This is largely the current situation when it comes to artificial intelligence (AI) applications in space. Space missions are complex endeavours that involve travelling great distances, harsh environments and many unknown factors, and they cost hundreds of millions to billions of dollars from conception to completion. While there is an inherent level of risk that is undertaken to do the work, a certain level of conservatism is also necessary to ensure a mission’s success.

“AI works in a non-linear way. This is the advantage of AI, what makes it so powerful.”

While some labs at 91��ɫ are creating technologies that are applied to actual space missions today, the work being done to develop AI applications is looking towards a future, exact date unknown, where AI robots will take over much of the labour of space exploration. In some cases, that technology is simultaneously being translated to applications on Earth, where there are far less environmental constraints, but the need for greater trust in AI is no less important, say the researchers at 91��ɫ’s Lassonde School of Engineering who are developing next-generation technologies.

Decades ago, ’s interest in space robotics was piqued after NASA launched the Hubble telescope, only to announce shortly after that the mirrors Hubble relied on to capture images of distant galaxies were flawed and all the images it captured were blurry. NASA looked into the feasibility of sending robots to fix the issue, but later abandoned this approach, instead sending astronauts. Yet, the idea of using space robots to service and fuel crafts intrigued Zhu and it remains an area of research interest to the present day. Now a professor at 91��ɫ and director of the Space Engineering Design Laboratory, he is developing robotics and AI future applications for MDA Space – Canada.

“AI works in a non-linear way. This is the advantage of AI, what makes it so powerful. But because of its unexplainable nature, because you cannot disentangle it, the space industry does not currently trust it, but is still very much interested in exploring the future of these powerful potentials,” he says.

Currently, explains Zhu, every time a satellite or craft is launched into space, an exact replica is created and left on Earth, so if something goes wrong, engineers can work with the replica to pinpoint the error and fix it. AI, in not showing its work, does not lend itself to such easy corrections.

While colleagues at MDA are attempting to create explainable AI to address this concern, Zhu is working on other pieces of the puzzle, often not involving the most powerful and complex AI technologies, but simpler ones that might be able to be adapted to space sooner. These include simulations to train AI vision for the low-level light conditions that exist in space when approaching a spacecraft; robotics and AI swarming technologies that involve several AI robots that are not the most powerful, but can work together to do more complicated tasks; and training AI robots on learning tasks like grip strength. Zhu is also looking at developing lightweight materials that can be used in space as radiation shields, as the sophisticated AI chips developed by companies like Nvidia cannot currently be used in space.

Associate Professor , director of the Astronautics and Robotics Laboratory at 91��ɫ, says that while his field used to be focused on fairly traditional methods, that is beginning to change. “Previously, this work has been dominated by classical techniques, but I would say in the last 10 years or so, we’ve seen a huge expansion where there’s interest in how we can apply machine learning, reinforcement learning, deep learning, deep reinforcement learning and computer vision to these fields.”

While space does pose unique challenges in terms of the environment, Bazzocchi says that many of the technologies they develop for space can be applied to the benefit of humans on earth and vice versa.

“While they’re not the same problem, they have many similarities that allow us to apply related techniques.”

One example from his work is an exoskeletal suit designed for firefighters to reduce the amount of effort required while doing strenuous tasks. Part of this lab work requires motion capture to understand a firefighter’s movements, but also requires employing different optimizations and algorithms to understand how the device might reduce or increase muscle activation in ways that might be beneficial.

"If you could send out autonomous robots first, they could perhaps create the right conditions for the humans to follow.” 

In space, the challenge for astronauts is quite the opposite: zero gravity conditions lead to muscle atrophy and eventually bone loss. The same research and principles can create wearables that purposefully create more resistance for astronauts when executing basic tasks.

“It’s not artificial gravity, because it won’t bring them to the floor, but it will make their movements more difficult,” he says. “When they want to do a task, for example, and they have to flex their arm, there’s a motor that’s resisting the motion so that it is not as easy.”

While the possibilities are exciting, Bazzocchi says that in both scenarios, machine learning and AI are not yet trusted.

“When you’re dealing with humans, you want predictability, and very obvious control that’s not going to potentially do something that’s unexpected and lead to injury,” he says. “And the same thing goes for space, when dealing with these multi-million-dollar assets, you want a certain level of predictability and explainability if something goes wrong.”

Still, Bazzocchi thinks it won’t be long until AI plays a bigger role in space.

“There have been some applications of autonomy in space already, such as for time-sensitive operations where there are long time-delays or for doing data processing. So, for example, creating algorithms that evaluate Earth imagery to detect wildfires is very much already in play.”

Zhu says that one day AI technologies might develop to the point where they can pave the way for creating hospitable living conditions for humans in space.

“Elon Musk wants to send humans to Mars. I think in the short term, it’s very difficult because the astronauts would die, the radiation exposure would be too much. But if you could send out autonomous robots first, they could perhaps create the right conditions for the humans to follow,” says Zhu.

Still, how would we know that the robots, working together and autonomously settling Mars, would still act in the interest of the humans that sent them there?

That’s the billion-dollar space robotics question, and according to the researchers, one we don’t currently have an answer for.

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“What excites me most about mechatronics engineering is the creativity, empathy and big-picture thinking it demands,” she says.

“We’re preparing students to lead in a world transformed by AI – equipping them to use it as a tool, understand its limitations, and apply it ethically and responsibly to solve problems people care about most.”

This integrated and interdisciplinary degree will give students the broad, higher-level engineering skills necessary to use advances in artificial intelligence (AI) and other technologies to solve today’s complex challenges.

As we increasingly rely on more advanced, often AI-driven technologies, future graduates of the program could be the ones to create next-generation medical devices to improve patient care, design renewable energy systems or develop smart technologies that can be integrated into people’s homes, workplaces, schools and communities to improve lives.

“I would absolutely recommend the mechatronics program to students who are looking for a balance of creativity, design and technology.”

What makes the program stand out is that students take courses in mechanical, electrical, software, computer and space engineering, as well as computer science, which gives them the tools to be more creative and innovative. Hands-on learning is a large component of their studies and could include working on systems for spacecraft attitude control, drone navigation and robotic automation, as well as vibration testing, satellite communications, flight software development and hardware testing for components heading into space.

“The goal of mechatronics is to provide the necessary technical background so that any graduate is well-prepared for that, but also providing the soft skills, work and life experiences that will make them well-suited for careers in industry,” says Mechatronics Program Director Michael Jenkin, also a professor at Lassonde. “One of the things that’s particularly exciting about mechatronics is that the systems interact with the real world. So, it’s not just something in software that exists in simulated isolation.”

In the first-year block model option, students focus on one course at a time rather than juggling several at once. Lassonde has tested this approach in recent years, and early results show it is helping students achieve higher grades, reduce stress and find a better study-life balance. Another innovation is cross-year collaboration, with students in upper years acting as mentors to students in lower years.

Third-year engineering student Chantal Hanna, who recently transitioned into the mechatronics engineering discipline to prepare for a career in robotic automation, says the program opens doors to a wide range of emerging fields.

“I would absolutely recommend the mechatronics program to students who are looking for a balance of creativity, design and technology,” says Hanna.

“Mechatronics is teaching me to see technology not just as machinery, but as a way to connect with the future and innovate with purpose. There are always new advancements in tech, and this is the field that will continue to grow alongside those advancements.”

Students will also gain work experience through two mandatory work terms, plus optional co-op placements. “With work-integrated learning and strong employer partnerships, our graduates will be ready to shape technology that connects with society and ensures AI serves people first,” says Goodyer.

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With an average of 74 cyclists killed every year in Canada, according to Statistics Canada, Jadidi decided to investigate how modern technologies could help make the cycling experience safer and less stressful. 

In a paper titled Improving Cyclists’ Safety Using Intelligence Situational Awareness System, published this year in Sustainability, Jadidi and her co-authors (Gunho Sohn, associate professor in geomatics engineering, and PhD candidate Amir Nourbakhsh) described how they were able integrate information from disparate sources into a mobile app that delivers updated information in real-time to Toronto cyclists via voice alerts.

“Many technology companies have worked with the car industry, so we have lots of sensors embedded in the car like back-up cameras and safety sensors,” she points out. “But the bike has not really changed. We thought about how we could build a system using the current infrastructure without adding more tech and be accessible to most people, so we focused on the phone.”

Jadidi’s team created a solution that analyzes location data, historical collision data, weather information, real-time current road conditions and traffic patterns to determine whether cyclists are at higher risk of collisions as they move around the city. 

“Information is a power,” she says. “When you have this power, you can make better and informed decisions. If a cyclist receives a warning telling them they’re entering a high-risk area, they can change their behaviour, go slower, or stop and take a different and safer route.”

Jadidi is also currently using quantum computing to analyze how to optimize bike sharing systems to better anticipate supply and demand by distributing bikes where they are most needed in real-time. She explains that she’s passionate about supporting cycling as a safe, accessible, and sustainable way to move around cities. 

“The bike can be very easily streamlined into the transit system, and it’s easy to connect these two modes of transportation,” she points out. “It’s a great way to get around the city without taking a car and making more pollution”—that is, if the safety issues can be addressed. 

With the source code for Jadidi’s safety application freely available on GitHub, she’s hopeful that it will be adapted by other developers to create safer streets that support cyclists as well as drivers. 

“Cycling is sustainable, inclusive and accessible, with a lower cost than a car,” she says. “We have the technology to deliver the information cyclists need to be safer. So why not do it?”

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Along with marvellous innovations in medicine, education and entertainment, rapidly emerging technological advancements are also delivering unintended consequences, and some communities are being left behind. Making sure everyone benefits from the technological boom reflects 91��ɫ’s signature mission to create positive change in the world, both locally and globally.

$318-million+ Connected Minds research program to bring equity and inclusion to murky waters of AI.

“We don’t want to slow progress in technology, but rather, work together to be more thoughtful about the consequences – and try to mitigate the negative outcomes and optimize the positive ones,” says Doug Crawford, a 91��ɫ Distinguished Research Professor in Neuroscience who is the inaugural scientific director of the first-of-its-kind enterprise.

The Connected Minds program will bring together experts from 91��ɫ and Queen’s University who are working across many different fields including liberal arts, engineering, health, law, life sciences, and the arts to develop a framework to guide future innovations in technology with a focus on inclusivity. 

“Receiving this second CFREF award in the last two competitions reflects 91��ɫ’s leadership as a research-intensive university that from its inception has understood the importance of an interdisciplinary approach in tackling complex, global problems. Connected Minds is particularly timely as we consider the implications of AI for creating a more equitable and inclusive world,” says 91��ɫ president and vice-chancellor Rhonda Lenton.

The researchers say putting some parameters around technological disruption would avoid the type of headline-grabbing pitfalls experienced by the AI text generator ChatGPT, almost as soon as it hit the market. Guidelines would also ensure underrepresented groups could enjoy the benefits of our shifting and evolving technologies and play a role in their creation.

“91��ɫ is an international leader in interdisciplinary research. The federal government’s substantial investment will unite 91��ɫ’s incredible strengths with Queen’s health specialties to chart new territory in socially responsible research for a rapidly changing digital world,” says Amir Asif, 91��ɫ’s vice-president research and innovation.

“We’re seeing a changing society with increasing intermingling between humans and machines and a host of different technologies,” says Pina D’Agostino, vice director and founder of 91��ɫ’s IP Innovation Clinic at Osgoode Hall Law School and vice-director of Connected Minds. “The social framework – the law – hasn’t kept pace. What we’re trying to do is develop technologies and frameworks that are socially responsible before they are disseminated in society, so we get ahead of the biases that may arise. That way underrepresented communities don’t get sidelined as technologies progress.”

The initiative’s equity focus will be applied to many projects that are already underway at the two universities, and also to the issue of Indigenous data sovereignty. Through an Indigenous Advisory Circle and partners, researchers hope to explore a framework for use of Indigenous Peoples’ data in a digital environment.

“Our work will seek to address the unexpected consequences of technological innovation, like the growing digital divide between broader society and Indigenous Peoples in terms of access to internet and also the colonization of it as well,” says Sean Hillier, associate director of 91��ɫ’s Centre for Indigenous Knowledges & Language and associate director of Connected Minds.

“We continue to see researchers in Indigenous communities saying, ‘how do we implement ownership, access, control and possession of our knowledge in a virtual world?’ We don’t have the capacity to do so.”

Already, more than 50 community groups are stepping up to engage in the research, a signal that the initiative is tapping into a recognized need. The City of Vaughan, for example, has contributed $36 million in land. Mitacs, which funds research and innovation, has contributed $1 million for internships and trainees. The Baycrest Health Centre – Rotman Research Institute, which studies aging and the human brain, is giving $2 million.

Potential projects include explorations into a more inclusive metaverse, virtual reality and community organizing, technologies for healthy aging and how the human brain functions when people interact with AI versus each other.

“We’re trying to figure out the way machines work, but we also need to understand the way the human brain works,” explains D’Agostino. “That’s the secret sauce in the machines and the technology. As we try and blossom machines, we have to link them up to the way we think. Something like empathy, for instance, will they ever have that?”

Another project is an Indigenous online gaming metaverse in which Indigenous Peoples can learn traditional language and gaming at the same time by engaging in land-based learning that recognizes the physical, mental, and spiritual connection to the land that is part of Indigenous identity.

“We hope that with our checklist, anytime someone innovates they won’t only think from a mainstream perspective,” says D’Agostino.

Technological disruption is only going to grow, adds Crawford, and it’s not too late to create guidelines to shape the future in a way that incorporates the values of equity, diversity and inclusivity.

“Here at 91��ɫ and at Queen’s, we have engineers and scientists involved in a number of technologies, some of them related to health, transportation, communications and computer vision,” Crawford notes.

“We hope to bring this new perspective to that. The other part is developing the paradigm. If we are successful in that approach, then the aim is to beta test here at 91��ɫ and Queen’s and have a broader effect on the way research is done in Canada and the world,” he concludes.

The CFREF grant of $105.6 million dollars when combined with the contributions from multi-sector partners, municipal governments, and collaborating partners is valued at $318.4 million, making Connected Minds the biggest 91��ɫ-led research program in the University’s history. 

Connected Minds will also expand Canada’s research power and create opportunities for early career up-and-comers. 

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While working on research in developing optimization algorithms, Seyyed-Kalantari’s life was derailed by a medical misdiagnosis that took two years to resolve. It was an agonizing experience, but it also inspired her to find a way to prevent the same thing from happening to others. 

“I saw the impact of having an under-diagnosis in my personal life,” she says. “I remember wishing that my research could help patients reduce pain.” 

Seyyed-Kalantari found a way to do just that during her post-doctoral fellowships at the Vector Institute and the University of Toronto, where she began investigating inaccuracies in AI diagnostics—work that she continues to pursue at 91��ɫ. 

And she’s uncovered some troubling findings that have caught even her by surprise.

In a paper published in Nature Medicine, Seyyed-Kalantari, as the lead author, examined data from multiple sources in the U.S. and discovered that AI-driven screening tools of chest X-rays had a concerning rate of under-diagnosis among underserved patient populations. 

“Historically vulnerable subpopulations—for example, Black, Hispanic, female and low-income patients—are suffering more from AI mistakes in these algorithms compared to other sub-populations,” 

she explains, noting that under-diagnoses are particularly harmful. “Upon deployment of such AI models, these patients were wrongly diagnosed as healthy. That means they may not have received any treatment in a timely manner and were sent home without further assessments.”

Even radiologists were taken aback, she added. “They said that when reviewing patient results, they don’t know anything about the patient’s race. They are sitting in a dark room reviewing the images and asking themselves ‘How can we be unfair to a patient that we have never seen?’” 

So, Seyyed-Kalantari and her multi-disciplinary, multi-institutional team delved further, looking into whether AI could determine the race of a patient from X-rays, CT scans and mammographic images alone. The results, published in The Lancet Digital Health, were astonishing.

“With a very high accuracy, AI models can determine the race of the patient by just looking at medical images,”

says Seyyed-Kalantari. “Everybody was surprised, and it was alarming. We don't know what AI is doing with this information. While we find that AI models can detect the race of patients, we find at the same time that AI is behaving against some races.”

The question now is: how is it happening? And what are the repercussions? 

Seyyed-Kalantari is actively looking for answers as she delves deeper into her work at Lassonde. In the meantime, she urges caution in embedding AI into healthcare. 

“Some AI algorithms have received FDA approval in the U.S. for applications in radiology. But to the best of my knowledge, they haven’t proven that the
algorithms are fair,” she warns. 

“If we’re deploying these algorithms and using them for disease diagnoses -and we’re not sure if they’re fair or not -this could harm some groups in our society.”

This concern underscores why research like Seyyed-Kalantari’s is so important, and how further research in this field can help ensure that the healthcare of tomorrow is truly fair and equitable. 

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Traditionally, data is exchanged by creating copies that are shared by data owners for end users. Bitnobi offers up a different approach – a privacy-protected decentralized data sharing platform that keeps the raw data at the source and sends only aggregate data to the end user.

The idea originated with a group including Marin Litoiu, a former IBM scientist and now a professor of software engineering in the Department of Electrical Engineering and Computer Science and in the School of Information Technology. Litoiu is the founder and chief scientific officer of Bitnobi.

"In the last two decades or so, data has become the new gold. It's used in AI and machine learning, and in intelligent systems in general."

“In the last two decades or so, data has become the new gold. It’s used in AI and machine learning, and in intelligent systems in general,” says Litoiu. “Its potential for improving every aspect of economy and society is tremendous.”

Litoiu was inspired to overcome the major challenges of data sharing and wanted to create a way to advance research and discovery without compromising privacy.

In 2013, a team composed of Litoiu, Michael Smit (Dalhousie University) and Litoiu’s postdoctoral Fellows at the time, Bradley Simmons and Mark Schtern, approached the problem of data sharing with a solution called DaaSPatcher, with the idea that data could be dispatched as a service. The group met with Hassan Jaferi, a commercialization manager with Toronto Innovation Acceleration Partners (formerly MaRS Innovation) in 2014 with the goal of taking the technology a step further.

Through 91��ɫ, they commercialized the technology and launched the data sharing startup. The name Bitnobi was inspired by “bit” – the ones and zeros that make up the language of computer science – and “shinobi,” closely related to “ninja.”

“Our technology eliminates the need to transfer copies of raw data from a data owner to a data consumer,” explains Jaferi, now CEO of Bitnobi. “Bitnobi flips the paradigm of data sharing from a ‘need to know’ to a ‘need to share.’”

By using a web interface provided by Bitnobi, end users run their software and data custodian premises, while the owners of the data remain in control at all times, determining the rules of engagement as to what and how much data can be accessed.

What Bitnobi offers is “clean, segmented and anonymized data,” explains Litoiu. “Bitnobi governs and audits usage policies on behalf of data custodians and federates data from different sources to prevent unauthorized usage.”

Given the number of serious data breaches that occur internationally, it’s a simple yet ingenious approach to data sharing that will prove to be a gamechanger for Canadian innovation.

Bitnobi has already caught the attention of major private and public sector partners in health care, government and defense – areas that are defined by heavy bureaucracy, data security, data privacy and governance. In a new partnership, Diabetes Action Canada is engaging Bitnobi to deploy a decentralized health care data-sharing network that will unlock diabetes data.

“Corporate organizations, like Roche Canada, have been very supportive of startup companies like Bitnobi in terms of providing us with the opportunity to develop proof of concept activities,” says Jaferi.

Marin Litoiu remains close to Bitnobi as a board member and chief science officer. His lab at 91��ɫ works with Bitnobi to envision future problems to tackle. Bitnobi has employed several 91��ɫ graduates and the University remains a shareholder in the company.

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