Data Sciences Institute

Data Sciences Institute hosts networking event with newly upskilled talent and top employers

by Andrea Smitko

The Data Sciences Institute (DSI) — a central hub and incubator for data science research, training and partnerships at U of T — hummed with excitement as participants from the first two cohorts of its new Data Science and Machine Learning Software Foundations Certificates met representatives from several organizations during an engaging in-person employer networking event.

Nearly 50 participants seized the opportunity to meet and mingle with their peers, as well as make connections with prospective employers.

With the financial support of Upskill Canada, powered by Palette Skills and the Government of Canada, the DSI Certificates are 16-week part-time intensive offerings. The Certificates are designed to train and upskill working professionals with three or more years of experience for careers in data analytics and applied machine learning.

“We just launched our Certificates a few months ago and we have had over 400 applications and over 200 participants and it is just growing — there is such a need in the community for this work,” said Lisa Strug, academic director of the DSI and professor in the Departments of Statistical Sciences and Computer Science and the Division of Biostatistics, in her opening remarks.

“These Certificates are very unique because we’ve developed them in concert with industry, so we’re making sure that the tools everybody receives are the tools that are actually needed to solve the problems that we’re seeing out there in the real world.”

Designed to be accessible and to build a more inclusive workforce, these Certificates aim to support diversifying the industry. From the first cohort, 90 per cent of participants belong to at least one underrepresented group.

The Certificates include job readiness training dedicated to career advancement and offer valuable coaching in job-seeking skills such as resume writing, interview preparation and networking.

“I really enjoyed the Certificate. Everything included in it was great. There was time to learn and to put that learning into practice,” said Certificate participant, Niyaz Nazari. “All of the associates were very professional, and I really enjoyed the job search courses. I needed to learn those soft skills. The theory is not enough, so that helped a lot.”

As part of its commitment to employment training, the DSI’s goal is for 75 per cent of participants to obtain a new role within six months of completing the Certificate.

“That’s why events like these are so important. To achieve this goal, we need to facilitate connections between organizations looking for talent with the in-demand skills we are teaching through these certificates,” said Strug.

The event welcomed nine organizations looking to hire new talent in the data sciences, including Accenture, Ontario Digital Services, Children’s Aid Society of Toronto, MPAC, Ontario Health, SOCAN, MunichRe, Norton Rose Fulbright, and Yorkville University. Employers were positioned in the DSI’s event space and attendees moved throughout asking questions, pitching their skills, and inquiring about the company and potential employment opportunities.

“Of all the talks I’ve given and events I’ve been a part of, I enjoy this audience the most,” said Tristan Walsh of MunichRe. “It’s all really positive. There’s such a strong level of engagement and great insight. It’s good to see people learning and growing, and it’s so great to meet people in person.”

“The Certificate was a great experience. I want to go back and do another course,” said program participant, Ahmed Alhuraibi Alamoudi. “It was very valuable, and now I can develop a roadmap so I can improve and transition into data science and hopefully do a co-op or an internship so I can practice what I’ve learned.”

 

To join our next event and meet accomplished professionals with data science and machine learning skills to grow your team, please contact dsi.partnerships@utoronto.ca

Data Sciences Institute conference explores the future of virtual reality

by Andrea Smitko

The Data Sciences Institute (DSI) — U of T’s multidisciplinary hub for data science innovation and collaboration — recently hosted “Questioning Reality: Explorations of Virtual Reality (VR) and our Social Future,” a three-day conference where leading scholars, industry professionals, and VR enthusiasts gathered to discuss the future of VR and its impact on social interactions.

The conference  led by the DSI’s Bree McEwan, an associate professor in the Institute for Communication, Culture, and Information Technology (ICCIT) at the University of Toronto Mississauga and Sun Joo (Grace) Ahn, director of the Center for Advanced Computer-Human Ecosystems and professor at the University of Georgia featured a series of engaging discussions, presentations and networking opportunities.

Programmed with the goal of shaping a social interaction-informed agenda for the next research cycle on VR, the event focused on exploring social interactions in mediated environments, including VR, augmented reality (AR), extended reality (XR), and mixed realities (MR).

“This event is an extension of the DSI’s mission to bring the data sciences across industries together to drive social change and work on a concept of social interaction across a variety of realities,” said McEwan. “We’ve brought together not only the academics but also industry professionals to hear their ideas about the potential future of this area of research.”

With the intention of sparking dialogue and fostering meaningful connections, the event was kept to 40 attendees, which allowed for an atmosphere that promoted relationship building, a free flow of ideas and many key opportunities for cross-collaboration.

“Everybody in attendance is interested in social interactions, but across a different range of media or technologies,” said Ahn at the event.

“Each attendee represents a piece of the question: how do people interact in virtual environments using different devices — it could be video games, virtual reality, social media, XR. All of the conversations over the next few days should reveal the kinds of questions we should be asking in the next phase of research: What are the important and critical questions that will push forward the research for the next five or 10 years as an output?”

The conference began on Thursday afternoon with introductions and a keynote presentation on communication in VR/AR by Professor Lynn Miller of the University of Southern California.

In a talk entitled Interpersonal Science in Space and Time: Advancing (and Learning from) Emerging Synchronous Virtual (and “Real”) Worlds, Miller spoke about the importance of understanding and improving social interactions in both virtual and real-world contexts.

On the second day, attendees participated in a series of collaborative exercises and lightning talks on cutting-edge research, brainstormed “blue sky” ideas, and explored forthcoming challenges from privacy concerns to the democratization of VR experiences.

In the afternoon, Shalini De Mello, director of research and distinguished research scientist at NVIDIA, delivered the keynote talk Democratizing Telepresence with AI-Mediated Photoreal Avatar Creation, where she spoke about the exciting field of AI-mediated reality and the intersection of technology with human communication and interaction.

The day also featured an industry panel discussion with leaders Reality Prime, Meta Reality Labs, Engage XR and JP Morgan Chase. Panelists spoke about the important relationship between business and research, and the challenges faced and opportunities available when partnering on future projects.

I would really love to see, not just online schools but also in-person schools, create an ecosystem with social VR that allows students to feel more engaged with content socialization, because our world is shifting and changing,” said Maxwell McGee of Engage XR and Post University. “It’s not as easy as it once was to travel halfway across the world to your dream university or college. I would like to see more ecosystems created to increase those connections where they otherwise might not be available.” 

The last day included a session devoted to forecasting for the future and a final keynote presentation by Tony Liao, associate professor at the University of Houston, Moving Across and Between Realities: An Agenda for the Next Wave of Social XR Research, in which he emphasized the critical need for responsible and thoughtful development of artificial intelligence (AI) technologies as we navigate the intersection of virtual reality and our social future. Liao also noted that the Questioning Reality conference served as a potentially field-configuring event, and that the discussions that took place over its three days may shape the field and direction of research for years to come.

The Questioning Reality conference was supported by the Alfred P. Sloan Foundation, a not-for-profit, mission-driven grantmaking institution dedicated to improving the welfare of all through the advancement of scientific knowledge. The grant was awarded to the DSI to delve into VR technology and its profound implications for human interaction and communication.

“VR and AR technologies have the potential to reshape how we interact and collaborate as individuals, groups and as a society,” said Josh Greenberg, program director for the Sloan Foundation. “We’re very proud to fund this innovative work through the DSI and to support the advancement of this research that will help to inform the responsible development of this influential technology.”

Discussions from the conference will be reflected in a new edition of Debates in Digital Media focused on virtual reality. The Sloan Foundation will also fund five mini-grant research projects, each designed to propel the field forward through innovative research endeavors. The Questioning Reality conference and Sloan Foundation grant serve as a beacon of support and recognition for the DSI’s commitment to pushing the boundaries of knowledge and innovation in the data sciences. 

DSI Welcomes Undergraduate Scholars to the Summer Undergraduate Data Science Program

by Sara Elhawash

The Data Sciences Institute (DSI) is thrilled to welcome 38 undergraduate students from across Canada for an immersive data sciences research experience through the Summer Undergraduate Data Science (SUDS) research opportunity. 

SUDS Opportunities offer students the experience to apply data science methodologies and tools across diverse disciplines. Projects range from research on the robustness for machine learning models, to commercial determinants of health in online gaming, mass extinctions, nocturnal behaviour, sleep modeling, neural systems, and searching for stellar streams in the milky way. SUDS Scholars are supervised by DSI member researchers across U of T and external funding partners. Alongside their research projects, SUDS Scholars have access to a comprehensive suite of data science skills, networking events, and professional development opportunities. 

The programming for SUDS Scholars commences the week of May 6 with the DSI Data Science Bootcamp, where Scholars will gain proficiency in data science skills including Unix Shell, R, Python, and machine learning. 

Advika Gudi, a SUDS Scholar from U of T , expressed her excitement for the program, stating, “I’m looking forward to using data to tell a story – by identifying trends and measuring the impact of policies, to ultimately improve policy outcomes on society is incredibly motivating for me.”   

Rachel Way, another SUDS Scholar, will be working with Professor Spike Lee, Rotman School of Management on the project Automated Text Analysis of Fake News and Biased News. This project aims to analyze approximately 7 million news articles from around 500 media outlets to discern differences between fake news and real news in terms of moral themes, cognitive styles, antiscience attitudes, emotional valence, and other psychological characteristics. 

“The SUDS Scholar will apply automated text analysis and machine learning techniques to these articles in order to identify linguistic patterns and biases depending on how fake or real and how left-leaning or right-leaning the media outlet is,” says Professor Lee. 

“I have a passion for social data science. I am fascinated by the ability to use data to answer pressing questions in the social sciences,” says Way. 

The DSI’s cohort programming includes the Data Science@Work Series, where representatives from the private sector and government organizations share data science applications in the workplace. The program culminates in August with the DSI Showcase, during which SUDS Scholars present their research findings. 

“Our SUDS Scholars benefit from acquiring data science expertise and professional growth opportunities. We are enthusiastic about the prospect of inspiring these students and, hopefully, launching their careers in data science,” says Professor Laura Rosella, DSI Associate Director of Education and Training.   

SUDS offers students a valuable pathway to engage in high-quality and enriching data science learning, serving as stepping stone for students aspiring to build careers in data science. 

See the full list of 2024 Scholars, Supervisors and research opportunities here 

DSI and TISS partner to seed research to advance wearable health technology

by Sara Elhawash

Wearable devices have long been praised as the future of healthcare, fitness tracking, and athletics. However, the reliability of these devices has been hampered by the presence of motion artifacts, which greatly diminish the quality of data collected. 

The Data Sciences Institute (DSI) and the Tanenbaum Institute for Science in Sport (TISS) at the University of Toronto are pleased to award a Catalyst Grant for research in the Development of Convolutional Neural Network for Motion Artifact Mitigation in Wearable PPG Devices. Co-Led by Professors Daniel Franklin (Institute of Biomedical Engineering, Temerity Faculty of Medicine, University of Toronto) and Chris McIntosh (Department of Medical Biophysics, Temerity Faculty of Medicine and University Health Network), the project aims to revolutionize athletics and sports medicine by integrating novel sensors with advanced machine learning algorithms. 

The researchers propose a novel approach to overcome motion artifacts in wearable devices by enabling real-time motion artifact cancellation in optical wearables. This includes the development of a multimodal sensor coupled with deep learning models. The sensor will combine force and multiwavelength optical measurements to capture relative motion at the sensor interface, addressing a critical limitation of current wearable devices. 

“Conventional wearable devices capture global motion, but our approach focuses on capturing relative motion at the sensor-skin interface, which is crucial for accurate data interpretation. Wearable technologies offer a unique glimpse into patient function and biology outside of episodes of care. If AI is the present, wearables with AI are the next frontier,” says Professor Daniel Franklin. 
 
The research project will progress through several phases, including controlled lab experiments and real-world examples of motion. By collecting a novel multi-modal motion artifact dataset, the team aims to develop a robust algorithm for real-time optical motion artifact cancellation. 

“We are thrilled to partner with the DSI to award this seed grant. This project has the potential to significantly advance wearable health monitoring technologies for applications to the healthcare, fitness, and sports sectors,” says Dr. Ira Jacobs, Director of the Tanenbaum Institute for Science in Sport. 

The implications of this research extend beyond healthcare into consumer health, sports, and athletics. By enhancing the usability and interpretability of wearable device datasets, the project promises to advance remote health management and athletic performance tracking. 

“We envision a future where wearable devices provide more accurate and actionable insights, leading to improved patient care and athletic performance,” added Professor McIntosh. 

The DSI and TISS partner to co-sponsor Catalyst Grants focused on innovative and novel data science in sport and sport analytics.  

DSI and T-CAIREM co-fund two Catalyst Grants that are breaking bias in medical research and supporting children with complex communication needs

by Sara Elhawash

The Data Sciences Institute (DSI) and the Temerty Centre for AI Research and Education in Medicine (T-CAIREM) at the University of Toronto join efforts for the second consecutive year to co-fund two 2024 Catalyst Grant Awards focused on innovative and novel data science methodologies in medicine and health. 

Each catalyst grant provides up to $100,000 in seed funding for multidisciplinary researchers forming Collaborative Research Teams (CRTs) that are developing novel statistical or computational tools that address important societal needs. 

“These jointly funded catalyst grants are directed at highly innovative initiatives that have the potential to transform healthcare with data science, and this year’s winners are no exception,” says Muhammad Mamdani, executive director T-CAIREM. “It’s rewarding to see initiatives that not only focus on specific segments of our population to improve their quality of life but also those that have far reaching implications for society at large.” 

Examining biases due to confounders and colliders in observational health data using individual-based simulation models

Sharmistha Mishra (St. Michael’s Hospital, Unity Health Toronto and Rafal Kustra (Dalla Lana School of Public Health, University of Toronto)  

In the realm of medical research, observational studies leveraging large health-administrative datasets are crucial. However, bias in the data, including residual confounding and collider bias, can produce misleading results, potentially skewing policy decisions, resource allocation, and clinical management.  

This research aims to enhance public health outcomes during infectious disease outbreaks by employing simulation modeling combined with causal inference and statistical learning methods to identify and address different types of biases that could undermine inference drawn studies of health using observational data. 

Specifically, the researchers plan to generate synthetic datasets using simulation models that replicate the complex dynamics of the 2022 Mpox outbreak in Toronto, in collaboration with clinicians, public health teams, and community-based organizations. They intend to use statistical learning methods to predict how big the problem of residual confounding and collider biases could get when inferring risk factors and the effectiveness of interventions during an evolving outbreak. They will then pilot-test analytic approaches to reduce these biases. 

“This work has the potential for applicability across health conditions by helping to improve validity in estimating risks and intervention impact,” says Professor Mishra. 

Decoding unintelligible speech: a conversational context-aware assistive technology for children with complex communication needs (CCN) 

Tom Chau (Holland Bloorview Kids Rehabilitation Hospital) and Monika Molnar (Temerty Faculty of Medicine, Department of Speech-Language Pathology, University of Toronto)  

Children with CCN often prefer to vocalize, but their sounds are typically unintelligible to those unfamiliar with them. They are often excluded from fully participating in education, society, and eventual employment. 

This Catalyst Grant proposal is dedicated to helping children with complex communication needs (CCN), potentially leading to the development of assistive devices. 

The research team plan to utilize machine learning to decode the unintelligible speech of these children using an existing audio-video dataset of speech samples. This project could pave the way for the development of artificial intelligence-driven electronic devices tailored for children with CCN. 

“There are currently no assistive technologies that can accurately decode their speech sounds,” explains Professor Chau. “As a result, children with CCN remain excluded from full participation in education, society, and eventual employment.” 

The researchers hope this project will accelerate the impact of data sciences in the fields of rehabilitation and biomedical engineering, driving positive social change for children with CCN. 

The DSI’s Catalyst Grants, co-funded by T-CAIREM, play a crucial role in supporting these research projects by providing the essential seed funding and fostering the collaboration among research teams needed to realize this impactful work and apply for external funding in the future.