鈥淲hen we think of environmental sustainability, we often immediately think about newer energy-efficient technologies. Organic waste treatment becomes rather an afterthought,鈥� says Reema Kumar, a PhD candidate at 91亚色's and lead author of the study.

That perspective is beginning to change as researchers look for new ways to recover value from organic waste. Instead of sending food waste to landfill 鈥� where it can contribute to greenhouse gases and other forms of pollution 鈥� scientists are exploring how it can be converted into useful resources.

One promising approach uses microorganisms to break down discarded food and produce chemicals that are typically made from petroleum-based sources, creating an alternative to landfill disposal and fossil-based production.

While researchers have tested adding microorganisms to increase the production of useful compounds from discarded food, most of that research has focused on systems that operate at relatively warm temperatures. Much less is known about whether the same process can selectively produce compounds under colder, lower-energy conditions.

According to Kumar, maintaining warmer operating conditions can require significant energy input, particularly in colder climates. Seeking a more energy-efficient approach, Kumar and her colleagues turned their attention to lower-temperature systems.

鈥淲e were inspired to optimize this natural system of microorganisms using food waste to produce volatile fatty acids under lower temperature conditions to make it more energy efficient as well as provide a targeted approach for production,鈥� says Kumar.

They honed in on Clostridium butyricum, a bacterium known for generating butyric acid and a commercially valuable chemical commonly used in food, pharmaceutical and industrial products. Yielding such chemicals from organic waste could provide a more sustainable alternative to conventional manufacturing methods that rely on fossil-fuel-derived raw materials.

Their work questioned whether introducing the bacterium into a low-temperature food-waste fermentation system could increase production of butyric acid.

In a study published in , Kumar and her collaborators tested the idea using food waste and wastewater sludge. The research was co-supervised by Lassonde Professor Satinder Kaur Brar, along with Guneet Kaur, associate professor at the University of Guelph.

The team created a series of small-scale experiments using food waste collected from restaurants in 91亚色 Lanes and sludge sourced from the Humber Wastewater Treatment Facility. Together, the food waste and sludge created conditions that allowed naturally occurring microorganisms to break down the waste.

Clostridium butyricum was then introduced into some of the samples to see if the bacterium could steer the process toward producing more butyric acid.

鈥淲e wanted to show that you can 鈥榞uide鈥� a complex microbial community, made up of many different bacteria naturally found in wastewater sludge, toward a specific, useful outcome just by introducing one well-chosen microorganism,鈥� says Kumar. 鈥淚t's a bit like steering a crowd by adding a few people who know where they're going.鈥�

The approach worked even better than the researchers expected. The system that received the bacterium produced more than twice as many acids overall and more than five times as much butyric acid compared to the control.

鈥淲e didn't expect such a strong response at a temperature of 17 C," says Kumar. "That was a genuinely exciting result."

The findings, she adds, point to a future where discarded food can be viewed as a resource rather than waste.

Increasing the production of commercially valuable compouds at lower temperatures could pave the way for more energy-efficient waste-treatment systems that recover greater value from discarded food. Over time, it may help keep organic waste out of landfills while creating renewable alternatives to some petroleum-derived chemicals.

鈥淲e hope it helps move the needle toward low-cost, low-energy ways of recovering value from food waste, especially in colder countries,鈥� says Kumar. 鈥淥nce this approach can eventually be scaled up, it could support local biorefinery systems that turn organic waste into useful chemicals without requiring expensive heating infrastructure. That has real implications for both sustainability and economics.鈥�

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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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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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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.

Knee injuries and osteoarthritis are among the most common causes of pain, disability and reduced mobility. While knee braces are often prescribed to support recovery after injury or surgery, most provide only passive support and rely on subjective feedback to guide treatment decisions.

Patients and clinicians have limited tools to monitor changes in knee function between appointments, creating challenges when personalizing rehabilitation and tracking recovery progress.

At 91亚色, researchers from the and the are working together to develop an instrumented "smart" knee brace that could help monitor knee function beyond the clinic.

The project brings together William Gage, professor at the School of Kinesiology and Health Science in the Faculty of Health, Gerd Grau, associate professor in the Department of Electrical Engineering and Computer Science, and Garrett Melenka, associate professor in the Department of Mechanical Engineering. Combining expertise in biomechanics, engineering design, wearable technologies, sensing systems and prototype development, the team aims to create a knee brace that is scientifically precise and practical for real-world use.

鈥淥ur project was inspired by a simple question: What if we could continuously monitor knee function outside the clinic using a wearable device?鈥� says Gage.

The Intelligent Knee Brace transforms a traditional support device into a wearable, smart monitoring system. By integrating sensors and machine-learning algorithms, it captures data on how people move in their daily activities, providing a more complete picture of mobility and recovery.

Gage and his team received a Phase 2 Connected Minds Prototyping Award, which provides up to $50,000 for full prototype development. The award program is part of the Connected Minds transdisciplinary research initiative at 91亚色 that partners with Queen鈥檚 University to support the development of socially responsible technologies.

Backed by the Canada First Research Excellence Fund and a network of more than 50 industry, hospital and community partners, Connected Minds explores how humans and intelligent machines interact.

Through the prototyping award, Gage and his team have moved the Intelligent Knee Brace through prototype development, sensor integration and the early development of machine-learning capabilities. Now developed into a working model, the smart knee brace integrates wearable sensors capable of measuring lower limb movement.

鈥淭he award has created an environment where researchers and industry partners can work together to rapidly test ideas, identify challenges and refine solutions that have the potential to make a meaningful impact in health care,鈥� says Gage.

From idea to development, the team has gained insights on how wearable sensing technologies and AI can be combined to generate meaningful information about human movement.

鈥淲hile wearable sensors can collect large amounts of data, transforming that data into clinically useful insights is a much more complex challenge,鈥� says Gage. 鈥淭hese findings are helping to shape the next generation of the prototype.鈥�

The project has demonstrated the feasibility of integrating sensing technology into a knee brace and will advance into the testing phase and will begin the validation process with industry and technology partners.

Gage says the goal is to determine how accurately the brace captures knee motion compared with laboratory-based systems.

As technology continues to develop, the potential for this smart device to enhance health care extends beyond individual clinical assessments. By offering continuous monitoring of knee function, the brace can provide more personalized rehabilitation, track recovery following injury or surgery and detect early changes in mobility that may require intervention.

In medical settings, this means clinicians can access continuous data between appointments, offering a more holistic understanding of patient needs. Over time, this comprehensive data can help shift care from periodic assessments toward more proactive models of health management.

"Ultimately, our goal is to help clinicians make better-informed decisions while giving patients more personalized feedback about their recovery and mobility," says Gage.

The next phase of the project will focus on expanding participant testing, validating the system鈥檚 accuracy and refining the machine-learning models used to interpret movement data. The team also plans to explore how the brace performs in populations with knee osteoarthritis and other mobility-related conditions.

Building on the project鈥檚 early successes, Gage and his team hope to establish large-scale clinical studies and industry collaborations that will support the technology鈥檚 path toward real-world health care applications.

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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�

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The award honours the team behind the project First-Year Engineering Block Model 鈥� a NEW Way of Teaching, led by Associate Professor Jeffrey Harris at the .

The project introduces a modular, block-based teaching structure that fundamentally restructures how students engage with courses by supporting student learning, reducing cognitive load and improving well-being. It was selected as one of five recipients through a national adjudication process recognizing collaborative innovation in post-secondary education.

The 91亚色 initiative brings together faculty and staff across multiple disciplines and roles and reflects the award鈥檚 emphasis on collaborative teaching innovation. Developed through Lassonde in collaboration with the Faculty of Science, the block model restructures the traditional course system, delivering courses in intensive, sequential formats rather than concurrently.

鈥淥ur project brings together expertise from engineering, mathematics, physics and computing to redesign the structure of the first-year experience,鈥� says Harris. 鈥淭his work is deeply collaborative and highlights what is possible when faculty are supported through educational development and instructional design.鈥�

Harris says the design responds to structural challenges students were facing 鈥� such as commuting, employment commitments and heavy workloads 鈥� by redistributing academic demands across the term.

Piloted in Fall 2023 with 63 students, the initiative has expanded to include 120 participants with plans to reach 250 students by the 2026-27 academic year.

Across three years of implementation (2023-25), students in the model achieved higher success rates compared to those in the traditional delivery model. Students also reported stronger peer connections, increased interaction with instructors and improved clarity on learning goals and assessments.

It has also led to increased collaboration across faculties and strengthened teaching practices through shared design.

鈥淏y focusing on how learning is delivered, we鈥檝e demonstrated that meaningful, large-scale academic transformation is possible within institutional and accreditation requirements,鈥� says Harris. 鈥淭he next phase builds on this foundation, with a new curriculum that expands the model into an integrated first-year experience launching in Fall 2026.鈥�

The team聽receiving the award聽includes Lassonde colleagues Associate Professor聽Mojgan Jadidi, Assistant Professor聽Kai Zhuang, Tanveer Bhimani, instructional and learning designer, and聽Saskia van Beers, research associate along with Faculty of Science Professor聽Matthew George聽and Associate Professor聽Andrew Skelton. The team also includes Patrick Molicard-Chartier from the Universit茅 de l鈥橭ntario Fran莽ais.

The project was supported in part by 91亚色鈥檚 Academic Innovation Fund.

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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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Awarded by the Vector Institute, an Ontario-based AI research organization, the merit-based scholarships are support Ontario graduate students advanced studies in fields including business analytics, AI management, and computer engineering and science.

In addition to financial support, recipients are given access to networking opportunities with researchers and industry professionals, along with the Vector Institute鈥檚 Digital Talent Hub which connects AI specialists with potential employers.

About the recipients 

Mitali Chaudhary
Chaudhary is a graduate student in the Master of Business Analytics program at Schulich, with experience in building AI-ready data infrastructure and deploying scalable cloud-based solutions. Her work examines how AI can solve complex business problems and support decision-making, with a focus on generative AI and business applications.

鈥淩eceiving the聽Vector聽Institute Scholarship is both an honour and a strong validation of my work,鈥� she says. 鈥淚t motivates me to continue building impactful, real-world solutions using artificial intelligence and to contribute meaningfully to the growing AI ecosystem in Canada.鈥�

Romisaa El-Saidy
El-Saidy is pursuing graduate studies in computer engineering at Lassonde, focusing on AI applications. She has contributed to a range of applied AI and data-driven projects, including systems to predict geomagnetic storms using NASA data developed during international hackathons. She has also completed internships in research, development and 3D deep learning, supporting the design of AI-enabled applications and contributing to project planning and development. Her experience reflects a broad interest in using AI applications to address real-world challenges.

Harshit Gupta
Gupta recently completed an undergraduate degree in computer science focused on a AI, computer vision and graphics research. As he begins his MSc at 91亚色, his work will explore how AI can support the creation and understanding of 3D environments, with the goal of making immersive 3D experiences more accessible.

鈥淚 believe the next major shift in computing will be from 2D content to interactive 3D," he says. "My research focuses on making that transition possible by developing AI systems that can efficiently understand, represent and render 3D worlds. The Vector Scholarship helps me continue working toward that goal.鈥�

Amir Mohammad Jafari
Jafari is an incoming MSc student in computer science at Lassonde, where he will be supervised by Professor Ruth Urner. His research focuses on the safety of machine learning systems, including the robustness of large language models against adversarial attacks, with the goal of contributing to more reliable and trustworthy AI.

鈥淩eceiving the Vector Scholarship is a great honour and a strong motivation for me. It not only supports my graduate studies but also reinforces my commitment to advancing safe and reliable AI,鈥� Jafari says. 鈥淚鈥檓 especially excited to be part of the Vector community and to learn from researchers who are shaping the future of artificial intelligence.鈥�

Maxwell Levy
Levy is a graduate student in the Master of Management in Artificial Intelligence program at Schulich. Building on hands-on experience as an operations analyst at BNY Mellon, he is interested in how organizations can use AI and data analytics to improve decision-making and create competitive advantage.

鈥淚 chose Schulich because of its strong reputation and the depth of its AI programs,鈥� he says 鈥淣ow, being named a Vector Scholar not only supports my journey as an international student but also connects me to Canada鈥檚 growing AI community.鈥�

Fu Yao (Fuyao Q) Qiu
After working in the finance sector for several years, Qiu went back to being a student, now in the Master of Management in Artificial Intelligence program at Schulich. He focuses on designing AI systems that can support routine financial tasks and improve efficiency in corporate settings.

His aim is to design internal data-trained AI systems that handle tasks under human supervision, and to prepare for a future as an AI Implementor and product manager within corporate finance.

"Being named a聽Vector聽Scholar validates my transition back into academia and allows me to focus on building AI-driven financial solutions,鈥� he says.

Visit the for more information about its scholarship programs.

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The Faculty of Graduate Studies recognizes outstanding research annually through its thesis and dissertation prizes.

The annual prizes 鈥� valued at $2,000 for doctoral dissertations and $1,000 for master鈥檚 theses 鈥� honour work defended in the previous calendar year that demonstrates originality, excellence and impact.

This year鈥檚 awards highlight six projects that explored pressing questions with implications for food security, AI, public health, aging, air quality and workplace accessibility. Together, the projects show how graduate research at 91亚色 connects scientific inquiry with real-world challenges.

Doctoral recipients 鈥� dissertation prize

Jie Lin (PhD, biology) examines how phytoalexin biosynthesis is regulated in soybean plants in her dissertation, Identifying missing glyceollin transcription factors in soybean.

Her research identifies and characterizes a network of transcription factors that control plant defence responses and introduces an improved soybean root transformation protocol that supports gene expression studies and research tools to the plant science community.

鈥淎ltogether, her work transformed the current views of regulatory networks controlling phytoalexin biosynthesis and introduced better tools that benefited the plant research community at large,鈥� says Associate Professor Peter Cheung.

Matthew Kowal (PhD, electrical engineering and computer science) studies how computer vision models interpret images and video in relation to AI.

His dissertation, Disentangling visual concepts across space and time: from image hierarchies to video dynamics, examines how visual concepts are represented, connected and evolve across data and time. His work introduces new frameworks for analyzing learned representations, helping researchers better understand how AI systems make decisions.

鈥淗is dissertation represents an exceptional and cohesive body of groundbreaking work on interpretable and concept-based representations in modern computer vision models,鈥� says Professor Michael Brown.

Congjie Shi (PhD, mathematics and statistics) developed the Information鈥揅ognition鈥揈pidemic (ICE) model, a multilayer network framework that integrates mechanisms of information flow, including rumour transmission and correction. Her dissertation, Integrating cognitive factors in network models of epidemiology with applications to disease control, examines how these dynamics affect disease spread.

The findings show that warning individuals and correcting misinformation can improve epidemic control while accounting for variation in behaviour and access to information.

鈥淚n every way 鈥� originality, methodological skill, academic impact and relevance to societal challenges 鈥� Dr. Shi's thesis surpasses expectations,鈥� says Professor Dong Liang, graduate program director.

Master鈥檚 recipients 鈥� thesis prize

Yashar Ebrahimi-Iranpour (MSc, chemistry) developed a one-dimensional atmospheric chemistry model to investigate the origin and distribution of nitrous acid, a key factor in air quality.

His thesis, Vertical structure and surface interactions of nitrous acid using a 1D model, integrates surface interactions, meteorology and atmospheric transport to better understand atmospheric processes.

鈥淭his thesis substantially exceeds the normative expectations of an MSc degree and approaches the level of our strongest doctoral work,鈥� says Professor Ryan Hili, graduate program director.

In psychology, Patrick Hewan (MA) examines how age-related differences in brain structure affect decision-making in older adults. His thesis, Prefrontal brain microstructural integrity is related to an exploitation bias in older adulthood, explores the relationship between prefrontal brain microstructure and exploitation bias using cognitive neuroscience approaches.

The findings contribute to understanding how brain changes influence behaviour in ageing.

鈥淗is committee went so far as to say this was 鈥榞roundbreaking and even paradigm-shifting for the broader field of cognitive neuroscience,鈥欌�� says Professor Adrienne Perry, graduate program director.

Grace Pawliw-Fry (MA, geography) studies how neurodivergent workers navigate precarious labour markets in Ontario. The thesis, Teetering on the edge of surplus: neurodivergent work, social reproduction and bodyminds in the Ontario labour market, examines the intersections of work, disability and social reproduction.

It contributes to scholarship in labour geography, critical disability studies and workplace accessibility.

鈥淭his is a sophisticated and beautifully argued MA thesis, which integrates several literatures with very rich empirical data,鈥� says Professor Alison Bain, graduate program director.

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91亚色 alumna Randa Qashoa鈥檚 journey from the to a career advancing space technology highlights the growing impact of women in shaping the future of engineering.

Today, Qashoa (BEng 鈥�21, PhD 鈥�25) is a systems engineer at Honeywell Aerospace, where she works on the assembly, integration and testing of quantum communication payloads. While still early in her career, she is already contributing to technologies that could play an important role in the future of secure communications in space.

Her path into the industry was shaped by the people and opportunities she encountered at Lassonde.

"My experience at Lassonde was instrumental in helping me pursue a career in the space sector," Qashoa says. "The main driver was the wealth of experience in space engineering that Lassonde faculty carry."

Exposure to faculty-led research gave her firsthand insight into how engineering can tackle complex challenges and create meaningful impact beyond academia. Seeing professors lead innovative projects inspired her to pursue a career that contributes to advancements in the field.

That goal became reality when she joined Honeywell Aerospace 鈥� one of the world鈥檚 largest suppliers of aviation and defense systems. Among her proudest accomplishments is the opportunity to work on flight hardware that is planned for future operations in space.

Her experience also highlights the importance of mentorship and community in the study of engineering. Throughout her time at 91亚色, and now early in her career, she noticed she was often the only female on a project team or in a meeting. Rather than viewing this as a barrier, she stayed focused on contributing her skills and expertise while building a network of mentors and peers with shared experiences.

One of those mentors was Professor Regina Lee, who supervised Qashoa鈥檚 PhD studies and helped her navigate the transition from academia to industry.

That support, says Qashoa, provided valuable insight into the realities of the engineering workforce 鈥� and continued in a new way after graduation.

Through Honeywell Aerospace's mentorship program for women in engineering, she was paired with a more senior colleague who offers advice and career guidance.

Together, those experiences reinforced the value of strong support networks in helping women thrive in technical fields.

As more women enter engineering and space-related professions, Qashoa expects the industry to benefit from a wider range of perspectives and experiences. Increased diversity, she believes, will help drive innovation and bring new ideas to some of the sector's most complex challenges.

For students considering a future in space engineering, her message is simple: persevere.

鈥淢y advice to current students is to never give up no matter how impossible the challenge,鈥� she says. 鈥淓ven if you are the only woman on your team now, you are bringing something valuable to the table.鈥�

She encourages students to stay confident, embrace challenges and recognize the impact they can make. As the industry continues to evolve, she sees increasing opportunities for women to help shape the future of space exploration.

Her path from Lassonde to work in aerospace highlights how education, research and mentorship can shape careers in emerging areas of engineering 鈥� especially for women.

Watch Qashoa discuss her Lassonde experience and what it means to contribute to the future of the space sector.

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