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U of T student wins Pioneer Tournament with team for innovation that predicts human cancer risk

Hannah Le and teammates developed an innovation that blends AI, machine learning, and genomics

U of T student wins Pioneer Tournament with team for innovation that predicts human cancer risk

As many U of T students were wrapping up classes in March, first-year engineering student Hannah Le and her team won the third Pioneer Tournament — a worldwide competition that rewards participants for developing innovative ideas — for their project that used machine learning to identify and understand human biomarkers that predispose individuals to certain diseases.

Competition participants submit their project online and post weekly progress updates. The project then earns points awarded by contestants, who vote on the updates. After three weeks, the project becomes eligible to win a weekly prize, which is awarded to the team that wins the highest number of points at the end of that week. A project that places as a finalist for three weeks wins the team a larger award.

Le and her team members — Samarth Athreya, 16, and Ayaan Esmail, 14 — earned a top spot on the leaderboard in March and were awarded $7,000 from Pioneer to put toward their project. 

How the team got together

“Samarth, Ayaan and I met each other at an organization called The Knowledge Society in 2017,” wrote Le to The Varsity. The Knowledge Society is a startup incubator that exposes high school students to emerging technologies, such as artificial intelligence (AI), virtual reality, and brain-computer interfaces.

When the three innovators met, Esmail was working on a project that could accurately pinpoint and target cancer cells, while Athreya was working with machine learning models. With Le’s interest in genetics, the three decided to team up and investigate whether there was a way to use metabolic data to predict the onset of a disease.   

“I became incredibly curious on how we can decode the 3 billion letters [of DNA] in every cell of our body to increase human lifespan and healthspan,” wrote Le.

“Inspired by my grandmother who passed away due to cancer, I started asking myself the question: [could] there possibly be a way for us to predict the onset of cancer before it happens, instead of curing it?”

How Le’s team developed a model for predicting the risk of cancer development

At its core, the team’s AI platform uses a patient’s biological information to predict their risk of developing certain forms of cancer.

Metabolites are molecules that play a key role in maintaining cellular function, and some studies have shown that high levels of certain metabolites can signal the progression of lung cancer. But to develop and test their model, the team needed a large amount of metabolic data.

“To overcome such [a] limitation, we had the fortune to reach out to mentors such as the Head of Innovation at JLABS, [a Johnson & Johnson incubator], for further guidance and advice,” wrote Le. “As our team cultivates a stronger database, we would be able to produce more reliable results.”

“As teenagers we were far from experts [in] the field but we were really hungry to learn,” added Le.

As participants of the Pioneer Tournament, Le and her team received the opportunity to select a board of virtual advisors, who would provide guidance for their project.

“I recalled contacting Josh Tobin at OpenAI to ask him about the use of synthetic data in genomics research,” wrote Le. “[That enabled] us to understand both the strengths and weaknesses of such [an] approach, allowing us to pivot on what models to implement.”

The competition as a learning experience

Le remembers the Pioneer Tournament as an exciting chance to learn about different machine learning models and what made them effective as well as other projects that fellow participants were working on, all while attending courses at U of T.

“First year was an interesting journey of challenging course content, intertwined with unexpected personal growth,” wrote Le. “I learned how to strike a balance between working on personal projects, meeting interesting people, while completing my school work.”

And while Le is intrigued by the intersection of machine learning and genomics, she wrote, “I hope to keep an open mind and continue to be curious about the world around me.”

Chemistry PhD student named 2019 Vanier Scholar for innovative research proposal

Austin Marchese recognized for his exceptional leadership and scholarly research

Chemistry PhD student named 2019 Vanier Scholar for innovative research proposal

Austin Marchese, a U of T Organic Chemistry PhD student supervised by Professor Mark Lautens, has been named a Vanier Scholar — one of Canada’s most prestigious awards for students in doctoral studies.

Marchese was awarded the scholarship for his research proposal “Novel Enantioselective Nickel-Catalyzed Transformations Forming Medicinally and Industrially Relevant Halogenated Compounds.”

The proposal details his findings that affordable nickel-based catalysts — which can speed up the rate of a chemical reaction without being consumed — could be used in an innovative way to produce compounds important in medicine and industry.  

The impact of Marchese’s research

Writing to The Varsity, Marchese explained that the first part of his research proposal explored a “unique phenomenon” that he and his colleague observed in the course of their research.

“We discovered a rare and intriguing method to generate our compounds with moderate enantioselectivities,” he wrote. An enantioselectivity is a tendency for a reaction to produce one particular variant of a product, in greater quantities than another.

“We would like to understand why exactly we see this phenomenon and how we can exploit it and improve upon it,” he added. “A breakthrough in this would yield a useful and interesting synthetic technique to generate these divergent medicinally relevant compounds with high enantioselectivities.”

The second part of the proposal is to develop improved methods to form bonds between carbon and fluorine. “This methodology would be of interest to pharmaceutical researchers,” noted Marchese, “as carbon-fluorine bonds are ubiquitous in biologically active compounds, but there is a severe lack of synthetic methodologies available to install these bonds in a mild and selective manner.”

“In an ideal world, both parts of my proposal would come together; a nickel catalyzed process of this nature to enantioselectivity generate medicinally relevant compounds while installing an invaluable carbon-fluorine bond, but we are quite far away from achieving this.”

The positive attitude of an organic chemist

Marchese attributed his ability to overcome challenges during his doctoral studies to his passion for his research.

“I believe if you genuinely enjoy what you do and have confidence in yourself,” wrote Marchese, “everything will turn out alright.”

“Many people in my field do very long days, but if you enjoy it does not feel like work. It is similar to the lessons I learned competing Varsity track and field in undergrad; you put in a lot of work so those short instances of success become more rewarding, and that propagates you to work harder after.”

“Expectations do go up in grad school, and you have less time to study and work between deadlines, so I just try to stay calm and trust that if I give it my best and put in as much effort as I can, everything will work out.”

Flaw in WhatsApp exploited to target human rights lawyer, finds Citizen Lab

Lawyer has been embroiled in lawsuit against NSO Group, controversial Israeli technology firm

Flaw in WhatsApp exploited to target human rights lawyer, finds Citizen Lab

On May 12, a London-based human rights lawyer received peculiar video calls on his WhatsApp account while visiting Sweden.

Concerned by receiving the calls at such odd times in the morning, he reached out to cyber specialists at U of T’s Citizen Lab to investigate.

The Citizen Lab is a multidisciplinary research institute located at the Munk School for Global Affairs and Public Policy. The lab explores issues related to cybersecurity, surveillance, and digital censorship.

The lawyer, who remains anonymous due to fears of retaliation for speaking out, suspects potential foul play given his involvement with a civil lawsuit against NSO Group, an Israeli technology firm.

Foreign governments, including Saudi Arabia, Mexico, and the United Arab Emirates, have allegedly used NSO Group’s products to spy on journalists and political dissidents, including a critic of Saudi Arabia living in Canada.

According to reports from the Financial Times, the spyware targeting the lawyer’s phone had digital characteristics typical of NSO Group products.

Citizen Lab Senior Researchers John Scott-Railton and Bill Marczak led the investigative team that discovered WhatsApp’s vulnerability.

In an interview with The Varsity, Scott-Railton said he “observed a case where it looked like there was an attempt to target that lawyer’s phone with this novel attack, which would have happened over WhatsApp through a missed call.”

By exploiting the app’s vulnerability, NSO Group’s Pegasus spyware could enter a target’s iPhone or Android device through WhatsApp’s call function. The malicious code could then extract private information such as text messages and call histories, regardless of whether a target answers the call or not. The spyware can also collect new data by turning on the device’s camera or microphone.

 

WhatsApp’s response

WhatsApp engineers worked to patch the vulnerability as quickly as possible once they became aware of the susceptibility in the software. When finished, their company urged its 1.5 billion users to update their apps.

“WhatsApp encourages people to upgrade to the latest version of our app, as well as keep their mobile operating system up to date, to protect against potential targeted exploits designed to compromise information stored on mobile devices,” WhatsApp said in a public statement.  

The social network also informed the United States Department of Justice officials and issued a Common Vulnerabilities and Exposures notice to inform cybersecurity experts.

Scott-Railton praised WhatsApp for acting swiftly after discovering the vulnerability. “The way that WhatsApp has responded to this has been, I think, quite positive,” he said, noting how WhatsApp contacted a number of human rights organizations, which are common targets of the Pegasus spyware, before publicly announcing the security vulnerability.

According to Scott-Railton, this was an “unprecedented” move by a social media company and signals that it “felt there was something very wrong that had been done… and they didn’t like what they saw.”

It is unclear how many people were targeted or impacted by the vulnerability. However, based on WhatsApp’s comments, Scott-Railton said it seems like “there was a problem… [which was] much larger” than the attack on the human rights lawyer alone.

NSO Group promises reform

NSO Group maintains that it partners with governments to assist with law enforcement efforts and prevent criminal activity such as terrorism.

In response to reports that its software was targeting the human rights lawyer, NSO Group said that it “would not, or could not, use its technology in its own right to target any person or organization, including this individual.”

Earlier this year, NSO Group was partially acquired by the UK-based private equity fund Novalpina Capital. When Novalpina took over, it promised to reform the company in light of recent reports of suspected abuse.  

When the acquisition occurred, Novalpina was hoping to “establish a new benchmark for transparency and respect for human rights in full compliance with the [United Nations] Guiding Principal,” said Stephen Peel, co-founder of the fund.

Scott-Railton believes that “if indeed this was NSO, it suggests that this public story about human rights abuse may not [match up] with other things that we’ve observed.”

A bigger picture

Citizen Lab has been involved in multiple investigations tracking companies that sell spyware. Earlier this year, Citizen Lab itself had been targeted by undercover agents — masked as “socially conscious investors” — for its research on NSO Group.

Scott-Railton believes this case points to a larger trend of companies selling spyware to target individuals. “I think in the long run, we won’t really understand the digital risks and challenges that we all face until we see cases where harm happens to individuals,” he said.

“It’s very disconcerting to someone who has WhatsApp on their phones when they hear that there’s some company out there that’s selling a technology to basically use that as a way onto their phones, without any interaction,” Scott-Railton said.

“It’s almost unpreventable.”

Disclosure: Kaitlyn Simpson previously served as Volume 139 Managing Online Editor of The Varsity, and currently serves on the Board of Directors of Varsity Publications Inc.

Editor’s Note (September 28, 12:17 pm): This article has been updated to reflect the author’s former and current affiliations with The Varsity.

U of T team wins top prize at KPMG’s international AI competition

Paramount AI team created device that sorts waste with 94 per cent accuracy

U of T team wins top prize at KPMG’s international AI competition

A team of five U of T graduate students named Paramount AI won first place in KPMG’s 2019 Ideation Challenge, a worldwide competition to develop solutions to problems facing businesses using artificial intelligence (AI). KPMG is one of the world’s top four accounting firms.

The U of T students faced off against 600 participants from top universities across nine countries, including Canada, Australia, China, Germany, Luxembourg, Italy, the Netherlands, and the United Kingdom.

The final round was held from May 10–12 in Amsterdam, where the students — Maharshi Trivedi, Nikunj Viramgama, Aakash Iyer, Vaibhav Gupta, and Ganesh Vedula — won the top prize for their innovation, which used AI to automate waste segregation.

Paramount AI’s innovative solution

The winning innovation is a sorting system able to distinguish between three different categories of waste: recycling, organic, and garbage.

Iyer, who is specializing in data analytics and financial engineering, explained that the initial prototype of the system used LED light bulbs and basic circuits to classify the waste.

The five students worked continuously, with little breaks and limited sleep during the three days of the competition, which came at the expense of exploring Amsterdam.

The reward for their efforts came in the confirmation of the practicality of using the system in real-life situations. The device completed both a financial and market analysis by the end of the competition.

The importance of waste segregation

Viramgama, who is specializing in data analytics and data science, explained that the team chose to focus on the issue of waste segregation because they were concerned about improper sorting in Toronto.

He noted that about one in three residents in Toronto contaminate the waste they place in recycling bins, and that 20 per cent of waste placed in blue recycling bins ends up in a landfill.

Since there is limited landfill space, this has motivated government spending on improved waste management. An increase in spending may lead to a raise in taxes,which makes the emergence of automation in waste segregation something that can greatly benefit our waste management.

The U of T team tackled this issue by creating a system that accurately sorts waste about 94 per cent of the time. Current waste systems have an accuracy of only up to 74 per cent, and each percentage of accuracy translates to significant savings for spending on waste management.

The pressing need for a solution to this environmental problem, which has economic consequences, could be a reason why Paramount AI won the competition.

The other reason, explained Vedula, was that the team was “not only thinking about saving the environment, but… also trying to help businesses [maximize] profits.”

The future of Paramount AI

The next step for Paramount AI is to present their prototype to experts at KPMG’s annual AI summit in October. By then, the team hopes to further develop their model, aiming to continue increasing the accuracy of their system, while likely adding new features to increase the value of the product for potential clients.

The students currently have the intellectual property rights of their invention. With the support of KPMG, the team is interested in looking to commercialize their product.

They are also optimistic about the future of AI in positively shaping the lives of Torontonians, as a whole. “We completely believe that in the next few years, we will see AI being integrated in every part of our lives, because there is a huge potential,” said Vedula.

“[AI] is already involved in making our lives easier.”