About
I am an EWSC Postdoctoral Fellow at the Broad Institute of MIT and Harvard. My research lies at the intersection of machine learning and healthcare. I work on developing methods that integrate multimodal biomedical data to better understand human health. I am also interested in challenges of deploying clinical ML in healthcare environments and finding solutions for effective and safe use of such tools in practice. I received my PhD in Computer Science from the University of Toronto, under supervision of Dr. Anna Goldenberg. During my PhD, I received the Apple Scholars in AI/ML Fellowship and the CIHR Health System Impact Fellowship.
Education
- Ph.D. in Computer Science, University of Toronto, 2023
- B.Sc. in Computer Engineering, University of Toronto, 2018
Awards
- Rising Star in Computational and Data Sciences (2023)
- Apple Scholars in AI/ML PhD Fellowship (2021)
- NSERC Canada Graduate Scholarships – Doctoral (2021)
- Queen Elizabeth II Graduate Scholarship in Science and Technology (2020)
- CIHR Health System Impact Fellowship (2019)
- NSERC Undergraduate Student Research Award (2015, 2016)
Selected Research Papers
HDP-Flow: Generalizable Bayesian Nonparametric Model for Time Series State Discovery
Sana Tonekaboni, Tina Behrouzi, Addison Weatherhead, Emily Fox, David Blei, Anna Goldenberg;
UAI, 2025.
Sana Tonekaboni, Tina Behrouzi, Addison Weatherhead, Emily Fox, David Blei, Anna Goldenberg;
UAI, 2025.
The Latentverse: An Open-Source Benchmarking Toolkit for Evaluating Latent Representations
Yoanna Turura, Samuel Freesun Friedman, Aurora Cremer, Mahnaz Maddah, Sana Tonekaboni;
CHIL, 2025.
[Code]
Yoanna Turura, Samuel Freesun Friedman, Aurora Cremer, Mahnaz Maddah, Sana Tonekaboni;
CHIL, 2025.
[Code]
An information criterion for controlled disentanglement of multimodal data
Chenyu Wang, Sharut Gupta, Xinyi Zhang, Sana Tonekaboni, Stefanie Jegelka, Tommi Jaakkola, Caroline Uhler;
ICLR, 2025.
Chenyu Wang, Sharut Gupta, Xinyi Zhang, Sana Tonekaboni, Stefanie Jegelka, Tommi Jaakkola, Caroline Uhler;
ICLR, 2025.
Learning under Temporal Label Noise
Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen;
ICLR, 2025.
Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen;
ICLR, 2025.
Modeling Personalized Heart Rate Response to Exercise and Environmental Factors with Wearables Data
Achille Nazaret; Sana Tonekaboni; Gregory Darnell; Shirley You Ren; Guillermo Sapiro; Andrew C. Miller
npj Digital Medicine, 2023.
Achille Nazaret; Sana Tonekaboni; Gregory Darnell; Shirley You Ren; Guillermo Sapiro; Andrew C. Miller
npj Digital Medicine, 2023.
Decoupling Local and Global Representations of Time Series
Sana Tonekaboni, Chun-Liang Li, Sercan O Arik, Anna Goldenberg, Tomas Pfister;
AISTATS, 2022.
Sana Tonekaboni, Chun-Liang Li, Sercan O Arik, Anna Goldenberg, Tomas Pfister;
AISTATS, 2022.
How to validate Machine Learning Models Prior to Deployment
Sana Tonekaboni, Gabriela Morgenshtern, Azadeh Assadi, Aslesha Pokhrel, Xi Huang, Anand Jayarajan, Robert Greer, Gennady Pekhimenko, Melissa McCradden, Fanny Chevalier, Mjaye Mazwi, Anna Goldenberg;
CHIL, 2022.
Sana Tonekaboni, Gabriela Morgenshtern, Azadeh Assadi, Aslesha Pokhrel, Xi Huang, Anand Jayarajan, Robert Greer, Gennady Pekhimenko, Melissa McCradden, Fanny Chevalier, Mjaye Mazwi, Anna Goldenberg;
CHIL, 2022.
Unsupervised Representation Learning for TimeSeries with Temporal Neighborhood Coding
Sana Tonekaboni, Danny Eytan, Anna Goldenberg;
ICLR, 2020.
Sana Tonekaboni, Danny Eytan, Anna Goldenberg;
ICLR, 2020.
What went wrong and when? Instance-wise feature importance for time-series models
Sana Tonekaboni, Shalmali Joshi, Kieran Campbell, David K. Duvenaud, Anna Goldenberg;
NeurIPS, 2020.
Sana Tonekaboni, Shalmali Joshi, Kieran Campbell, David K. Duvenaud, Anna Goldenberg;
NeurIPS, 2020.
What Clinicians Want: Contextualizing Explainable ML for Clinical End Use
Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg;
MLHC, 2019.
Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg;
MLHC, 2019.