UNews - Lukas Grasse

��Ѹ��Դ��߿�Ƭ of Lethbridge student team captures a first-place finish in big data challenge

caroline.zentner — Fri, 12 Aug 2022 20:54:45 +0000

What if scientists could have predicted the path of COVID-19 infections and insured communities in those soon-to-be-affected areas had enough resources, such as personal protective equipment (PPE) and ventilators, to help stop further spread?

That’s the question a team of four ULethbridge graduate students from the Canadian Centre for Behavioural Neuroscience (CCBN) asked themselves as part of STEM Fellowship’s Inter-��Ѹ��Դ��߿�Ƭ Big Data Challenge 2022, a global competition that saw them take first place in the Research Solutions category.

Sally Sade, top row left, and Lukas Grasse, top row right, Yagika Kaushik, bottom left, and HaoRan Chang analyzed a large data set to determine patterns of COVID-19 infection.

HaoRan Chang, a PhD candidate, Lukas Grasse, a PhD student, and Yagika Kaushik and Sally Sade, both master’s students, analyzed a data set from Johns Hopkins ��Ѹ��Դ��߿�Ƭ that tracked the daily number of new cases of COVID-19, mostly at locations in the United States, from March 2020 to June 2022.

The COVID-19 pandemic revealed flaws in the world’s ability to respond to an unexpected health disaster. Essential medical supplies like PPE and ventilators were in short supply and could not be sent to the areas that needed them the most. But, the students reasoned, if the next geographical location in the pandemic’s path could be predicted, the potential to stop the spread of the virus would be far greater.

“What we could do with that data is allocate scarce resources to those regions pre-emptively before you see spikes occurring, so you’re not wasting resources in one region when they could be allocated to another,” says Sade.

“Our goal was to predict the spread of COVID, both in clusters of geographical locations and also across time,” says Grasse. “We were trying to predict, if we have a certain number of cases in a certain location, how that is going to spread to other locations in the future and also predict the number of future COVID cases in general.”

The team reduced the number of locations into 10 clusters that represented geographically similar locations in the same time period.

“We could see how each cluster influenced other clusters,” says Grasse. “A cool thing we found is that certain clusters, if they could have been eliminated, would have prevented the spread of COVID to later clusters. The idea is that if you could stop the spread of COVID at this one time and place, it would actually prevent all this later infection.”

In the U.S., the data shows COVID cases started along the east and west coasts and then spread to the Midwest, before spreading back again to the coasts.

“If some of that infection could have been prevented in the Midwest, or resources actually allocated there even though there isn’t quite the same population density as the coast, you could have hopefully prevented a lot of the later cases in the high population areas on the coasts,” says Grasse.

“The model is generative in a sense, as you’re able to forecast how the cases will evolve over time,” says Chang. “We are able to predict or forecast the number of cases across wide geographical regions. That way, we’re able to allocate and pinpoint resources in a much more centralized manner.”

Using their model, the team predicted a spike in COVID cases for July 2022, Sade says, and that turned out to be the case with the surge in the BA.5 subvariant.

Kaushik learned about the competition and encouraged her colleagues to get involved. They participated virtually in the global competition that saw 213 teams from 69 universities enter. The team submitted a scientific article outlining their data analysis and results, which was chosen by judges as one of the top 16 entries. The team submitted a video about their project and took part in a question-and-answer session with the judges.

In the end, the ULethbridge team placed first in the Research Solutions category. They credit their different backgrounds in neuroscience, biotechnology and computer science for helping them approach the problem from a different perspective. Along with a $1,000 prize, the team’s manuscript will be published in the STEM Fellowship Journal.

“The way we approached the whole problem was very different from other teams, where perhaps a lot of people came from purely analytical backgrounds. They would see the problem as a set of analyses that you have to undertake,” says Chang. “In our case, the analysis follows post hoc from the problem itself. Having a neuroscience background gave us a unique perspective on how we viewed this data set.”

Faculty and student researchers buoyed by NSERC funding

trevor.kenney — Wed, 17 Oct 2018 18:07:49 +0000

A diverse and comprehensive group of ��Ѹ��Դ��߿�Ƭ of Lethbridge researchers was awarded $1.98 million in funding from the Natural Sciences and Engineering Research Council of Canada (NSERC) this week, part of $558 million in total funding to post-secondary researchers and students, the largest investment in research from NSERC this year.

Projects in chemistry & biochemistry, neuroscience, kinesiology & physical education, mathematics & computer science, environmental science, biology and psychology all received funding support.

In addition, eight graduate students received $336,000 in funding, further broadening the impact of the federal government’s investment in research activities at the U of L.

“Canada supports science and our talented researchers. We are delivering on our historic investment in research and in the next generation of scientists. These remarkable researchers and students we are celebrating are working to make the world a better place and to secure a brighter future for all Canadians,” says The Honourable Kirsty Duncan, Minister of Science and Sport.

Dr. Erasmus Okine, the ��Ѹ��Դ��߿�Ƭ’s vice-president (research) says he is impressed with the breadth of research being funded.

“It speaks to the level of activity we have going on throughout the institution, and the variety of issues our researchers and students are tackling,” says Okine. “This level of funding is a recognition by NSERC that our people are making a real difference through their research work and will continue to do so.”

Projects in chemistry & biochemistry, neuroscience, kinesiology & physical education, mathematics & computer science, environmental science, biology and psychology all received funding support. Dr. Robert Sutherland’s study in the Department of Neuroscience, Hippocampus and memory: A systems level approach, earned $285,000 over five years, the largest award of the funded projects.

Sutherland describes the hippocampus as being situated at the hub of a set of distributed cortical networks that represent movement and perceptual information. Amnesia is the most prominent effect of damage to or dysfunction of the hippocampus and most forms of human memory disorder involve the hippocampus.

“The current proposal examines, in detail, how the interactions between the hippocampus and other cortical networks establish long-term memories,” says Sutherland, director of the Canadian Centre for Behavioural Neuroscience. “We will discover exactly which types of information depend on the hippocampus and how the hippocampus modifies the functioning of the cortex through long-term interactions.”

Dr. Louise Barrett, Canada Research Chair in Cognition, Evolution and Behaviour and member of the U of L’s Department of Psychology, will receive $200,000 over five years (plus an accelerator supplement of $120,000 over three years) for her project, Behavioural Flexibility, Fertility and Social Network Influences in Human and Non-Human Primates.

In her work, Barrett aims to understand how evolutionary processes influence the behaviour of human and non-human primates.

“More specifically, I am interested in exploring those aspects that we share with other primate species, and those that make us different,” she says.

Other funded researchers include:

Dr. Matthew Tata, neuroscience; Dr. Steven Mosimann, chemistry & biochemistry; Dr. Marc Roussel, chemistry & biochemistry; Dr. Athanasios Zovoilis, chemistry & biochemistry; Dr. Marc Bomhof, kinesiology & physical education; Dr. John Anvik, mathematics & computer science; Dr. Alexey Popov, mathematics & computer science; Dr. David Euston, neuroscience; Dr. Sergio Pellis, neuroscience; Dr. Stephanus Henzi, psychology; Dr. Cameron Goater, biological sciences; Dr. Majid Mohajerani, neuroscience.

Graduate students who received funding include:

Elijah Dueck, chemistry & biochemistry; Lukas Grasse, neuroscience; Samantha Krause, psychology; Kailyn Nelson, environmental science; Candace Burke, neuroscience; Serena Jenkins, neuroscience; Justin Lee, neuroscience; Conner MacNeil, chemistry & biochemistry.

Coding the iCub – making connections with cognitive robotics

trevor.kenney — Mon, 05 Feb 2018 23:12:51 +0000

An international partnership between ��Ѹ��Դ��߿�Ƭ of Lethbridge neuroscience professor Dr. Matthew Tata and Dr. Francesco Rea (Italian Institute of Technology in Genoa) has given three undergraduate students the unique opportunity to work on an independent study focused on cognitive robotics.

Tata started working with Rea during a sabbatical year in 2013-2014 when he lived in Genoa, Italy and worked full time at the Italian Institute of Technology (IIT).

Each of the students had an opportunity to work on different features of the iCub's interactivity.

“It was a perfect example of how a sabbatical study leave should work. I spent a year working with Dr. Rea learning everything I could about robotics, which was completely absent from the curriculum and research environment at the U of L. I brought robotics back with me and set up a lab and an introductory course, and maintained the collaboration with Dr. Rea so that students and researchers at the U of L can tap the expertise of IIT,” says Tata. “Our collaboration with colleagues at IIT aims to translate our discoveries about human cognitive neuroscience into technologies for robot perception and attention. This will make robots better at understanding and responding to human instructions.”

Rea received a BSc in Software Engineering from the ��Ѹ��Դ��߿�Ƭ of Bergamo, Italy and went on to do an MSc in Robotics and Automation at Salford ��Ѹ��Դ��߿�Ƭ, England. He then received a PhD from the ��Ѹ��Դ��߿�Ƭ of Genoa in 2013 where he developed machine vision and attention algorithms for human-robot interaction. Since 2013, he has been a researcher at IIT where he takes a brain-inspired approach to develop advanced cognitive robotics for the iCub humanoid robot.

“My research is focused on human-robot interaction and also cognitive robotics. These two disciplines work together, and we strongly believe that if we want to interact with robots, we need to share the same neuroscientific models of interaction,” says Rea. “We know that the U of L is a very important university where research in the field is well-known across the world. We are convinced that by studying those models here, we can more easily port them on a complex humanoid robot such as the iCub.”

The iCub is the humanoid robot developed at IIT as part of the EU project RobotCub and subsequently adopted by more than 20 laboratories worldwide. It has 53 motors that move the head, arms and hands, waist and legs. It can see and hear, and it has the sense of proprioception (body configuration) and movement (using accelerometers and gyroscopes).

“The humanoid robot, iCub, is complex – and there is a very specific reason. We want to create the perfect platform for the study of humans, so we need a little bit of complexity that is justified by the fact that we really want to reproduce some human behaviours,” says Rea. “It is complex, but there is a huge community of iCub users that collaborate together. By doing so, we can easily build on each other’s work and quickly provide very new innovative achievements, which relaxes the complexity of the platform a bit and is definitely one of the advantages of working with the iCub.”

Rea was in Tata’s lab working with computer science undergraduate students Lukas Grasse, Austin Kothig and Alex Hochheiden on the iCub robot. The students have been focused on various applications involving the implementation and improvement of cognitive models of the human attention system. He is working on introducing the students to developing new algorithms on a complex humanoid robot, which requires very specific procedures to create new behaviours and skills. “The idea is to achieve cognitive robotics and apply neuroscientific plausible models to robots.

The goal is to improve and validate those models – at the same time trying to give the robot skills that are human-like, skills that will eventually allow the robot to interact with humans in a natural fashion,” says Rea.

The students found their work with Drs. Tata and Rea to be very rewarding, and gained a lot from working with the iCub. Alex Hochheiden has been getting up to speed working with the robot for the first time.

“Other team members have been working with it for a semester or more, so I'm just trying to learn what they know and how I can contribute,” he says. “In addition to that, I've been looking at how we can optimize our code, helping troubleshoot issues and thinking about how to apply some software engineering best practices.”

Lukas Grasse has been working on the iCub’s understanding of speech in the environment and its response to when someone addresses it with “Hello iCub” or in Italian “Ciao iCub”. Like the others, he was first introduced to robotics through an Introduction to Robotics course offered by Tata, and has pursued the interest ever since.

“I really liked the class and have been doing independent studies in Dr. Tata’s lab since then. Cognitive robotics is an awesome field because it requires knowledge from many different areas, and you get to work with people that have different backgrounds and experience,” he says. “The field of cognitive robotics is just getting started. Working with Dr. Tata and Dr. Rea has made me realize how important it is for people to be able to interact with robots naturally using speech, touch, etc. I think this is true for technology in general, and I plan to keep working on solutions that enable these natural interactions.”

Austin Kothig also has plans to continue working with robotics.

“I've been spending a lot of time working in the lab with Dr. Tata and Dr. Rea, and have definitely learned a lot about how the global iCub community develops software for the robot,” he says. “Prior to doing my summer independent study I thought that I would be happy with a Bachelor in Computer Science. Since then I have been inspired to continue on to apply for a master's program doing research on AI and robotics.”

It is important to consider the impact of cognitive robotics in a world where humans have been building machines to help us do work for thousands of years.

“Now, with the advances of computer science, engineering and cognitive science we can build machines that are interactive and smart. They can make decisions. This is the most important technology of the 21st century and it will be highly disruptive,” says Tata. “There are many important technical and societal implications that we need to carefully consider and understand, so Canada needs to have highly-trained scientists working on the state-of-the-art in the field. That means working at the interface between neuroscience and robotics.”

Connect with Dr. Matthew Tata to learn more, or visit his lab website: tatalab.ca

U of L programmers lead Canadian schools at Rocky Mountain Regional

trevor.kenney — Wed, 18 Nov 2015 22:28:06 +0000

��Ѹ��Դ��߿�Ƭ of Lethbridge student programmers earned the highest finish of all Canadian universities, placing fourth overall, at the 2015 ACM Rocky Mountain Regional Programming Contest hosted by the ��Ѹ��Դ��߿�Ƭ of Alberta recently.

U of L Team 1, consisting of Kai Fender, Brandon Fuller and Lukas Grasse, solved seven of 11 total problems with 999 penalty minutes to earn the top spot among Canadian schools. ��Ѹ��Դ��߿�Ƭ of Calgary 3 was second amongst Canadian entries and fifth overall, while the ��Ѹ��Դ��߿�Ƭ of Alberta and ��Ѹ��Դ��߿�Ƭ of Saskatchewan had teams that ranked eighth and ninth overall in the competition.

“Basically, their solutions have to be in the form of computer programs that will run and produce the correct answers,” says Dr. Howard Cheng, associate professor of mathematics and computer science and the group’s coach. “For example, one of the easier problems they solved was to write a computer program that will read a recipe for a certain number of portions, and scale all the ingredients to some desired number of portions. A harder problem was to write a program that will read a map of a scavenger hunt and the values of each item in the hunt, then find a way to achieve the maximum value and still finish the hunt in time.”

Cheng says a wide cross-section of students take part in the contest, and all reap the rewards of the experience.

“I have students who are not in math and computer science at all. Some have just taken some programming classes and enjoyed it, and decided to try out for this,” he says. “The skills they get are general problem solving skills, as well as the ability to quickly turn a conceptual solution into a computer program that works correctly and efficiently. These skills are commonly sought after by high-tech companies, so they are increasingly using these types of problems/puzzles in their job interviews.”

A total of 52 teams were entered in the competition from throughout Western Canada and the western United States, with ��Ѹ��Դ��߿�Ƭ of Utah, Colorado School of Mines and ��Ѹ��Դ��߿�Ƭ of Arizona finishing first through third respectively. Both Utah and Colorado solved eight problems, while Arizona solved seven but had less penalty minutes, 823, than the U of L’s top team.

In all, the U of L entered four teams with all four finishing in the upper half of the competition.

��Ѹ��Դ��߿�Ƭ of Lethbridge 2, with team members Lindsay Ablonczy, Matt Basaraba and Stephanie McIntyre, placed 14th overall (five solved, 555 penalty minutes), while U of L 3, with Brad Melchin, Julius Moore and Soraj Seyed Mahmoud, placed 20th (four solved, 205 penalty) and U of L 4, consisting of Lyle Snelgrove, Marko Ilievski and Justin Werre, was 21st overall (four solved, 341 penalty).

To view full results, visit the competition website.

Programmers earn third-place finish at regional contest

trevor.kenney — Fri, 05 Dec 2014 23:29:12 +0000

A third-place finish led the way for a quartet of ��Ѹ��Դ��߿�Ƭ of Lethbridge student teams that participated in the Rocky Mountain Regional Contest of the 2014 ACM International Collegiate Programming Contest recently.

The U of L sent four teams to the 53-team competition, with the group of Kai Fender, Brandon Fuller and Camara Lerner grabbing third place overall. The ��Ѹ��Դ��߿�Ƭ of Calgary and the ��Ѹ��Դ��߿�Ƭ of Alberta finished first and second respectively. Other teams represented Arizona, Utah, Colorado, Wyoming, Eastern Nevada, Idaho, Montana, Saskatchewan and New Mexico.

“The students have done a tremendous amount of preparation for this competition,” says ��Ѹ��Դ��߿�Ƭ of Lethbridge associate professor of mathematics and computer science Dr. Howard Cheng, the team coach. “To get ready for this, some of the students were putting in eight hours per week under actual contest conditions.”

Students are given a series of complex, real-world problems that they must solve over a five-hour time period. Competitors race against the clock, and each other, in a battle of strategy, logic and mental endurance. Teammates collaborate to rank the difficulty of the problems, deduce the requirements, design test beds and write programs that solve the problems under the intense scrutiny of expert judges. For a well-versed computer science student, some of the problems require precision only. Others require a knowledge and understanding of advanced algorithms. Still others are simply too hard to solve – except, of course, for the world’s brightest problem-solvers.

The past two years saw a U of L team qualify for the world finals, and while this group fell just shy of making it to the international stage, Cheng is excited about their prospects moving forward.

“We had some of our senior students move on after last year, so we’re in a bit of a rebuilding phase,” says Cheng. “What was really exciting was that through this contest, we attracted interest from a number of high profile companies looking to recruit students. These events are excellent career-building opportunities for our students.”

The u of L’s other teams included the group of Lindsay Ablonczy, Chris Thomas and Justin Were (15th place); Matt Basaraba, Lukas Grasse and Marko Ilievski (19th place); and Brandon Robertson, Soraj Seyed Mahmoud and Zackery Shortt (36th place).

UNews - Lukas Grasse

��Ѹ�����Դ���߿�Ƭ of Lethbridge student team captures a first-place finish in big data challenge

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