MiCHAMP Seminar Series

The biweekly MiCHAMP Seminar Series is intended for MiCHAMP investigators and other invited speakers to present their funded research or proposals under development on data science, machine learning and predictive modeling.  Discussion is highly encouraged and trainees are welcome to attend with their faculty mentors. The Seminar Series reflects the rich multidisciplinary and collaborative nature of MiCHAMP, with membership from Medicine, Engineering, Statistics, Nursing, Public Health and Pharmacy.

MiCHAMP Seminar Series will be presented via Zoom.

Contact us at michamp-mgr@umich.edu for details.

Upcoming Seminars

Friday September 25, 2-3pm

Joelle Pineau, PhD, MSc, BASc, Co-Managing Director at Facebook AI Research, Assoc Prof at McGill University & Faculty Member at Mila.

On the Development of Robust and Reproducible AI Systems for Automatically Learning Personalized Treatment Strategies

Location: Zoom

Friday October 9, 2-3pm

Nilay D Shah, PhD, Professor of Health Sciences Research at Mayo Clinic


Location: Zoom

Friday October 23, 2-3pm

David Kent, MD, CM, MS Prof of Medicine, Neurology and Translational Science, Tufts University &

Jessica Paulus, ScD, Investigator, Institute for Clinical Research and Health Studies, Tufts University


Location: Zoom

Friday November 6, 2-3pm

Cooper Stansbury, MSc, Informatics PhD Student –U-M


Location: Zoom

Friday November 20, 2-3pm

Marzyeh Ghassemi, PhD, MSc, Asst. Prof of Computer Science and Medicine at the University of Toronto

Don’t Expl-AI-n Yourself: Exploring “Healthy” Models in Machine Learning for Health

Location: Zoom

Friday December 18, 2-3pm

Inbal (Billie) Nahum-Shani, PhD, Co-Director Data-Science for Dynamic Decision-Making Lab (d3lab), Institute for Social Research, U-M

Experimental Designs for Building mHealth Interventions: Connecting the Dots between Factorial Designs, SMARTs and MRTs

Location: Zoom

Friday February 12, 2021, 2-3pm

Rashmee U. Shah, MD, MS Asst Prof in Cardiovascular Medicine at the University of Utah School of Medicine


Location: Zoom

Past Seminars

Friday September 11, 2020

VG Vinod Vydiswaran, PhD, Asst Prof of Learning Health Sciences, Medical School & Asst Prof of Information, School of Information

Harnessing the Power of Clinical Text for Cohort Identification and Medication Extraction

Friday, May, 29, 2020

Alanson Sample, PhD, Associate Professor, Electrical Engineering & Computer Science

Sensing Systems for In-home Activity Inferencing and Health Monitoring

Friday, May 15, 2020

Rada Mihalcea, PhD, Professor, Electrical Engineering & Computer Science

The Artificial Intelligence Lab at Michigan: Ins and Outs ; Bonus: Natural Language Processing for Health Communication

Friday, March 6, 2020

Andrew Krumm, PhD, Associate Professor of Learning Health Sciences at U-M Medical School

Data-Intensive Approaches to Measuring Learning in Education and Health Systems: Reflections, Examples, and Implications

Friday, February 21, 2020

Karandeep Singh, MD, MMSc

Journal Club: A clinically applicable approach to continuous prediction of future acute kidney injury

Friday, February 7, 2020

James O. Woolliscroft, MD, MACP, FRCP, Professor of Internal Medicine and Learning Health Sciences

& Cornelius A. James, MD, Instructor of Internal Medicine and Pediatrics

Machine Learning meets Evidence-Based Medicine: A Users’ Guide for Clinicians

Friday, January 24, 2020

Saige Rutherford, BS, Data Analyst with MiSCAN Lab

The Current State of Prediction in Neuroimaging

Friday, January 10, 2202

Shengpu Tang, BSE, PhD student, Computer Science & Engineering, U-M

& Parmida Davarmanesh, College of Literature, Science, and the Arts student, U-M

Democratizing EHR Analyses – A Comprehensive, Generalizable Pipeline for Learning from Structured Clinical Data

Friday, December 20, 2019

Arvind Rao, Ph.D., Associate Professor, Dept of Computational Medicine & Bioinformatics and Radiation Oncology

& Tingyang Li, BS, Student

Bias and Fairness in Cardiovascular Disease Risk Prediction

Location: IHPI Collaboratory (NCRC B10-G079)

December 6, 2019

Nicholson Price, JD, Asst Professor of Law, Michigan Law, U-M

Law, Innovation, and Bias in Medical AI

November 22, 2019

Hamid Ghanbari, MD

& Kevin Wheelock, Medical Student

Preliminary Results From the MiAfib Registry

November 8, 2019

Rajan Dewar, MBBS, PhD, Adjunct Associate Professor, Dept of Pathology, U-M

Maternal Health Worldwide – Is There a Role for Predictive Analytics to Improve Health Delivery?

October 25, 2019

Seth Klapman, BS, U-M MD/MBA Student
& Karandeep Singh, MD, MMSc, U-M Learning Health Sciences & Internal Medicine

1000 Heart Sounds: Leveraging Intelligent Auscultation to Predict Cardiovascular Disease

October 4, 2019

Michael Ho, MD, PhD, Professor of Medicine, University of Colorado School of Medicine and Co-Director of the Center for Innovation at Denver and Seattle VA Medical Centers

NavLab: Trials and tribulations of implementing a learning health system

September 27, 2019

Drew Bennett, MBA, U-M Office of Technology Transfer

Software Licensing 2020: IP Management – Open Source, Proprietary and Protection

September 13, 2019

Erin Kaleba, MPH, Data Office for Clinical and Translational Research
& Cinzia Smothers, M. Bioethics, U-M Precision Health

The Precision Health Analytics Platform: Data, Analytics, and Resources for Your Research

June 20, 2019

Rahul Deo, MD, PhD, One Brave Idea

Doing more with less … extending cardiovascular diagnostic interpretation beyond human ability

May 31, 2019

Hae Mi Choe, PharmD, Associate Dean for Pharmacy Innovations and Clinical Associate Professor, College of Pharmacy, U-M
& Amy Pasternak, PharmD, Clinical Assistant Professor of Pharmacy and Clinical Pharmacist, College of Pharmacy, U-M

Precision Health Implementation at Michigan Medicine

May 17, 2019

Karandeep Singh, MD, MMSc,Assistant Professor in Learning Health Sciences and Internal Medicine U-M

Potential FDA Regulation of Artificial Intelligence/Machine Learning Algorithms

April 19, 2019

Danai Koutra, PhD, Assistant Professor, Computer Science & Engineering, U-M

Fast Inference and Mining of Functional Brain Networks

March 22, 2019

Nikola Banovic, PhD, Assistant Professor, Electrical Engineering & Computer Science, U-M

A Computational Modeling Approach to Predicting Hospital Readmission

March 8, 2019

Hamid Ghanbari MD, MPH, Cardiologist, Assistant Professer, U-M

Novel Techniques for Evaluation of Symptoms in Atrial Fibrillation: A Machine Learning Approach

February 22, 2019

Laura Balzano, PhD,Assistant Professor in Electrical Engineering and Computer Science,U-M

Finding Low-rank Structure in Messy Data

February 14, 2019

MIDAS Music Challenge recipient:

Somangshu Mukherji, PhD, Assistant Professor of Music Theory, U-M

Computational Music Theory and Music as the “Universal Language”

February 8, 2019

Tim Guetterman, PhD, Assistant Professor, Co-Director, Michigan Mixed Methods Program, U-M
& Vinod Vydiswaran, PhD, Assistant Professor of Learning Health Sciences, Medical School and Assistant Professor of Information, School of Information, U-M

Natural Language Processing/Machine Learning for Qualitative Data Review and Analysis

January 25, 2019

Richard Gonzalez, PhD, Amos N. Tversky Collegiate Professor of Psychology and Statistics, U-M

You Say `Features’, I Say `Variables’ – Exploring Key Differences between Statistical and Machine Learning Approaches to Modeling Data

January 11, 2019

MIDAS Health Science Challenge recipients:

Anna Gilbert, PhD, Herman Goldstine Collegiate Professor, Dept of Mathematics, U-M
& Jun Li, PhD, Professor & Associate Chair for Research of Computational Medicine and Bioinformatics, U-M

An Overview of the MIDAS Single Cell Data Analysis Center: Analysis, Modeling, and Applications

December 7, 2018

Ben Wellner, PhD, MITRE Corporation

Predicting Septic Shock in Pediatric Intensive Care Units (PICUs)

November 9, 2018

Karthik Duraisamy, PhD, Michigan Engineering, Michigan Institute for Computational Discovery and Engineering (MICDE)

Machine Learning Augmented Predictive Modeling of Complex Systems

November 8, 2018

Donald Likosky, PhD, Associate Professor, Dept of Cardiac Surgery, U-M
& Steven Yule, PhD, Associate Professor of Surgery, Harvard Medical School

Novel Assessments of Technical and Non-Technical Cardiac Surgery Quality

November 2, 2018

Mike Sjoding, MD, Pulmonary and Critical Care Medicine, Internal Medicine, U-M
& Jenna Wiens, PhD, Computer Science and Engineering, U-M

Using Reinforcement Learning to Identify Optimal Treatment Policies for Acute Respiratory Failure

October 19, 2018

Jodyn Platt, MPH, PhD, Assistant Professor of Learning Health Sciences

Introducing Predictive Models into the Clinical Space: Designing Trustworthy Systems

October 12, 2018

Ulysses Balis, MD, Professor of Pathology, U-M Medical School

Early Insights from the Application of Machine Vision and Machine Learning Techniques to Histopathological Subject Matter

August 10, 2018

Vincent Liu, MD, MSc, Kaiser Permanente Northern California Division of Research

Towards Precision Delivery: Balancing Prediction and Phenotyping

June 1, 2018

Elliott Brannon, MPH (MD/PhD student) & Karandeep Singh, MD, MMSc

Towards a Learning Health System to Reduce Emergency Department Visits at a Population Level

May 18, 2018

Mohammed Saeed, MD, PhD

Creating Healthcare Databases to Support Research in Machine Learning: Lessons Learnt from MIMIC

May 11, 2018

Donald Likosky, PhD & Michael Mathis, MD

Development and Evaluation of Novel Computer-Assisted Assessments of Technical and Non-technical Cardiac Surgery Quality

May  4, 2018  – MiCHAMP / CHOP / IHPI Combined Event

David Hodgson, MD, MPH,  University of Toronto

Change has its Enemies: Opportunities and Barriers in the Adoption of Machine Learning Methods in Oncology


Danielle Rodin, MD, MPH, University of Toronto

Variation in Cancer Spending: Implications for Value-Based Care

See the MiCHAMP News Post

April 18 to April 20, 2018

John P.A. Ioannidis, MD, DSc, Stanford University

• The Power of Bias and What to do About it
• Precision Health, Big Data and Evidence-Based Medicine—Contradictions or Companions?
View this seminar
• Reproducible and Useful Clinical Research: Mission Impossible?

For more information, see the MiCHAMP News

April 6, 2018

Jiaxuan Wang, BS, Ian Fox, & Jenna Wiens, PhD

The Advantage of Doubling: A Deep Reinforcement Learning Approach to Studying the Double Team in the NBA

March 23, 2018

Kayvan Najarian, PhD

Major Challenges of Using AI in Healthcare and Potential Solutions

March 9, 2018

Dr. Steffen Leonhardt, MD, PhD, Professor, RWTH Aachen University, Aachen, Germany.

Thou Shalt Not Touch – Nonobtrusive and Noncontact Monitoring Techniques for Medical Applications

*this lecture was co-sponsored by MiCHAMP, MCIRCC, and U-M Department of Computational Medicine & Bioinformatics

February 9, 2018

Andrew Gelman, PhD, Professor of statistics and political science and Director of the Applied Statistics Center at Columbia University.

What’s Wrong with ‘Evidence-Based Medicine’ and How Can We Do Better?

*this seminar was co-sponsored by MiCHAMP, Interdisciplinary Statistical Learning Workshop (LSA Political Science) & the Department of Philosophy

January 26, 2018

Jeff McCullough, PhD

Causal Inference in Machine Learning with Applications for Heterogeneous Treatment Effects for Medical Device Utilization

January 12, 2018

Hallie Prescott, MD, MSc

Upcoming IIR on Hospital Performance Measurement

January 10, 2018

Mohammad Ghassemi

Healthcare 2.0: Integrating Health and Behavioral Data for AI-driven Care


December 15, 2017

Seth Klapman and Karandeep Singh, MD, MMSc

Digital Auscultation to Predict Echo Findings in Cardiovascular Disease

December 8, 2017

Wenshou Liu, PhD

Journal Club – Deep Learning

November 17, 2017

Yun Jiang, PhD, MS, RN

Mobile Sensor Data-to-Knowledge (MD2K) – NIH Training Institute 2017 Scholar

November 3, 2017

Akbar Waljee, MD, MSc, Ji Zhu, PhD, MSc, Xuefei Zhang, BS, Boang Liu, MA, and Tony Van

Predicting Hep C Progression Using Machine Learning

October 19, 2017

John Spertus, MD, MPH, FACC, CCMR Distinguished Visiting Professor; Director, Health Outcomes Research, Saint Luke’s Mid American Heart Institute; Professor, University of Missouri-Kansas City.

The Past, Present and Future of Patient-Reported Outcomes

October 6, 2017

Tim Guetterman, PhD

Bioinformatics and Education

September 22, 2017

Tejas Prahlad, Dan Zeiberg, and Mike Sjoding, MD

Data-Driven Patient Risk Stratification for Acute Respiratory Distress Syndrome

September 8, 2017

Brahmajee Nallamothu, MD, MPH

Internal Medicine Bicentennial Presentation

May 19, 2017

James Davies

We Predict, and a Health Use Case

May 12, 2017

Mike Mathis, MD

Integrating Perioperative Care into the Diagnosis of Heart Failure: A Data Science Approach

May 5, 2017

Ravi Shah and Venk Murthy, MD, PhD

Integrated Cardiovascular Phenotyping and Molecular Characterization: From Populations to Molecules

April 28, 2017

Matt Churpek, MD, MPH, PhD

Using EHR Data to Detect Clinical Deterioration

April 21, 2017

Jack Iwashyna, MD, PhD

ResCU II – “Long-Term Trajectories of Recovery Following Serious Hospitalization with In-Hospital Cardiac Arrest”

March 10, 2017

Ryan Stidham, MD & Akbar Waljee, MD, MSc

Big Data / Better Data: Using Machine Vision in Crohn’s Disease

February 17, 2017

Srijan Sen, MD, PhD

Medical Internship as a Model to Identify Real-Time Objective Predictors of Depression under Stress

January 27, 2017

Ian Fox and Jenna Wiens, PhD

Contextual Motifs – Improving the Utility of Motifs for Analyzing Physiological Signals

January 20, 2017

Mike Sjoding, MD and Kayvan Najarian, PhD

New Machine-learning Paradigms to Improve Identification of Acute Respiratory Distress Syndrome

January 13, 2017

Anna Kratz, PhD

God is in the Details: Ambulatory Methods and Mysteries of Health-related Quality of Life

January 6, 2017

Adam Markovitz, MD, PhD, Mike Mathis, MD,  Jeremy Sussman, MD, MS

SPRINT Challenge Update – 3 Approaches and a Discussion

December 16, 2016

Sardar Ansari, PhD and Kayvan Najarian, PhD

Polyvinylidene Fluoride Based Sensor for Non-invasive Hemodynamic Monitoring

December 9, 2016

Venkatesh Murthy, MD, PhD

Molecular Markers of Early Cardiometabolic Health Transitions

December 2, 2016

Andy Ryan, PhD and Jeff McCullough, PhD

Nowcasting & Forecasting Health Expenditures

November 11, 2016

Allen Flynn, PharmD

Digital Library of Learning (Computable Knowledge Object Library System)

October 28, 2016

Karandeep Singh, MD, MMSc

Using Clinical Notes to Uncover Everyday Natural Experiments in Healthcare

October 21, 2016

Jeremy Sussman, MD, MS

Improving Doctors’ Report Card with Analytics:  Benefit-Based Performance Measurement in Cardiovascular Disease

October 7, 2016

Jacob Mack, MD, BS

SPRINT Challenge