glover

Master’s Student, Statistics

Forecasting Geomagnetically Induced Currents at the Ottawa Magnetometer Station using ACE Variables

Roman Kouznetsov

PhD Student, Statistics

deepST: A Graph Convolutional Autoencoder for Spatial Transcriptomics

Best Master’s Presentation

Best Undergraduate Presentation

Abigail Loe

Master’s Student, Biostatistics

Just Statistics: In the Dark, Statistical Analysis, and the Failure of the Justice System

Yiling Huang

Junior, Statistics

Balance Assessment of Matched Data with Multiple Treatment Levels


Events

Invited Speakers

Presentations

Speed & Poster sessions

Learn about the cutting-edge research of our invited Keynote speaker and our Michigan junior faculty speaker

View abstracts

Students share their recent research in various presentation sessions

View sessions

Students display and discuss their research in a poster session preceded by speed presentations

View abstracts

Venue


Michigan League, 2nd floor

911 N University Ave
Ann Arbor, MI, USA
48109

Floor plan

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COVID

Our goal is to hold this event in person at Michigan League. For this reason, we will be abiding by all University guidelines (also see Michigan Unions COVID FAQs). In particular:

  • Face coverings will be required, regardless of vaccination status, except when actively eating or drinking.
  • You will be asked to show your health screening status using the ResponsiBlue app. Visitors entering U-M Facilities are expected to complete the ResponsiBlue Guest screening check.
  • You will be asked to sign a contact tracing sheet.

As the two previous years taught us, it is hard to know what the future has planned for us. We will be following the University’s decisions if it becomes unrealistic to meet in person: participant will be notified in time if MSSISS 2022 is moved to a remote format.


Sponsors

Department of Statistics, University of Michigan
With additional contributions from Professors Laura Balzano, Alfred Hero and Clayton Scott

Photos



Contact

Organizing Committee

mssiss2022-contact@umich.edu

Organizing Committee


Student Organizing Committee

Lap Sum Chan

PhD Student, Biostatistics

Curtiss Engstorm

PhD Student, Program in Survey and Data Science

Simon Fontaine

PhD Student, Statistics

Cheoljoon Jeong

PhD Student, Industrial and Operations Engineering

Alexander Ritchie

PhD Student, Electrical Engineering and Computer Science

Faculty Advisory Committee

Raed Al Kontar

Assistant Professor of Industrial and Operations Engineering

Johann Gagnon-Bartsch

Assistant Professor of Statistics

Timothy Johnson

Professor of Biostatistics

Brady West

Research Associate Professor of Survey Methodology

Clayton Scott

Professor of Electrical Engineering and Computer Science and of Statistics

Thanks

We would like to thank Judy McDonald from the Statistics department for all the administrative help in organizing this MSSISS iteration.

We would like to thank Lindsay Sorgenfrei, our Michigan League event organizer, for all the logistical help.

We also would like to extend our thanks to the 2021 MSSISS student organizers (Seokhyun Chung, IOE; Yijun Li, Biostatistics; Zeyu Sun, EECS; Ziping Xu, Statistics; Xinyu Zhang, Survey Methodology) and faculty mentors (Ed Ionides, Statistics; Jian Kang, Biostatistics; Vijay Subramanian, EECS) who helped with the transition and provided insightful suggestions.

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