Fahad Kamran

PhD Candidate at the University of Michigan.

I am a fourth year Ph.D. candidate in Computer Science at the University of Michigan, working in the MLD3 lab under Jenna Wiens. My primary research lies in the intersection of machine learning and healthcare. Specifically, my research focuses on identifying challenges preventing the use of machine learning in real clinical applications and building novel solutions to tackle these problems, particularly in the fields of causal inference and survival analysis. I am also interested in the combination of machine learning and data from wearable sensors to detect and prevent physiological harm, the use of electronic health record (EHR) data to improve patient care across a multitude of settings and diseases, including COVID-19 and Sepsis, and sports analytics.

I received my Bachelors degree from the University of California, Berkeley in Mathematics, Statistics, and Computer Science. Outside of research, I enjoy going to the gym, playing and watching sports, and watching movies and television.

News

  • Our work on early identification of at-risk covid-19 patients was highlighted in the STAT Newsletter.

  • Our works "Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study" was accepted to the BMJ.

  • Our works "Automated Loss-of-Balance Event Identification in Older Adults at Risk of Falls during Real-World Walking Using Wearable Inertial Measurement Units." and "Noninvasive Estimation of Hydration Status in Athletes Using Wearable Sensors and a Data-Driven Approach Based on Orthostatic Changes." were accepted to Sensors

  • Our work "Automatically evaluating balance using machine learning and data from a single inertial measurement unit." was accepted to the Journal of NeuroEngineering and Rehabilitation

  • Our work focused on validating the Epic Deterioration Index on COVID-19 patients was highlighted in the media: In scramble to respond to Covid-19, hospitals turned to models with high risk of bias.

  • Our work focused on validating the Epic Deterioration Index on COVID-19 patients was highlighted in the media: From collaboration to validation: How a team of engineers, clinicians, programmers, and administrators evaluated one of the most widely implemented predictive models.

  • Our work "Estimating Calibrated Individualized Survival Curves with Deep Learning." was accepted to the AAAI 2021.

Publications

  • Fahad Kamran et al. "Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study." BMJ. 2022. Link

  • Jeremiah Hauth, Safa Jabri, Fahad Kamran, Eyoel W Feleke, Kaleab Nigusie, Lauro V Ojeda, Shirley Handelzalts, Linda Nyquist, Neil B Alexander, Xun Huan, Jenna Wiens, Kathleen H Sienko, "Automated Loss-of-Balance Event Identification in Older Adults at Risk of Falls during Real-World Walking Using Wearable Inertial Measurement Units." Sensors. 2021. Link

  • Fahad Kamran, Kathryn Harrold, Jonathan Zwier, Wendy Carender, Tian Bao, Kathleen H Sienko, Jenna Wiens, "Automatically evaluating balance using machine learning and data from a single inertial measurement unit." Journal of NeuroEngineering and Rehabilitation. 2021. Link

  • Fahad Kamran*, Victor Le*, Adam Frischknecht, Jenna Wiens, and Kathleen Sienko. "Noninvasive Estimation of Hydration Status in Athletes Using Wearable Sensors and a Data-Driven Approach Based on Orthostatic Changes." Sensors. 2021. Link

  • Fahad Kamran and Jenna Wiens. "Estimating Calibrated Individualized Survival Curves with Deep Learning." 2021 AAAI Conference on Artificial Intelligence. 2021. Link

  • Karandeep Singh, Thomas S. Valley, Shengpu Tang, Benjamin Y. Li, Fahad Kamran, Michael W Sjoding, Jenna Wiens, Erkin Otles, John P Donnelly, Melissa Y Wei, Jonathon P McBride, Jie Cao, Carleen Penoza, John Z Ayanian, Brahmajee K Nallamothu, "Validating a Widely Implemented Deterioration Index Model Among Hospitalized COVID-19 Patients." Annals of the American Thoracic Society. 2020. Link

  • Caleb Belth, Fahad Kamran, Donna Tjandra, and Danai Koutra. "When to remember where you came from: node representation learning in higher-order networks." 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 2019. Link

Teaching

  • 07/21: Lecturer for Big Data Summer Institute at the University of Michigan

  • 09/19-12/19: Graduate Student Instructor for EECS 492: Introduction to Artificial Intelligence at the University of Michigan

  • 07/19: Lecturer for Big Data Summer Institute at the University of Michigan

  • 05/18-08/18: Course Instructor for Data 8: Foundations of Data Science at the University of California, Berkeley

  • 01/16-05/16; 08/16-12/16; 08/17-05/18: Head Teaching Assistant for Data 8: Foundations of Data Science at the University of California, Berkeley

  • 01/17-05/17: Teaching Assistant for CS 61B: Data Structures and Algorithms at the University of California, Berkeley

  • 05/16-08/16: Teaching Assistant for CS 188: Introduction to Artificial Intelligence at the University of California, Berkeley

Awards

  1. Computer Science Outstanding Teaching and Leadership Award. University of California, Berkeley, 2018.
  2. Campus Outstanding GSI Award, University of California, Berkeley, 2019.
  3. Computer Science and Engineering Service Award for Excellence in Climate, Diversity, Equity, and Inclusion. University of Michigan. 2020.

Miscellaneous

  • If you would like to check out some of my study materials for UC Berkeley courses such as CS61A, CS70, or CS C8, check out my teaching section.

  • Check out some of my photography here.

  • Check out my sports blog Ballin' with Fahad!