Data Sciences Institute Research Day 2024

On October 1, 2024, join us for the Data Sciences Institute Research Day, featuring leading voices in data science. 

The DSI Research Day #DataSciencesDay showcases the work of the DSI community and
provides a forum for collaborators in academia, industry and government to connect. The day includes a poster session to highlight the innovative research taking place in DSI-funded projects.

Join us for engaging lightning talks and discussions, networking activities and interactive panels. Discover cutting-edge research through presentations and posters presented by DSI researchers.

Program
9:00 – 9:30 am	Registration Opens
9:30 – 9:40 am	Welcome and Opening Remarks Prof. Lisa Strug, Director, Data Sciences Institute
9:40–10:45am	Navigating the Emergent Data Winter: Reimagining Data Access and Stewardship in the AI Era - Keynote Dr. Stefaan G. Verhulst, Research Professor, Tandon School of Engineering. Co-Founder of The GovLab (NYC) and the DataTank (Brussels). Editor-in-chief of Data & Policy (Cambridge University Press) In an age where datafication is pervasive and data science is experiencing a renaissance, we paradoxically face a potential "data winter." Access to crucial data is increasingly restricted, posing a threat to data science progress and, more importantly, stalling essential data-driven research and public interest initiatives. This talk delves into the emerging data asymmetries and their profound implications. It will address critical questions such as: How can we prevent a data winter by establishing systematic, sustainable, and responsible public-private data collaboratives? What strategies and foundational elements are necessary for this transformation? Is there a need for a new science of questions to complement and enhance data science? How should we reimagine data stewardship? How can we advance digital self-determination through a social license for data reuse? What steps are needed to transition from data to decision intelligence?
10:45 –11:00 am	Break
11:00am–12:00pm	Research Software for Impact - Lightning Talks Jo Bovy, Professor and Canada Research Chair in Galactic Astrophysics, Department of Astronomy & Astrophysics, University of Toronto Gregory Schwartz, Scientist, Princess Margaret Cancer Centre, University Health Network, and Professor, Medical Biophysics, University of Toronto, Canada Research Chair in Bioinformatics and Computational Biology Areti Angeliki Veroniki, Scientist, Knowledge Translation Program, St. Michael’s Hospital, Unity Health Toronto, and Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto Moderator - Lisa Strug, Director, Data Sciences Institute, Professor, Departments, Computer Science and Statistical Sciences, University of Toronto, and Senior Scientist, Program in Genetics and Genome Biology, The Hospital for Sick Children
12:00 – 1:30 pm	Lunch and Poster Presentations Posters will be displayed during the lunch and trainees will be available to discuss their work
1:30 – 2:30 pm	Research to Impact - Lightning Talks Sara Allin, Associate Professor, Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto Robert Batey, Professor, Department of Chemistry, University of Toronto Brice Batomen Kuimi, Assistant Professor, Epidemiology, Dalla Lana School of Public Health Bree McEwan, Associate Professor, Institute for Communication, Culture, and Information Technology, University of Toronto Mississauga Moderator - Ethan Fosse, Department of Sociology, University of Toronto Scarborough and DSI Associate Director, UTSC
2:30 – 2:45 pm	Break
2:45 – 4:00 pm	Translating Data for Decision-Making - Panel Michael Hillmer, Assistant Deputy Minister, Digital Analytics and Strategy Division, Ministry of Health and Ministry of Long-Term Care, Ontario Public Service Lillian Sung, Canada Research Chair in Pediatric Oncology Supportive Care, Division of Haematology/Oncology, Chief Clinical Data Scientist, The Hospital for Sick Children Amol Verma, Clinician-Scientist, St. Michael's Hospital, and Assistant Professor, Temerty Professor of AI Research and Education in Medicine, University of Toronto Linbo Wang, Associate Professor, Department of Computer and Mathematical Sciences, University of Toronto Scarborough Moderator – Laura Rosella, Associate Professor, Dalla Lana School of Public Health and Department of Laboratory Medicine & Pathobiology, Temerty Faculty of Medicine, University of Toronto
4:00 – 4:10 pm	Closing Remarks Lisa Strug, Director, Data Sciences Institute

Keynote

Stefaan G. Verhulst
Co-Founder of the Governance Laboratory (The GovLab) Dr. Verhulst is an expert in using data and technology for social impact. He is the Co-Founder of several research organizations including the Governance Laboratory (GovLab) at New York University and The DataTank base in Brussels. He focuses on using advances in science and technology, including data and artificial intelligence, to improve decision-making and problem-solving. He is the Editor-in-Chief of the open-access journal Data & Policy and has served as a member of several expert groups on data and technology, including the High-Level Expert Group to the European Commission on Business-to-Government Data Sharing and the Expert Group to Eurostat on using Private Sector data for Official Statistics. He has been recognized as one of the 10 Most Influential Academics in Digital Government globally. He has published extensively on these topics, including several books, and has been invited to speak at international conferences, including TED and the UN World Data Forum. He is asked regularly to provide counsel on data stewardship to a variety of public and private organizations.

Research Software Tools for Impact - Lightning Talks

Jo Bovy
Professor and Canada Research Chair in Galactic Astrophysics, Department of Astronomy & Astrophysics, University of Toronto

Prof. Bovy’s research is currently mostly focused on understanding the dynamical structure, formation, and evolution of the Milky Way, but he is interested in a variety of problems in astrophysics, especially those that involve large-scale data analysis.

Working with postdoctoral fellow Mike Walmsley and the DSI Research Software Development Office, Prof. Bovy developed Zoobot3D, a cutting-edge new DSI-funded software development project that connects AI industry with human ingenuity, efficiently measuring, labelling, annotating and cataloguing images of deep space. Zoobot3D will be the first and software tool for galaxy feature segmentation, underpinning a new field of research that will help researchers answer questions that would otherwise be impossible. Essentially, Zoobot3D will help researchers develop maps to millions of previously unknown galaxies.

Gregory Schwartz
Scientist and Canada Research Chair in Bioinformatics and Computational Biology, Princess Margaret Cancer Centre, University Health Network, and Professor, Medical Biophysics, University of Toronto

Dr. Schwartz has developed several methodologies for mutation detection, data integration, and cellular population visualization to understand cancer heterogeneity and diverse responses to anti-cancer therapies. His current research involves integrating multi-omic information and leveraging single-cell resolution to identify underlying mechanisms of drug resistance in cancer.

Dr. Schwartz had a vision to deploy a set of tools for clustering and visualizing single-cell data. To bring this vision to life, the DSI Research Software Development team developed an app as a reimplemented version of an existing static visualization algorithm. One notable component of TooManyCells tool is its custom-made visualization feature which presents cell relationships as a tree. Through the utilization of TooManyCells, it has become possible to identify rare cancer cells that contribute to disease progression, thus addressing an important need in the field.

Areti Angeliki Veroniki
Scientist, Knowledge Translation Program, St. Michael’s Hospital, Unity Health Torontoo
Assistant Professor, Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto

Dr. Veroniki’s research interests are in optimizing the processes of evidence-based medicine, and in particular, in the statistical modelling for knowledge synthesis, including network meta-analysis. She is a co-Convenor of the Cochrane Statistical Methods Group and co-Chair of the Cochrane Methods Executive.

Dr. Veroniki aimed to develop a user-friendly web interface called Rank-Heat Plot R Shiny tool. This tool allows health researchers to upload spreadsheets containing medical treatment results and visualize and compare outcomes easily. It particularly addresses the challenges faced by health researchers, especially in data interpretation, when utilizing network meta-analysis (NMA) that combines evidence from multiple randomized trials to compare various treatments. The DSI Research Software development team created the R Shiny interface for the Rank-Heat Plot tool. The tool can now empower clinicians, guideline developers, and policy makers to make well-informed decisions regarding drug coverage, provide recommendation and discuss optimal treatment options with patients across different outcomes.

Lisa Strug – Moderator
Director, Data Sciences Institute
Director, Canadian Statistical Sciences Institute (CANSSI), Ontario Region
Professor, Departments, Computer Science and Statistical Sciences, University of Toronto
Senior Scientist, Program in Genetics and Genome Biology, The Hospital for Sick Children

Dr. Strug is the inaugural Director of the Data Sciences Institute, a tri-campus, multi-institutional, multi-disciplinary hub for data science activity at the University of Toronto and affiliated Research Institutes. Dr. Strug holds several other leadership positions at the University of Toronto including the Director of the Canadian Statistical Sciences Institute Ontario Region (CANSSI Ontario), and at the Hospital for Sick Children as Associate Director of the Centre for Applied Genomics and the Lead of the Canadian Cystic Fibrosis Gene Modifier Consortium and the Biology of Juvenile Myoclonic Epilepsy International Consortium. She is a statistical geneticist, and her research focuses on the development of novel statistical approaches to analyze and integrate multi-omics data to identify genetic contributors to complex human disease. She has received several honours including the Tier 1 Canada Research Chair in Genome Data Science.

Research for Impact - Lightning Talks

Sara Allin
Associate Professor
Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto
Director, North American Observatory on Health Systems and Policies

Prof. Allin’s research and teaching span comparative health systems and policies, health system performance and health equity. She is also Director of the North American Observatory on Health Systems and Policies (NAO), a collaborative partnership and research centre focused on sub-national and international health systems research to support evidence-informed policy making.

Profs. Allin and Tara Gomes (Unity Health Toronto) received funding to access linked administrative data to study the patterns of Flash Glucose Monitoring (FGM) systems among recent immigrants in Ontario compared to long-term residents. The FGM system is a novel diabetes management technology, consisting of a monitor and sensor, and is used to measure and display continuous glucose readings without the need to obtain a blood sample through finger pricking. This study, conducted by PhD Candidate Mary Elias, under the supervision of Allin and Gomes, is the first in Canada to examine the uptake of this novel medical technology among immigrants within the context of a publicly funded benefits program.

Robert Batey
Professor, Department of Chemistry, Faculty of Arts & Science, University of Toronto

Prof. Batey’s research program is focused on the development of new synthetic methods and their application toward the synthesis of biologically active compounds.

Profs. Batey and Matthieu Schapira (Department of Pharmacology and Toxicology, Temerty Faculty of Medicine, University of Toronto, received DSI seed funding to begin the development of a pan-Canadian chemical library. They leveraged this initial work to receive $1.5M funding from NSERC to develop a pan-Canadian chemical library to explore uncharted chemistry space for drug discovery. The Library is a collection of nearly 150 billion diverse compounds and could be a resource of choice for protein targets where other libraries have failed to deliver bioactive molecules.

Brice Batomen Kuimi
Assistant Professor, Epidemiology, Dalla Lana School of Public Health

Prof. Batomen Kuimi is fundamentally motivated by understanding the distribution and the determinants of early mortality and morbidity. Hence, his motivation to work on injuries, which are one of the leading cause of death, disability, and health care costs for people under 40 years of age.

His current project, supported by the DSI, aims to evaluate several municipal initiatives under Vision-Zero Plans related to road safety and active transportation. Specifically, he is leveraging image recognition algorithms to develop a comprehensive database detailing the installation of traffic calming measures across major Canadian cities.

Bree McEwan
Associate Professor, Institute for Communication, Culture, and Information Technology, University of Toronto Mississauga

Prof. McEwan’s research focuses on the intersection between interpersonal communication and communication technology. Her book Navigating New Media Networks explores how communication technology, in particular social media facilitates interpersonal communication processes and relationships. Her recent projects involve tests of an original theory of online information diffusion, the Mediated Skewed Diffusion of Issues Information theory, and exploring how people interact within virtual reality environments.

Profs. McEwan and Prof. Grace Sun Joo (Grace) Ahn (Director, Center for Advanced Computer-Human Ecosystems, University of Georgia) are co-leads on the project Questioning Reality: Explorations of Virtual Reality funded by the Alfred P. Sloan Foundation. After a successful and first conference in 2024, they are working on future initiatives including a special issue of Debates in Digital Media edition on Virtual Reality, another conference and micro-grants to bring together collaborative teams.

Ethan Fosse – Moderator
Professor, Department of Sociology, University of Toronto Scarborough
Associate Director, DSI@UTSC Computational & Quantitative Social Sciences

Prof. Fosse’s research focuses on using novel quantitative methods to understand social change. He is working on three interrelated projects: first, creating a new set of techniques for identifying age-period-cohort effects, with wide application in sociology and related fields; second, explaining social and cultural change, focusing on the economic, religious, and political views of recent birth cohorts; finally, developing and applying high-dimensional sparse regression models to quantitatively analyze textual data. He has recently begun a project analyzing the individual-level consequences of social mobility.

Translating Data for Decision-Making - Panel

Michael Hillmer
Assistant Deputy Minister,
Digital and Analytics Strategy,
Ontario Ministry of Health/Ministry of Long-Term Care

Dr. Hillmer is an Assistant Deputy Minister in the Ontario Ministries of Health and Long-Term Care where he is responsible for digital health, data, and analytics. Previously, he worked at the federal level and in the private sector. He is an associate professor in the Institute for Health Policy, Management, and Evaluation at the University of Toronto.

Lillian Sung
Scientist and Canada Research Chair in Pediatric Oncology Supportive Care, Division of Haematology/Oncology, and,
Chief Clinical Data Scientist, The Hospital for Sick Children

Dr. Sung is a Pediatric Oncologist and Clinician Scientist with an independent research program focused on supportive care for children with cancer. Her overall goal is to optimize supportive care for children with cancer, with an aim to maximize quality of life, survival, and cost-effectiveness. She is the Chair of Cancer Control and Supportive Care for the Children’s Oncology Group (COG). This group oversees all studies of supportive care including studies related to symptom management and patient-reported outcomes. Her clinical focus is on the inpatient care of children and adolescents with leukemia and lymphoma. She has taught graduate courses at the University of Toronto and co-directs an advanced randomized trials course.

Amol Verma
Clinician-Scientist, St. Michael’s Hospital
Assistant Professor, Temerty Professor of AI Research and Education in Medicine, University of Toronto
Provincial Clinical Lead, Ontario Health

Dr. Verma works to study and improve hospital care using data from electronic health records. He co-leads GEMINI, a data and analytics platform that partners with hospitals across Ontario. Dr. Verma is an inaugural Provincial Clinical Lead for Quality Improvement in General Medicine with Ontario Health, and co-leads the Ontario General Medicine Quality Improvement Network. He led the development and implementation of a machine learning tool to predict and prevent death and critical illness at St. Michael’s Hospital.

Linbo Wang
Associate Professor, Department of Computer and Mathematical Sciences, University of Toronto Scarborough
Faculty Affiliate, Vector Institute
Co-Lead, Causal Inference for Policy Emergent Data Science Program, Data Sciences Institute

Prof. Wang’s research interest is centered around causality and its interaction with statistics and machine learning including graphical models, and modern statistical inference in infinite-dimensional models. He is the recipient of several research awards, including a NSERC Discovery Accelerator Supplement. Prior to joining the University of Toronto, he spent two years at Harvard Causal Inference Program.

Laura Rosella – Moderator
Associate Director, Education & Training, and Co-Chair, Policy lab, Data Sciences Institute
Professor and Canada Research Chair in Population Health Analytics and Stephen Family Chair in Community Health, Dalla Lana School of Public Health and Faculty of Medicine Department of Laboratory Medicine & Pathobiology, University of Toronto

Prof. Rosella’s research interests include population health and population-based risk tools to support public health planning and public health policy. She holds Scientific Appointments at Vector, Schwartz Reisman Institute for Technology, and ICES. Prof. Rosella has training in statistics, epidemiology, and Public Health Policy.

Posters

Timothy Bender, Alexander Davis, Oleksandr Voznyy, Rachel Zigelstein, DSI Trainees
Virtual Screening for Organic Photovoltaic Materials

Samantha Berek, DSI Graduate Student Fellow
Should zeros count? Modelling the galaxy – globular cluster scaling relation with(out) zero-inflated count models

Madeleine Bonsma, DSI Postdoctoral Fellow
Exploring the geographical equity-efficiency trade-off in cycling infrastructure planning

Muhammad Enrizky Brillian, SUDS Scholar
Benchmarking Generalizability of Few Shots Action Recognition in Videos

Duncan Carruthers-Lay, DSI Graduate Student Fellow
Population genomics analysis of Neisseria gonorrhoeae shows link between population structure, mobile elements & antimicrobial resistance

Chen Chen, DSI Trainee
Longitudinal Cognitive Trajectory Modelling and Phenotyping with Multiple Features Using Health Administrative Data

Hongbo Chen, DSI Graduate Student Fellow
Detecting Stigmatizing Language in Electronic Health Records utilizing In-context Learning

Hriday Chheda, DSI Trainee
Sparse model for predicting hospital acquired delirium

Miranda Doris, DSI Trainee
Satellite data products & machine learning to develop temporally refined historic estimations of fine particulate matter: Applications in health for rural communities

Michaela Drouillard, DSI Trainee
Is It A Banger?: Modelling Danceability using Crowdsourced Metrics

Arturo Esquivel, DSI Trainee
Detecting Stellar Flares in Photometric Data Using Hidden Markov Models

Jianhui Gao, DSI Trainee
Infairness: Reliably Auditing Fairness with Semi-Supervised Inference

Advika Gudi, SUDS Scholar
Overloaded Circuits: Analyzing the Influence of Demographic Factors on Burnout Among Electricians

Harshit Gujral, DSI Graduate Student Fellow
Emerging Evidence for the Impact of Electric Vehicle Sales on Childhood Asthma. Can ZEV Mandates Help?

(Jessie) Ting Guo, DSI Trainee
White matter injury, white matter disconnections and neurodevelopmental outcomes in infants with congenital heart disease

Bushra Haque, DSI Trainee
HAWK-EYE: A high-throughput tool assessing exon skipping eligibility for antisense oligonucleotide treatments of rare genetic diseases

Yi Yue Jiang, DSI Trainee
Changes in T-Cell Repertoire During High-Risk Neuroblastoma Therapy: A Report from the Children’s Oncology Group

Grier Jones, DSI Trainee
Near-term Quantum Algorithms and Error Correction for Molecular Property Predictions

Sooyeon Kim, DSI Trainee
Effect of forest management on insurable wildfire risks in Northern Ontario

Zeenat Ladak, DSI Trainee
Equity factors, adequate prenatal care, and postpartum emergency department use among birthing individuals and their newborns in Ontario

Christie Lau, DSI Graduate Student Fellow
Discrepancies in single-cell sequencing gene expression linked to RNA abundance

Salaar Liaqat, DSI Graduate Student Fellow
Promoting Engagement in Remote Patient Monitoring Using Asynchronous Messaging

Bryant Lim, DSI Trainee
Trial Files: leveraging large language models to generate clinical trial summaries

Tianyi Liu, DSI Trainee
Representative Gene Selection for scRNA-seq Data

Zunaira Mehmood, DSI Trainee
Childhood-onset Systemic Lupus Erythematosus: Pregnancy and Birth Outcomes in Ontario

Sarah Paleczny, Saif Rjaibi, and Chris Brogly, DSI Trainees
Access to key data sources for understanding how recreational cannabis legalization has impacted poly-substance use, injury, and mental health in Canada

Smit Patel, DSI Trainee
Predicting the Onset of Agitation in People with Dementia

Delaram Pouyabahar, DSI Graduate Student Fellow
Modeling sources of variation in single-cell RNA-seq maps

Shivesh Prakash, SUDS Scholar
Development of deep learning model for accelerating chemical reaction discovery

Eric Sanders, DSI Graduate Student Fellow
Colocalization analysis of sex-dependent traits

Xiao Shang, DSI Trainee
Accurate Inverse Process Optimization Framework in Laser Directed Energy Deposition Using Machine Learning

Xiaochuan Shi, DSI Trainee
Simultaneous estimation of multiple treatment effects from observational studies

Yaqi Shi, DSI Trainee
Efficient Inference After Prediction: Extending Prediction-Based Methods

Faisal Shaik, SUDS Scholar
Development of High-Precision Deep Learning Models for Image-Based Spatial Omics Analysis of Chromosome Structure

Jiayi Sun, SUDS Scholar
Serum 25-hydroxyvitamin D and cancer risk in Canada: a prospective cohort study using the Canadian Health Measures Survey

Katherine Tamminen & Rylan Curtis, DSI Researchers
Critically Examining the Use of Generative AI Images and Visual Qualitative Methods

Yuan Tian, DSI Trainee
Enhancing Gene-Based Association Testing leveraging ML-Derived Surrogate Phenotypes from EHRs

Mike Walmsley, DSI Trainee
ZooTasks: a model-in-the-loop annotation platform for citizen science

Harmoni Watson, DSI Trainee
Maternal attachment, maternal sensitivity, and child socio-emotional and cognitive development: A mediation model

Rachel Yen, DSI Trainee
Just Your Type: Exploring Positive Activity Fit on Follow-Up Mood Moderated by Baseline Mood

Mete Yuksel, DSI Graduate Student Fellow
A (null) model for the evolution of the recombination landscape

Haochi Zhang, DSI Trainee
A Machine Learning Derived Patient Vulnerability Alert To Enhance Proactive Psychosocial Oncology Care

Rongqian Zhang, DSI Graduate Student Fellow
SAN: mitigating spatial covariance heterogeneity in cortical thickness data collected from multiple scanners or sites

See the DSI Research Day 2023 schedule here

October 1, 2024
9:30 a.m. to 5:00 p.m.
In-person
Data Sciences Institute 10th Floor, 700 University Avenue
Toronto, ON

Register Here

October 1, 2024
9:30 am -5:00 pm
DSI 10th floor Seminar Room, 700 University Avenue

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