Project Title: Equitable prioritization of active transportation infrastructure in Canadian cities
Supervisors: Shoshanna Saxe, University of Toronto, Faculty of Applied Science & Engineering, Department of Civil & Mineral Engineering; Timothy Chan, University of Toronto, Faculty of Applied Science & Engineering, Department of Mechanical & Industrial Engineering
"Building sustainable transportation systems is one of the most important problems we face. After a decade of experiencing the combined joy and frustration of active transportation first-hand, I am thrilled to join the Data Sciences Institute to apply cutting-edge interdisciplinary techniques to a problem I care about deeply: how to support safe and equitable active transportation in cities."
Project Title: Hypothesis Generation for Biochemistry Foundation Models
Supervisors: Florian Shkurti, University of Toronto Mississauga, Faculty of Arts and Science, Department of Mathematical and Computational Sciences; Chris Maddison, University of Toronto, Faculty of Arts and Science, Department of Computer Science; Alán Aspuru-Guzik, University of Toronto, Faculty of Arts and Science, Department of Chemistry
"Can powerful large language models or relevant techniques help advance modern biochemistry discovery effectively? I am delighted to have been selected as a DSI Postdoctoral Fellow, which will allow me to contribute to this impactful topic by exploiting my previous expertise in machine learning/data science and explore new possibilities in biochemistry."
Project Title: Can we discover conserved developmental pathways from single-cell transcriptomics data?
Supervisors: Sidhartha Goyal, University of Toronto, Faculty of Arts & Science, Department of Physics; Gary Bader, University of Toronto, Temerty Faculty of Medicine, Terrence Donnelly Centre for Cellular & Biomedical Research
This Postdoctoral Fellow is co-sponsored with the McLaughlin Centre, University of Toronto.
"I am very happy to receive a Data Sciences Institute Postdoctoral Fellowship. This fellowship allows me to pursue my research interests in applying data science to interdisciplinary problems in biology. Advances in experimental techniques are generating large quantities of data of single-cells, which presents exciting opportunities for data science research."
Project Title: Towards foundation models for gait analysis
Supervisors: Babak Taati, KITE Research Institute, University Health Network; Andrea Iaboni, KITE Research Institute, University Health Network
"I am honored to receive the Data Sciences Institute Postdoctoral Fellowship. Through this fellowship, I will focus on addressing a key bottleneck in AI-driven human movement analysis: the difficulty of obtaining sufficient labeled training data."
Project Title: Building publicly available data science tools for the assessment of naturalistic cognition in healthy aging
Supervisors: Rosanna Olsen, University of Toronto, Rotman Research Institute, Baycrest, Department of Psychology; Mark Chignell, University of Toronto, Faculty of Applied Sciences and Engineering, Department of Mechanical and Industrial Engineering; Jennifer Ryan, University of Toronto, Rotman Research Institute, Baycrest, Departments of Psychology & Psychiatry; Jed Meltzer, University of Toronto, Rotman Research Institute, Baycrest, Departments of Psychology & Speech Language Pathology
"I'm honoured to receive a Postdoctoral Fellowship from the Data Sciences Institute. This award will support our team's collaborative efforts, in data and neuroscience, to develop new, open-access tools to assess cognition in older adults, working toward a better understanding of age-related cognitive decline."
Project Title: Decoding Happiness: A Language-Based Analysis of Historical and Cultural Trends
Supervisors: Felix Cheung, University of Toronto, Faculty of Arts and Science, Department of Psychology; Sam Maglio, University of Toronto Scarborough, Department of Management
"I am very excited to receive the DSI Postdoctoral Fellowship which will allow me to learn and apply natural language processing to psychological well-being research. This multidisciplinary project will explore the determinants and consequences of happiness using a more inclusive and representative approach."
Project Title: Machine Learning Accelerated High Throughput Synthesis of Novel Energy Storage Materials for Li-ion Batteries
Supervisors: Oleksandr Voznyy, University of Toronto Scarborough, Department of Physical & Environmental Sciences; Gisele Azimi, University of Toronto, Faculty of Applied Science & Engineering, Department of Chemical Engineering and Applied Chemistry
"I feel extremely privileged to be a DSI post-doctoral fellow which allows me to pursue my academic career in one of the best scientific environments. I will make the most of this opportunity to discover novel materials for energy storage applications by combining cutting edge experimental techniques and data sciences. Output of my project will contribute to future solutions for the energy-related problems that our society is already facing."
Project Title: A generalized model of predicting outcomes of electrical neuromodulation studies
Supervisors: Paul Yoo, University of Toronto, Institute of Biomedical Engineering; José Zariffa, University of Toronto, KITE Research Institute, University Health Network & Institute of Biomedical Engineering
"I am thrilled to receive the Data Science Institute Postdoctoral Fellowship. Through this fellowship, I will be able to tackle a variety of challenges in the neural engineering space using innovative data science techniques."
Project Title: Integrative multi-omics study of pulmonary nodule malignancy based on molecular, clinical, and imaging data
Supervisors: Rayjean Hung, Lunenfeld-Tanenbaum Research Institute; Michael Brudno, University of Toronto, Faculty of Arts & Science, Department of Computer Science
"I am so honoured to receive this fellowship from the Data Sciences Institute. Through this postdoctoral fellowship, I am very excited to employ my multi-disciplinary knowledge to help advance data science related to multi-omics modeling, while addressing the imminent clinical challenge related to low-dose computed tomography screening for lung cancer based on unprecedented international data."
Project Title: Advancing Equity in Special Education: Assessing Educator Impact and Inclusion Trends in North American K-12 Schools
Supervisors: Elizabeth Dhuey, University of Toronto Scarborough, Department of Management; Michal Perlman, University of Toronto, Department of Applied Psychology and Human Development
"I am deeply grateful for the DSI Postdoctoral Fellowship. This fellowship will enable me to support my postdoctoral research which will use advanced quantitative methods and administrative longitudinal data to examine how education policies shape educational outcomes for students with disabilities in K-12 public schools."
Project Title: Public Health-Informed ML: High-Risk Diabetic Identification via Multidimensional Data Integration
Supervisors: Karim Keshavjee, University of Toronto, Dalla Lana School of Public Health, Institute for Health Policy, Management and Evaluation; Zahra Shakeri, University of Toronto, Dalla Lana School of Public Health, Institute for Health Policy, Management and Evaluation
"Diabetes and prediabetes affect over 11.7 million Canadians and costs the healthcare system $30 billion annually. With the support of the DSI Postdoctoral Fellowship, I will explore ways to enhance early detection and prevention of diabetes using data science methods, grounded in a well-articulated model of predictive, prescriptive, preventive, personalized, and participatory (P5) medicine."
Project Title: Multimodal speech analytics in the remote detection and tracking of neurological diseases
Supervisors: Yana Yunusova, University of Toronto, Faculty of Medicine, Department of Speech-Language Pathology; Ervin Sejdic, University of Toronto, Faculty of Applied Science and Engineering, Department of Electrical and Computer Engineering
"It is an honour to be a recipient of a Data Sciences Institute Postdoctoral Fellowship. This work will provide an unparalleled opportunity to advance our understanding of the interactions between sounds and movements in speech, and identify ways to combine these representations."
Project Title: Preterm birth, parental socioeconomic status, and long-term educational and economic outcomes: A novel application of multi-state modeling and causal inference methods on a national longitudinal cohort over 34 years
Supervisors: Petros Pechlivanoglou, The Hospital for Sick Children, Child Health Evaluative Sciences Labs; Eleanor Pullenayegum, The Hospital for Sick Children, Child Health Evaluative Sciences Labs
"I am delighted to receive the Data Sciences Institute Postdoctoral Fellowship to support my postdoctoral training in the Child Health and Evaluative Sciences Program at the Hospital for Sick Children. The DSI Postdoctoral Fellowship will give me the flexibility to pursue my research interests and broaden my research experiences. As a DSI fellow, I will have the chance to work with an interdisciplinary team of researchers and interact with researchers from other fields to expand my professional network. This opportunity will also allow me to develop my professional and academic skills to establish myself as an independent investigator."
Project Title: New Technologies and Evaluations for Novel Accented Speech Recognition
Supervisors: Ewan Dunbar, University of Toronto, Faculty of Arts & Science, Department of French; Gerald Penn, University of Toronto, Faculty of Arts & Science, Department of Computer Science
"Thanks to the DSI Postdoctoral Fellowship I am able to challenge the assumption speech recognition is one-size-fits-all. Addressing our failings is the only way that research may move forward."
Project Title: Log Gaussian Cox process to construct spatially continuous maps of disease risk
Supervisors: Patrick Brown, University of Toronto, Faculty of Arts & Science, Department of Statistical Sciences; Prabhat Jha, University of Toronto, Dalla Lana School of Public Health
"I am very grateful for the opportunity to join the Data Sciences Institute. Through this postdoctoral fellowship I will be able to be part of an interdisciplinary project whose final aim is the creation of an open source to construct spatially continuous maps of disease risks from aggregated data. This opportunity is a great step forward for my professional career as a researcher in applied statistics."
