This summer, YFile examines how 91亚色-led researchers move ideas into impact through the Connected Minds Prototyping Awards. This series shows innovation in practice 鈥� how socially responsible technologies are tested in real-world settings and how this work drives meaningful change.

As Canada's population ages and demand for care continues to grow, researchers are exploring how technology can help older adults live more independently while easing pressure on caregivers.  

An emerging area of focus is social robotics, a field dedicated to developing robots capable of interacting with people in natural, human-centred ways. Unlike industrial robots designed for manufacturing, social robots can communicate, respond to social cues and assist in settings such as homes, hospitals and long-term care facilities.  

At 91亚色, a team led by聽James Elder, professor聽at the 聽and the Faculty of聽Health聽and 91亚色 Research Chair in Human and Computer Vision,聽is聽exploring how聽social robots聽can better聽interact聽with the people they are designed to support.聽

The project centres on Psibot, a novel robotic vision system designed to help robots perceive and understand the people around them. By drawing inspiration from how humans see and direct their attention, the technology aims to equip robots with social awareness to assist, monitor and interact in more natural ways. 

"Our research explores the potential for robots and AI to work with human caregivers in providing continuous assessments, assistance and care to older adults," says Elder, who also serves the University as director of the Centre for AI & Society. "To fulfill this potential, robots must have a high degree of social intelligence."  

For social robots to be effective, they must be able to detect, recognize and interpret human behaviour and social cues. However, giving robots the visual capabilities to perform these tasks remains a significant challenge. 

Traditional robotic vision systems often face a trade-off: they can either scan a wide area at lower detail or focus closely on a specific person or object. Psibot tackles this challenge by combining broad awareness with the ability to focus on specific people and interactions when greater detail is needed. 

Much like people use peripheral vision to stay aware of their surroundings while focusing their attention on a person or activity,聽Psibot聽combines wide-angle cameras with a high-resolution sensor that can rapidly direct its gaze where it is needed most. This allows the robot to聽maintain聽awareness of its environment without losing the ability to closely聽observe聽important interactions.聽

The team has already developed two functioning prototypes, PSIBot 1.0 and PSIBot 2.0, and continues to refine the technology. 

The project received support through the Connected Minds Prototyping Award, which helps researchers move promising ideas closer to real-world testing and deployment. Connected Minds is a multi-million-dollar transdisciplinary research initiative led by 91亚色 and Queen鈥檚 universities that explores the bridge between emerging technology, public health and social justice.  

According to Elder, the funding has been instrumental in advancing this work toward field testing and commercialization opportunities. 

The prototype has significant potential in health care and senior care settings, where social robots could complement human caregivers by monitoring well-being, supporting daily activities and improving access to care. 

Elder also sees promise in their ability to support emotional and social health by identifying changes in social behaviour, such as an increase in isolation, and encouraging residents to participate in activities or connect with others. 

鈥淪ocial robots can serve as escorts, guiding an older adult from place to place within a potentially large facility,鈥� says Elder. 鈥淭his can preserve the mobility of the individual while keeping them safe.鈥� 

 Monitoring changes in mobility over time is another application, where caregivers could receive alerts about potential fall risks and offer earlier interventions when needed. 

As health care systems face growing demands, technologies that support independent living and aging in place may play an increasingly important role in helping older adults maintain their quality of life, says Elder. 

The post How AI-powered social robots could help older adults live more independently appeared first on YFile.

This summer, YFile examines how 91亚色-led researchers move ideas into impact through the Connected Minds Prototyping Awards. This series shows innovation in practice 鈥� how socially responsible technologies are tested in real-world settings and how this work drives meaningful change.

From buttoning a shirt to turning a doorknob, people rely on their hands to perform countless tasks every day. Yet, despite the importance of the human hand, studying how people learn and perform these movements is challenging for researchers.

Traditional methods of tracking hand movements are often expensive, time-consuming and require participants to wear uncomfortable sensors or reflective markers. These techniques often interfere with the natural hand movements researchers attempt to study, rendering the results as ineffective.

At 91亚色, researchers are addressing this challenge through the development of ATHENA (Automatically Tracking Hands Expertly with No Annotations), an AI-powered motion-tracking system that captures natural hand movements without requiring markers, sensors or wearable devices.

The project is led by Jonathan Michaels, assistant professor at the School of Kinesiology and Health Science, alongside Daanish (Dan) Mulla, a postdoctoral fellow and lead researcher on the project.

"We wanted a way to measure natural hand movement as it actually happens, without attaching anything to the person," says Michaels.

Using synchronized video from multiple low-cost cameras and machine-learning algorithms, ATHENA captures footage of a person to map their hand, body and face movements in three dimensions. This open-source software removes the barriers associated with traditional motion capture systems by eliminating costs and tedious setup requirements while upholding accurate measurements.

In validation studies, ATHENA was tested against traditional marker-based technology commonly considered the gold standard in movement science. The results showed strong accuracy across a range of tasks, from simple reaching and grasping to handling objects such as mugs, books, pens and tools.

Ultimately, the team hopes ATHENA will become a tool for those seeking to better understand how people move, learn new skills and recover from injury.

Now fully functional and freely available to researchers, ATHENA鈥檚 success moving from concept to real-world application was driven in part by the Connected Minds Prototyping Award.

The award is designed to support prototype developments aligned with the mandate of Connected Minds, a multi-million-dollar transdisciplinary research initiative led by 91亚色 and Queen鈥檚 universities that explores the bridge between emerging technology, public health and social justice.

Funding for ATHENA enabled the team to develop portable versions of the system that can be transported and deployed outside the laboratory. These mobile setups have already been used in autism clinics in Israel and the GTA, expanding the tool鈥檚 reach beyond traditional research environments.

"The award was instrumental in moving ATHENA from a validated proof-of-concept into a tool that can actually be used out in the world," says Michaels.

Recipients of the award also receive support from other sources and partners. For ATHENA鈥檚 team, it fostered a collaboration with 91亚色's IP Innovation Clinic for guidance on developing a strategy to maximize adoption while keeping it freely available.

By remaining open source, affordable and developed in collaboration with the communities and clinics that use it, Michaels says ATHENA reflects Connected Minds' goal of creating accessible, socially responsible technology.

Through the prototyping process, the team learned that developing a useful technology requires more than proving it works.

"The hardest part of building a useful tool is often not the core idea, but making it robust, easy and trustworthy enough that other people will actually adopt it," says Michaels.

Navigating the challenges of moving from controlled laboratory environments to clinics and community settings, where lighting conditions vary, people move more freely and privacy considerations become essential, he says.

Because the tool operates entirely without bulky tracking equipment, it can capture movement in more natural settings and offer a more comfortable experience for participants. The comfort and ability to track naturalistic movements translates well with respect to ATHENA's most promising application in health care and clinical research.

An example of this is a collaboration with the Freud Lab at 91亚色 where researchers are using ATHENA to study how children move during activities such as building with LEGO. The goal is to identify patterns that could support earlier and more objective identification of autism and other neurodevelopmental conditions.

Michaels says plans are underway to expand ATHENA's capabilities, such as integrating eye tracking, object tracking and multi-person tracking. And, by working with additional clinical and educational partners, the team hopes to broaden adoption while maintaining the platform's open-source model.

"Our goal is for ATHENA to become a broadly used, trusted and freely available resource that helps the research and clinical community better understand human dexterity and improve lives," says Michaels.

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AI is increasingly influencing research, industry and everyday life, prompting new opportunities alongside important questions about its development, application and impact.

In recognition of AI Appreciation Day, this special edition of YFile highlights research and innovation in AI across the 91亚色 community.

The stories within reflect the diverse ways researchers and alumni are engaging with AI technologies to address complex challenges and advance knowledge. Topics range from efforts to make AI tools safer for youth mental health support and AI developments in cancer care, to emerging applications in geophysics and real estate technology.

These stories illustrate how members of the 91亚色 community are exploring AI across disciplines while considering the importance of human expertise, as well as critical thinking and oversight in shaping how these technologies are developed and used.

While this special issue explores advances in AI, all articles were researched, written and edited by people, reflecting the essential role of human insight in journalism.

Featured stories include:

How 91亚色 researchers are using AI to support cancer care
Can AI help clinicians spend less time reviewing scans and more time caring for patients? 91亚色 researcher Ali Sadeghi-Naini is developing tools designed to support faster, more informed decision-making in cancer care.

Can AI be trusted to assess climate risks? A 91亚色 study investigates
A 91亚色 study explores how AI can help communities prepare for climate-related hazards by investigating whether emerging tools are ready for real-world applications.

91亚色 prof explores AI safeguards for youth mental health
AI is becoming a trusted source of advice for many young people. Postdoctoral researcher Abeer Badawi is exploring what that means for their mental health 鈥� and how to prevent harm.

Schulich alumni scale AI real estate investment tool聽
Learn how three Schulich School of Business graduates used 91亚色 mentorship and connections to launch Leni, an AI-powered tool that supports real estate investors in their decision making.

Know someone making an impact at 91亚色? Share your story ideas with YFile.

The post AI innovation at 91亚色 U starts with human intelligence appeared first on YFile.

In oncology clinics, diagnosing disease, monitoring treatment response and tracking tumour growth often begin with a meticulous review of medical images. For oncologists and radiologists, this can mean spending hours measuring tumours and comparing scans to understand how a patient's cancer has changed over time.

Much of that work is still done manually, even when clinicians are carrying out many of the same assessments across large numbers of cases. "There are many occasions where the time of oncologists and radiologists is spent reviewing cases that are very similar," says Sadeghi-Naini.

Spending significant time reviewing scans and performing routine assessments, he says, leaves less time for patients who require more urgent attention.

Sadeghi-Naini and his team at the QUANTIMB Lab are working to change that.

The 91亚色-based lab, led by Sadeghi-Naini, develops AI-powered imaging tools to support cancer care with a focus on helping clinicians process medical scans more efficiently.

鈥淭he idea is to automate things 鈥� to detect the location of the disease, quantify it and generate a report so the clinician can quickly review it,鈥� says Sadeghi-Naini, who teaches in the .

Rather than replacing clinical expertise, the goal is to develop AI tools that act as decision support systems, helping care providers assess scans and prioritize care. The tools are trained using large collections of medical scans, allowing them to identify patterns associated with disease progression and treatment response, which can then be flagged for clinical review.

One area of the lab's work focuses on monitoring brain tumours using MRI scans. For some patients whose cancer has spread to the brain, disease may appear as numerous small lesions scattered throughout the organ. In some cases, Sadeghi-Naini says, patients may have 10, 20 or 30 tumours that must be identified and monitored individually over time to determine whether treatment is working.

To help with that task, the lab has developed AI models that can analyze MRI scans, identifying and tracking small cancerous growths across a series of scans. The technology can automate much of that work and generate information to support treatment decisions, reducing the time clinicians spend manually locating and measuring each tumour over successive scans.

Another long-running project examines how tumours respond to treatment. For patients undergoing chemotherapy, one challenge is determining early on whether a tumour is responding to the drug. In some cases, this may only become clear after months of treatment, by which point valuable time and opportunities to adjust a patient's care may have been lost.

Using ultrasound data, Sadeghi-Naini and his team train AI models to look for biological changes that signal whether tumour cells are dying. By assisting in identifying those signals earlier than conventional monitoring approaches, the technology could give clinicians faster insight into whether a treatment is working. Detecting those changes earlier could help determine whether a different approach is needed.

鈥淚f a patient can be identified as not responding as early as possible, that spares months of ineffective chemotherapy and unnecessary side effects,鈥� says Sadeghi-Naini.

Although the projects focus on different clinical challenges, they are built around the same idea: using AI to extract useful information from medical images and help clinicians make decisions more quickly.

Across these projects, collaboration and human insight play a central role. The lab works closely with hospitals and clinicians, including researchers at Sunnybrook Health Sciences Centre, to access patient data, test new technologies and ensure the tools being developed address real-world clinical needs.

Feedback and guidance from clinical collaborators on the brain tumour monitoring technology have already been positive, says Sadeghi-Naini, who notes that some have expressed interest in using it as a support tool.

The lab is also designing interfaces that make the technology easier for practitioners to use, recognizing that ease of use is key to adoption in real-world settings.

Collaboration with those working directly in the field also helps accelerate the work. The ultrasound project, for example, has advanced to a clinical trial, a milestone that reflects growing interest among health care experts in evaluating the technology.

Although much of his work involves advanced technologies, Sadeghi-Naini says the motivation behind it is simple: helping patients receive the right care at the right time. Tools that monitor disease more efficiently, or determine sooner whether a treatment is working, could improve decision-making throughout the course of treatment and offer more time to focus on patient care.

"At the end of the day, this clinician time can be spent on somebody who actually urgently needs it," he says.

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Drawing on recent research findings, usage statistics and her own work, Badawi has observed that chatbot use is increasing, with many people turning to these tools not only for information and practical assistance, but also for advice, emotional guidance and support with personal decisions.

Badawi's interest in the issue grew out of her work with Kids Help Phone, Canada's national 24/7 e-mental health service for young people. While working at the Vector Institute, she gained exposure to the mental health challenges facing youth and saw firsthand how digital tools were increasingly being used to provide support.

The experience led her to pursue postdoctoral research at 91亚色 through the Connected Minds program with a focus on mental health and AI safety. Supervised by Assistant Professor Elham Dolatabadi and Laleh Seyyed-Kalantari from the , as well as Frank Rudzicz of Dalhousie University, Badawi鈥檚 research finds that youth, in particular, are turning to AI systems for help navigating everyday challenges, relationships and emotional concerns 鈥� even when they may not explicitly describe those interactions as mental health support.

Badawi's findings reinforced a growing concern about the role AI plays in people's lives. Chatbots, such as ChatGPT, are increasingly serving roles once filled by family members, friends and other trusted sources. Whether youth describe it that way or not, Badawi believes many of these exchanges have begun filling an emotional support role in people's lives.

鈥淓ven if they don't define it as mental health support, they are still using it as a type of mental health support,鈥� she says.

The concern, Badawi says, is that AI chatbots were not designed to serve that purpose.

Unlike therapists and other mental health professionals, general purpose large language models like ChatGPT are not designed to provide clinical care. As a result, users may receive advice or validation before sufficient context is gathered or alternative perspectives are explored.

鈥淵ou can end up with a system that always agrees with you,鈥� she says. 鈥淚t doesn't challenge you or ask questions in the same way a person would.鈥�

That dynamic can have consequences, she notes. Someone discussing a conflict with family, for example, may receive responses that validate their feelings without fully exploring the situation or offering alternative perspectives. Over time, Badawi worries that constant affirmation could contribute to overconfidence, one-sided thinking and an increasing reliance on AI systems.

Her research examines what she and her colleagues call 鈥� a potential pattern of interaction in which repeated reliance on AI may shift reflection, coping, emotional regulation and decision-making away from individuals and toward AI systems.

The concern, however, extends beyond questions of decision-making or dependence. She worries the same behaviours that encourage people to rely on AI for advice and emotional guidance may, in extreme cases, contribute to more serious harm. Models that consistently validate users, reinforce their perspectives and foster emotional attachment can become particularly problematic when people are vulnerable or in distress.

The issue became an important focus for Badawi following reported cases in which AI chatbot interactions were examined in connection with youth suicide. For her, these cases raised urgent questions about how chatbots respond when vulnerable users express distress, form strong emotional attachments to the system or require support beyond what an AI tool can safely provide. They also highlight the importance of designing models that recognize risk and encourage users to seek appropriate human help.

Those cases helped inform a research project supported through OpenAI's AI and Mental Health Grant Program, an initiative aimed at supporting research into how AI systems affect mental health and how they can be designed more safely.

As principal investigator, Badawi is leading Preventing Cognitive Atrophy in LLM Mental Health Support Through Psychometric Evaluation and Therapist-Aligned Design, a project that aims to better understand how AI systems can support mental health while reducing the risk of emotional dependency.

The team is developing new ways to measure how AI behaves in emotionally sensitive conversations. The goal is to design technology that will encourage users to seek help from people they trust and provide resources and responses that support independent coping and problem-solving.

To do that, researchers are analyzing conversations between users and chatbots and are working with experts in psychology and mental health to examine whether models gather sufficient context, encourage independent decicion-making, ask appropriate clarifying questions and respond with empathy.

One goal is to identify conversational patterns that can steer interactions into increasingly risky territory. Ultimately, Badawi hopes the work will help create safeguards that prevent AI systems from reinforcing harmful ideas, fostering unhealthy emotional attachment or encouraging dependence.

The obstacles, however, extend beyond the technology itself.

With more than a decade of experience working at the intersection of AI and health care, Badawi has collaborated with clinicians, mental health professionals and researchers across disciplines. Those experiences, she says, have underscored the importance of collaboration while also revealing how difficult it can be.

One obstacle is determining what a "good" response from an AI system actually looks like. As part of the project, and assess how the models respond in emotionally sensitive situations. Those evaluations help researchers identify the kinds of behaviours they want these tools to emulate 鈥� and those they want to avoid.

But unlike many areas of health care, there is no single correct answer. Different experts can interpret the same interaction in different ways, making it difficult to establish clear standards. A response one psychologist considers appropriate may prompt debate from another, not because either is wrong, Badawi says, but because they are approaching the situation from different perspectives.

鈥淚f humans don't agree, how are you expecting the model to follow a pattern?鈥� she asks.

Despite those challenges, Badawi believes progress is possible. She is also quick to emphasize that AI tools can still provide value.

鈥淲e can鈥檛 stop people from using AI tools,鈥� she says. 鈥淭he question is how to make them safer.鈥�

Her long-term goal is to develop AI-driven tools specifically , with safeguards that recognize when interactions are becoming problematic and encourage users toward reflection, autonomy and real-world sources of support.

鈥淭he real measure of progress is whether AI can recognize danger early, interrupt harmful patterns and connect a vulnerable person to human help before it is too late,鈥� she says.

Ultimately, the objective is simple: people are already using these systems every day. The task now is ensuring they can do so safely.

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is an AI platform built for real estate and asset management co-founded by Gaurav Madani and Arunabh Dastidar, who met as Schulich MBA students in 2017 and graduated together in 2019. The tool鈥檚 third co-founder, Zain Nathoo, is also a Schulich alum.

The platform was created to solve fragmented data challenges in real estate investing by using AI to organize information and provide customizable systems that help investment teams analyze data, automate tasks and make faster decisions. These were challenges both Dastidar and Nathoo encountered while working in real estate investment and helping to manage more than $1 billion in property assets.

Frustrated by delays in financial reports 鈥� which often arrived in spreadsheets weeks late and slowed decision-making 鈥� they turn to Schulich for guidance and support to bring their solution to market.

Early on, the founders brought their idea to Chris Carder, executive director of Schulich's Office of Innovation and Entrepreneurship. Madani recalls approaching Carder, who at the time was alone in the Schulich cafeteria, and sharing the team鈥檚 idea. Carder offered the team direction, facilitated important connections and amplified the company within his own network.

"He was a sounding board, which is what founders need in the early days," Madani says. "Especially in the early days when no one knows you, those kinds of things are really important."

Beyond Carder, the company drew on other forms of support at Schulich. Andre Kuzmicki, retired professor, introduced the team to senior professionals at large Canadian institutions who would become some of Leni's first clients.

As well, Schulich's Entrepreneurial Studies program has partnered with Leni to create student internships.

"Schulich gave us a community of people who believed in what we were building and opened doors that would have been much harder to access on our own," says Dastidar. "That early support was instrumental in helping us gain traction and credibility as we scaled."

While Leni began by connecting industry systems to track performance in real time, it evolved to integrate AI, which became central to its development from 2022 onward.

Today, it helps investment teams evaluate deals, conduct research and automate reporting tasks that would otherwise take days.

Madani says Leni stands out for its focus on accuracy. It is trained to break complex questions into parts, route them across multiple AI models, evaluate whether the responses meet its threshold, and surfaces an answer only when it passes 鈥� along with the reasoning and source data behind it.

"Leni will always treat any output as a hypothesis that needs to be proven," he says.

As the company expands, the relationship with Schulich continues in both directions. Leni's founders now serve as mentors, judges and guest lecturers with Schulich Startups, where they contribute to the same ecosystem that helped them get started.

For students who are thinking about building their own tool, Madani's advice is simple: "No two entrepreneurial journeys look the same," he says, adding that Schulich鈥檚 support was instrumental to Leni鈥檚 success.

With files from Mzwandile Poncana

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After two years of inactivity, the Google Developer Group (GDG) chapter at 91亚色 has been revived by a first-year student focused on hands-on learning and long-term leadership.

Soroush Baraouf, a computer engineering student at the , was appointed by Google's regional program team as the founder and organizer of the newly relaunched GDG on Campus at 91亚色 chapter earlier this year.

Part of a global Google-supported network, GDG chapters are student-run organizations that host workshops, project-based learning experiences and hackathons, giving students hands-on exposure to technologies such as cloud computing and AI. The 91亚色 chapter shut down after previous student leaders graduated or moved into upper-year studies.

Baraouf, who moved to Canada from Iran where he had spent years following the GDG network, hoped to be a part of 91亚色鈥檚 chapter. When he arrived at the University, however, he learned the chapter was inactive 鈥� so he took action to relaunch it.

"I could feel the bulb kind of turn on in my mind," he says. "Maybe I can be the person who can build this community."

Beyond his own ambitions, Baraouf saw a broader need: a stronger technical community that could help 91亚色 students make their work more visible to employers 鈥� especially in a competitive recruitment landscape.

"There are so many students at universities like U of T or Waterloo who just get more exposure simply because they attend those schools," he says. "What I wanted to fix was to create a serious community and do serious stuff so recruiters and employers can understand that people at 91亚色 can also get things done."

The chapter's programming is built around that goal. Rather than hosting speaker panels that students leave with little to show, Baraouf is centring the group on what he calls a builder mindset: workshops that begin with a real problem, guide participants through Google tools like Firebase and Google Cloud Platform, and end with a working project students can add to their portfolios.

First-year students are a particular focus, since many are entering the workforce without practical project experience.

"We want to help people actually build solutions 鈥� real-world stuff that solves real problems that they can showcase," he says.

The chapter's scope extends beyond engineering students. Baraouf sees tools like Google's Gemini AI models and cloud hosting as relevant across disciplines 鈥� for business students exploring fintech ideas, arts students using image generation tools or students who want to build and host a portfolio without a technical background.

"No matter what discipline you're in, what level you're at, there's still something you can do with AI," he says.

To keep the chapter from repeating the previous group's fate, Baraouf has built in structural safeguards. The executive team of approximately 23 students is organized into five groups 鈥� technology, academics, operations, finance, and outreach and growth 鈥� each deliberately staffed with both junior and senior students. If upper-year leaders graduate, there are always newer members ready to step into leadership roles.

The relaunch would not have happened without external support. Professor Jeff Harris helped Baraouf navigate 91亚色's club ratification process, while Adeola Omojola, former student and the previous chapter lead, shared key documents and guidance on the Google application process. Becky Phan, Google's regional program lead for North America, helped guide the Google collaboration.

For Baraouf, long-term success of the program means helping 91亚色 students build a stronger technical profile with employers and creating a club that continues well after he graduates. He envisions the club as one that contributes to students鈥� academic experience by partnering with professors on hands-on course projects.

On July 3, the group hosted the Engineering & AI Innovation (EAII) Case Competition at Google's Toronto headquarters 鈥� an event where students learn how Google is evolving in engineering, and then pitch AI-based solutions to Google engineers for feedback and discussion.

"We set out to prove GDG 91亚色 U is different: a club built on real technical depth, real ambition, real standards," says Baraouf. "Judging by the room that day, we made our case."

Students interested in joining can become members through the chapter's website at .

Executive applications for the current cycle are now closed, but general membership is open and a new round of leadership recruitment is planned for September.

With files from Mzwandile Poncana

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The Feodor Lynen Research Fellowship, awarded by the Alexander von Humboldt Foundation, is a competitive international research program. It connects promising German scholars with established researchers abroad to pursue independent inquiries and build global profile and networks.

Mehltretter is based at Leibniz University Hannover, where he leads the Photogrammetric Computer Vision Group. focuses on AI-driven 3D reconstruction and interpreting visual data 鈥� teaching computers how to see, understand and measure the 3D physical world using cameras and intelligent sensors.

Mehltretter will join 91亚色 on Oct. 1 to collaborate with Shan, a former Humboldt fellow and an expert in dynamics, control and navigation of autonomous systems. The research will focus on projects that combine advanced computer vision with smart sensing systems 鈥� an area of growing importance as industries adopt automation and AI tools.

鈥淒r. Mehltretter鈥檚 work explores areas that align closely with 91亚色鈥檚 strengths in space engineering and autonomous systems,鈥� says Shan, a professor at 91亚色鈥檚 .

Shan鈥檚 research centres on improving how satellites and autonomous systems move, operate and make decisions in challenging environments. He leads work that combines control theory with applications in space missions, robotics and intelligent systems, including contributions to missions such as .

Mehltretter also brings experience in international scientific leadership, including roles with the International Society for Photogrammetry and Remote Sensing and the German Society for Photogrammetry, Remote Sensing and Geoinformation. His fellowship at 91亚色 will contribute to academic exchange, mentorship and the development of graduate students and research teams.

The visiting fellowship also reflects the University鈥檚 commitment to support international collaborations and attract globally mobile talent, with 91亚色鈥檚 Offices of the Associate Vice-President Global and Vice-President Research & Innovation providing matching funds from the Global Research Excellence Seed Fund program.

鈥淧rograms like Humboldt show how 91亚色 continues to attract top international scholars,鈥� says Shan. 鈥淏y strategically investing in global collaboration, the University is strengthening its ability to address complex challenges through innovative, interdisciplinary research.鈥�

The post Humboldt fellow joins 91亚色 U for research collaboration on AI navigation systems appeared first on YFile.

This summer, YFile examines how 91亚色-led researchers move ideas into impact through the Connected Minds Prototyping Awards. This series shows innovation in practice 鈥� how socially responsible technologies are tested in real-world settings and how this work drives meaningful change.

In the field of mental health care, administrative pressures take valuable time away from patient care.

Many independent mental health care providers, including therapists and counsellors, face growing clerical demands. From scheduling and intake forms to documentation and follow-ups, when these responsibilities are managed through fragmented systems it creates inefficiencies for practitioners and patients.

At 91亚色, M. Murat Kristal, professor of operations management and information systems and director of the MBA in technology leadership at the , is working to address this challenge. Kristal is the founder of HazelCare, a digital health platform designed to support mental health practitioners through responsible AI, privacy-by-design principles and human-centred technology.

HazelCare brings together core administrative functions 鈥� including appointment booking, patient onboarding, documentation and communication 鈥� into a single, user-friendly system. The integration of AI tools offers enhanced operations by using natural language processing to support clinical notetaking, predictive analytics to reduce missed appointments and virtual assistants to guide patients through onboarding.

鈥淗azelCare emerged from my long-standing interest in understanding how technology can be used to solve meaningful societal challenges while preserving trust, empathy and human connection,鈥� says Kristal.

Rather than simply digitizing administrative tasks, HazelCare is designed as an AI-enabled practice platform that augments practitioner workflows while preserving the human relationship at the centre of mental health care.

Working alongside Kristal to bring this innovation to market are team members across various disciplines and diverse expertise. Longtime Schulich instructor Altay Aksulu, a solutions portfolio manager with the Ontario Public Service, brings industry experience to the team, helping ensure the platform meets real-world needs. Alex Volkov, a 91亚色 computer science graduate and senior software developer, leads the platform鈥檚 technical direction and architecture, bringing more than 15 years of experience building full-stack applications across government, enterprise and SaaS environments.

Murat and his team received the Phase 1 Connected Minds Prototyping Award, which provides up to $20,000 to support early-stage prototype development. Connected Minds is a $318.4-million transdisciplinary research program led by 91亚色 in partnership with Queen's University focused on the study of human-AI interactions to ensure future technologies are ethical, healthy and equitable.

Backed by the Canada First Research Excellence Fund and a network of more than 50 industry, hospital and community partners, the program funds transdisciplinary teams to move ideas beyond research into tangible prototypes though these awards.

With this support, Kristal's team has advanced HazelCare from a concept into a functional, pilot-ready platform. The funding enabled the development of core features, system architecture and testing processes.

鈥淏eyond the financial support, the award provided important validation of the project鈥檚 vision and potential societal impact,鈥� says Kristal.

Through the prototyping process, the team learned the value of designing technology around real user workflows. In a complex, highly regulated field like health care, this means balancing usability, privacy, security and regulatory requirements while ensuring the platform remains intuitive for both practitioners and patients. The result is a system that supports end-to-end workflows and is positioned for pilot testing.

By reducing administrative strain on independent providers, HazelCare could help expand access to mental health services, enabling practitioners to take on more clients while maintaining quality of care.

While practitioners benefit from more integrated workflows, the impact is also felt by patients. Instead of navigating multiple platforms to book appointments, complete intake and receive updates, patients can move through a more streamlined process from initial contact through ongoing engagement.

Kristal says HazelCare bridges new technologies and the human-centred nature of care resulting in a more connected and equitable mental health care system.

Moving toward implementation, the team will test HazelCare by working with practitioners to evaluate how it performs in real-world settings. Future enhancements to the platform include improving practitioner support tools, strengthening analytics and exploring responsible AI additions.

鈥淥ur goal is not simply to build software, but to demonstrate how responsible AI can strengthen the relationship between practitioners and patients while expanding access to mental health care,鈥� says Kristal.

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John Brown, a BEng mechanical engineering graduate who also completed a certificate in entrepreneurship, and Mehakdeep Singh, who earned a BSc (Honours) in computer science, are the 2026 recipients of the Bergeron Medal.

The award is presented by Lassonde and recognizes top graduating students who have demonstrated outstanding entrepreneurial achievement throughout their studies by applying their ideas through research, design and real-world work.

About the recipients

John Brown
Brown came to the University as a member of the 91亚色 Lions men鈥檚 basketball team. Off the court, he explored microfluidics projects, designing devices that produce tiny droplets to mimic cellular interactions. This focus has potential applications in medical and biological research.

鈥淚 do all this for a simple reason,鈥� he says. 鈥淚 want to understand how things work and find a way to leave some kind of impact on society while I am at it.鈥�

After three years on the varsity basketball team, Brown turned his attention to academic efforts, taking on research opportunities, securing grants and stepping into a leadership role with Lassonde Motorsports, a student-led Formula SAE team that designs, builds and competes with a race car. In his final year, he led the body and aerodynamics team as the club built its own chassis for the first time.

Brown finished top of his graduating class while building a record that included two conference papers and a patent filing on polymer science and microfluidic processes.

He also contributed to student-led innovation through initiatives such as TranReality, a virtual reality platform that helps new employees bridge the gap between knowledge and practical, on-the-job training.

Brown credits the scope of his accomplishments to the flexibility of 91亚色鈥檚 learning environment. 鈥�91亚色 gave me room to be a few things at once,鈥� Brown says. 鈥淣ot many schools would have let me be an athlete, a researcher and a builder at the same time.鈥�

He says balancing these roles wasn't always easy, making this recognition especially meaningful. 鈥淚 am honoured to receive this,鈥� Brown says of the Bergeron Medal. 鈥淚 think it reflects the effort I put into leaving a small mark on Lassonde, through seasons that ended in losses, research that failed more than it worked and plenty of late nights that went nowhere.鈥�

Brown sees the medal as a starting point rather than a culmination, saying it 鈥減oints toward where I am headed next, and I am at the start of that path, not the end. That is the part I am most excited about.鈥�

Now a mechanical engineering specialist at Ekstera, an early-stage energy startup, Brown hopes to learn firsthand about how companies are built. While he is also working toward his professional engineering licence, his longer-term goal is to found a company of his own.

Mehakdeep Singh
Singh joined 91亚色 with an interest in AI and machine learning. Through his studies, he became increasingly focused on how these systems often operate as 鈥渂lack boxes,鈥� where the inner workings and decision-making processes are not easily visible or fully understood by non-experts.

鈥淭his sparked my interest in understanding how AI systems function and how governance, accountability and transparency can be strengthened to support their responsible development and use,鈥� he says.

Singh explored these questions through a combination of research opportunities and experiential learning, including collaborating with other students during UNHack to apply his ideas to today's challenges. His academic achievements were also recognized through scholarships, including the Lassonde Entrance Scholarship and several continuing student awards.

鈥淭hese experiences allowed me to grow both academically and personally while building skills that will continue to serve me in my future career,鈥� he says.

Singh credits access to opportunities and an academic environment that enabled practical learning and professional development for his accomplishments at 91亚色 鈥� and for this award.

鈥淩eceiving the Bergeron Medal is a tremendous honour for me,鈥� Singh says. 鈥淭he award reflects not only my individual efforts, but also the support and mentorship I have received from faculty members, family and fellow students.鈥�

The award, he notes, has motivated him to pursue a master鈥檚 degree exploring AI governance and policy as evolving technologies continue to influence regulation and use. He hopes to develop frameworks that guide the responsible use of AI while balancing innovation with transparency, fairness and public accountability.

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