At the recent American Concrete Institute Convention in Toronto, CivMin’s Professors Emeriti R. D. Hooton and F.J. Vecchio were each honoured with special technical sessions held in their names and with individual receptions.
Doug Hooton
During the ACI Conference in Toronto there were four distinct sessions honouring Professor Emeritus R. Douglas Hooton’s 50 years of research contributions in cementitious materials and concrete durability. With approximately 200 in attendance at each session, the talks were presented by 14 international and Canadian researchers. Several U of T alumni spoke, including Andrea Boddy (CivE 9T7, MASc 2T0), Savio DeSousa (CivE 9T4, MASc 9T6), Kyle Stanish (CivMin MASc 9T7, PhD 2T0), current PhD student Christian Pavlidis (CivE 2T0+PEY, MASc 2T4), and CivMin Prof. Evan Bentz.
An industry-sponsored celebration, held after the formal programming, saw numerous industry professionals and friends of Hooton gather to recognize him. Colleagues, including ACI Ontario Chapter representatives, remarked on the industry achievements, as well as numerous executive positions at ACI Ontario, the honouree has held over a long and illustrious career.
Frank Vecchio
Friends, colleagues and former students from around the world gathered to celebrate the extraordinary career of Professor Emeritus Frank J. Vecchio. The event honoured Vecchio’s outstanding research contributions and his pivotal role in advancing behavioural models and analytical tools for the assessment of concrete structures.
Former CivMin PhD student Dr. Anca Ferche (CivMin PhD 2T0), who acted as the event organizer, remarks, “The reception featured tributes from former students and collaborators, who shared stories highlighting his technical brilliance, mentorship, and lasting influence. Professor Vecchio himself also offered heartfelt remarks, reflecting on his journey and expressing gratitude to the many individuals who have shaped his career. The room was filled with warmth, laughter, and deep appreciation for a career that has not only shaped a field but also touched the lives of countless people within it. Technical sessions followed, further showcasing his enduring impact. It was a fitting tribute to a legacy defined by innovation, generosity, and profound contributions to structural concrete research and education.”
With simultaneous celebration events for the two CivMin professors emeriti on the same evening, several other CivMin professor colleagues gathered.
Dr. Asieh Hamidi, a CivMin postdoctoral fellow (PDF), is the recipient of a Women in Mining Canada 2025 Research Grant. WIM Canada supports graduate students conducting EDI-related research in the mining industry, as well as women conducting technical research in the mining industry.
Hamidi’s research is in the area of Tackling Uncertain and Unreliable Rock Engineering Data in Mining: Applications of AI and Bayesian Analysis. Her research is aimed at advancing the field of rock engineering in mining by establishing a foundation for integrating AI, machine learning (ML), and Bayesian methods into geotechnical decision-making.
Understanding rock behaviour for mining geotechnical engineering design generally begins by analyzing complex datasets obtained from various sources. Often these datasets are plagued by missing data, and may be unreliable. In this work she will use advanced data imputation to develop techniques to ‘fill the gaps’, and then apply ML schemes to develop reliable predictive models of key rock properties for engineering. AI-driven models allow us to uncover intricate relationships between rock properties, governing mechanisms, and engineering performance, and has great potential to lead to safer and more optimized mining designs. However, uncertainty remains a critical factor in predictions of factors such as rock mass behaviour and in-situ stress state, and this hampers decision-making for surface and underground rock engineering designs. To address this, she will apply Bayesian inference to augment datasets with expert knowledge in a robust probabilistic fashion.
Overall, her work will contribute to a systematic data analysis approach for evaluating rock engineering behaviour, ultimately leading to more informed, reliable, and safer mining operations and designs.
The award announcement came via a LinkedIn post by WIM Canada.
A team of U of T researchers has an innovative way to use existing Street View images to reveal what’s inside structures.
Did you ever wonder how a building was constructed? Or perhaps if it has a recently renovated interior and is now more energy efficient? How would you know unless you had the opportunity to view it during a realtor’s open house?
Researchers at U of T have created a way to use Google Maps Street View images to assess existing structures. With the aid of machine learning, commonly known as artificial intelligence (AI), the images available online can be used to generate data to help determine the age, height and size for existing structures. Known fully as Image-based prediction of residential building attributes with deep learning, the system shows promise for future, widespread uses.
Why is this useful?
Planning for existing and future infrastructure needs, such as water, sewage, power, transportation and more, and understanding the resources consumed in building neighbourhoods is critical for towns and cities. Generating the kind of data needed is tremendously expensive and difficult to obtain.
Professor Shoshanna Saxe in the Department of Civil & Mineral Engineering (CivMin), Alex Olson (MIE MASc 2T0), a senior AI researcher at the Centre for Analytics and Artificial Intelligence Engineering (CARTE), along with first author Weimin Huang (MIE MASc student) and Prof. Elias Khalil (MIE)have developed the new system with an astounding overall 80 per cent accuracy.
Summing up the system they’ve developed, Saxe says, “This is the first paper we know of where people took a picture that shows you the front of the building and then predicts things that you can’t see in the picture.”
As Streetview is prevalent nearly everywhere, this cost-effective way to generate significant building data has the potential to assist in planning for infrastructure needs all over the world. “My motivations were very focused on embodied carbon research use, but this will be useful for lots of different people. I’ve talked to researchers who are looking at understanding water usage for future planning, or resilience assessments. There’s a lot of places where there’s just not reliable data. Having methods that can let us understand neighbourhoods and buildings at scale is really useful,” Saxe explains.
Illustrating just how cost-effective the method is, Saxe says” We spent maybe $1,000 on photos to get data that would otherwise cost millions of dollars to obtain. Nobody has millions of dollars to spend on just building dimensions, so this is the difference between being able to work on these problems and not.”
“Being able to assess the exteriors allows a sort of educated guess at the interiors and the kinds of uses the occupants put on local infrastructure,” Olson says. “It gives a strong estimate of the resources used in building, maintaining and operating the buildings.”
Saxe expands, “This is information you can’t get from traditional methods of just looking at maps or plans – you need to see structures. One of the distinctions is we’re predicting what the internal square footage of the building is. And, although obviously that tracks with the size of the outside of the building, it’s actually harder to predict. And you also can’t see how old the building is from the outside.”
“If you have experience, you can walk around and say, that building looks about this old to me, this building looks about that old to me and so on. But there’s all kinds of things about it that make it hard, including renovations. The front can be different from the back. And is the frontage brick, glass or is it concrete? Knowing the age of the building is important, as it tells you what materials were used and what embodied carbon there is. And, also, how it performs.”
One of the challenges they faced in their research was the way buildings change over time with both minor and major renovations. Deciding what constitutes a major change is often open for debate and interpretation. At what point is the structure no longer the original one? The “Ship of Theseus” paradox addresses this kind of change over time. Essentially, when is the ship no longer the original ship? At what point is a renovation so extensive that you are functionally dealing with a new building?
This popped up interesting challenges for the model. One example of a home in the study, 49 Nanton Avenue, is one that was completely gutted and renovated, but had an exterior much like its original. In the original data used for training the model 49 Nanton had been categorized as a new building based on the gut renovation. But looking at the Streetview image it was assessed by the model as an old 1910 or 1920 building.
The ability to see beyond the facades of buildings with this AI could help us better understand the resource needs of our cities and with prioritizing future infrastructure in areas of greatest need. Olson reflects,“You want to understand where there’s underused resources or infrastructure in your city. It sounds like we should already have the data, but we really don’t. With this, while it doesn’t model the future, it does quite accurately describe what the current situation is and allows us to use the data for planning our resource uses and what we want to do in the future.”
A team of U of T students earned second-place recognition at the annual Troitsky Bridge Building Competition this year. A recent scoring amendment brought the team their delayed recognition.
Held annually at Concordia University in Montreal since 1984, this year’s February 21-24 event attracted 33 teams from 11 Canadian universities. U of T fielded seven teams, the largest delegation overall, with each constructing a bridge model made of only popsicle sticks, glue and floss.
Testing was performed of each entry’s strength using a hydraulic press. Besides the ability to take a load, scoring for the event is also based upon structural efficiency (maximum load divided by the bridge weight), presentation score (to a panel of industry professionals and faculty) and team spirit.
Team captain Isabelle Ali (Year 3 CivE) remarks, “I’m very happy with how well we were able to perform across all the categories.” Continuing, “Our team’s I-beam design was a reflection of what we learned from past competitions. This year, we focused on optimizing the joints since the bridge had to be built in pieces before being assembled in Montreal.”
The group used the theme of Dr. Seuss’ The Lorax while calling their team Thneed for Speed. The 2025 second-place showing is the best since a 2020 first-place result for a U of T team.
April 16, 2025 | Bloomberg
April 5, 2025 | Toronto Star
A team of U of T students earned second place overall at a recent international competition held by the Earthquake Engineering Research Institute (EERI).
The annual Seismic Design Competition (SDC), held at the University of California at Berkeley from March 31 to April 3, saw the U of T Seismic Design Team join four other Canadian universities for a total of 48 teams from institutions around the world.
In essence, teams design a model structure capable of surviving conditions simulating an earthquake. Each team designs a complex tall building model, made from balsa wood, which is tested on a shaking table. They are judged on their oral presentation, summary poster, their model’s architectural design, ability to fit within the design criteria and constraints, analytical prediction of their model performance and response of their model during shaking table testing.
The team of 10 attending the event, comprised of nine Civil Engineering students and one from Daniels Architecture, won first place for Best Architecture and garnered enough points, along with acknowledgment of their damping device and poster, to rate second place overall. This showing is the best U of T has seen at the SDC, bettering a 2022 first-place Architecture award.
Under the guidance of faculty advisor CivMin’s Professor Constantin Christopoulos, and led by co-captains Sacha Morin (Year 3 CivE) and Joyce Zhong (Year 3 CivE), the team constructed their tall building model in Toronto, then shipped it to California.
“We are very proud of the U of T seismic Design Team for this great achievement,” says Christopoulos, recounting the dedication of the team to the tasks and ultimate delivery. “The students put in a tremendous effort for many months, learning new engineering concepts, developing their designs, building numerical models, getting better at building their structure, running shake-table tests, etc. In addition, they showed great organizational skills in putting together and coordinating a large team, finding donors, organizing their trip and finally representing U of T at UC Berkeley so well!“
Isobel Forrest (Year 3 CivE) recounts the logistics of seeing their entry shipped to the venue successfully, “We’d shipped the tower to a nearby UPS store and had been notified it had arrived a day early, so we had the perfect time to pick it up on Saturday. The new shipping method – using a cardboard box rather than a wooden crate – was successful! The tower arrived without any major breaks and the box was light enough for Freddy and Naveen to carry the 20-minute walk to the hotel.”
The most nerve-racking of tests, the shake table, saw U of T secure success with the stability of its design. Forrest relays, “When it was time for our shake, we were pretty confident our tower would survive both ground motions but were still nervous. Of course, our tower survived very well.”
By Phill Snel
A full team roster for the U of T Seismic Design Team:
Co-Captains
Joyce Zhong
Sacha Morin
Logistics
Isobel Forrest
Charlie Miller
Design & Analysis
Luana Zang
Freddy Fisher
Harry Chen
Carman Xu
Fabio Karanja
Mihir Agarwal
Dana Bou Saab
Puneet Cheema
Maya Richman
Architecture
Joseph Chen
Madison Munro
Leila Rashidian
Sharon Kim
Construction
Naveen Black
Kevin Xu
Brian Tobing
Nivin Khan
Noor Aghili
Maryam Rameen
Bans Kim
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April 5, 2025 | CBC
April 3, 2025 | CBC Online