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We create the future of AI
Impact Report 2020/21: transforming scientific excellence into economic impact for Alberta and beyond
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Words from Amii's Leaders

The opportunity of AI

AI is already generating vast cross-sector economic wealth. Current and near-term AI applications include productivity enhancements in energy, agriculture and life sciences; precision medicine; speech recognition; autonomous driving; robotics; financial trading; smart cities; user interfaces; home automation; and entertainment. It is difficult to imagine a significant economic activity where AI would not play a key role.

This technology will touch every aspect of how humans live, work and play. The economic value of being a persistent leader in AI technology is difficult to overstate.

Amii works with companies at every stage of AI adoption - from exploring use cases and operationalizing machine learning to advanced research - and takes pride in translating for clients the knowledge and technologies produced by the institute's world-leading researchers.

The opportunity of AI

AI is already generating vast cross-sector economic wealth. Current and near-term AI applications include productivity enhancements in energy, agriculture and life sciences; precision medicine; speech recognition; autonomous driving; robotics; financial trading; smart cities; user interfaces; home automation; and entertainment. It is difficult to imagine a significant economic activity where AI would not play a key role.

This technology will touch every aspect of how humans live, work and play. The economic value of being a persistent leader in AI technology is difficult to overstate.

Amii works with companies at every stage of AI adoption - from exploring use cases and operationalizing machine learning to advanced research - and takes pride in translating for clients the knowledge and technologies produced by the institute's world-leading researchers.

AI in Alberta

Amii contributes to the thriving AI ecosystem in Alberta and the burgeoning economy resulting from increased interest in the field.

More than $600M in venture financing has been secured by Amii alumni to date, including over $450M raised by Canadian-based companies.

Acting as the region’s AI connector, Amii works alongside the University of Alberta, various post-secondary institutions, economic development agencies and tourism authorities to advance conversations on a global stage related to Alberta’s role in scientific thought leadership in the field.

In addition, Amii plays a leadership role across the country -- moving the needle on diversity in the AI ecosystem, developing and recruiting international talent, and improving the general public’s understanding of AI technologies as they become more integrated into day-to-day life.

Alberta’s business and science communities have embraced Amii as their entry point to begin their AI adoption journey and find like-minded peers and collaborators to build new ventures.

Research
We advance the foundations of AI and enable 
revolutionary applications.

Meet Amii's new Canada CIFAR AI Chairs

This past year, Amii welcomed 15 new Canada CIFAR AI Chairs, bringing the total number of primary researchers to 30 (as of January 2020). Attracted and retained through Amii’s place in the Pan-Canadian AI Strategy, these individuals play a transformative role, both in the development of AI and in training the next generation of scientists.

Richard S. Sutton

Richard S. Sutton

Richard is a pioneer and leader in reinforcement learning and was recently named a Fellow of the Royal Society.

A professor at the University of Alberta and distinguished research scientist at DeepMind, Richard is most interested in understanding what it means to be intelligent, to predict and influence the world, to learn, perceive, act and think.

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Michael Bowling

Michael Bowling

Michael was named a Fellow of the Association for the Advancement of AI thanks to his landmark advancements in games.

A professor at the University of Alberta and Research Scientist at DeepMind, Michael is fascinated by the problem of how computers can learn to play games through experience. His teams’ milestone advances in poker -- including DeepStack, the first AI to beat human professionals at heads-up no-limit Texas hold’em -- represent theoretical leaps forward in the world of imperfect (or hidden) information games.

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Mo Chen

Mo Chen

Mo develops algorithms that allow robots to interact closely with humans in a way that is safe and natural.

An assistant professor at Simon Fraser University, Mo combines purely data-driven approaches and classical analytical approaches to find ways to make learning more effective. He is currently working on a project that leverages reinforcement learning to develop a robot that aims to autonomously stay in front of a person.

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Russ Greiner

Russ Greiner

Russ has advanced the field of computational psychiatry with his work on tools to help clinicians diagnose and assess schizophrenia.

A professor at the University of Alberta, Russ works closely with clinicians and researchers in medicine with a focus on developing and improving applications of machine learning in medicine, providing solutions for specific real-world problems across a range of clinical considerations.

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Yuhong Guo

Yuhong Guo

Yuhong works to automate the learning process and reduce the dependence of learning systems on human guidance.

A professor at Carleton University, Yuhong focuses on learning useful data representations and accurate classification models under various circumstances. Her ultimate research goal is to automate the learning process and reduce the dependence of learning systems on human guidance.

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Matthew Guzdial

Matthew Guzdial

Matthew develops creative AI, producing machine learning tools that support and enhance human creativity in areas such as video games.

An assistant professor at the University of Alberta, Matthew applies AI and machine learning to domains we would typically consider requiring human creativity, such as generating content for video games, visual art and creative commentary.

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Nidhi Hegde

Nidhi Hegde

Nidhi is developing fundamental approaches to privacy and ethics in AI, working to create algorithms that are private and fair by design.

An associate professor at the University of Alberta, Nidhi investigates how outcomes from AI and machine learning methods breach privacy and impact fairness and bias. She seeks to create algorithms that are private and fair by design, which involves new mathematical models and algorithms that provide desired outcomes while maintaining privacy and fairness.

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Levie Lelis Image

Levi Lelis

Levi designs intelligent systems that use machine-generated knowledge to teach humans interpretable strategies and problem-solving techniques.

An assistant professor at the University of Alberta, Levi develops intelligent systems that are able to augment people through teaching and collaboration. He seeks to use machine-generated knowledge to teach humans how to solve problems.

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Lie Ma

Lei Ma

Lei uses principles and methodologies in software engineering to bridge the gap between AI and its real-world applications.

An associate professor at the University of Alberta, Lei focuses on providing both fundamental quality assurance methodologies and systematic engineering support for building complex AI systems to make them more reliable, safe and secure. He works to bridge the gap between AI and its real-world applications.

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Martin Muller

Martin Müller

Martin is a world leader in modern heuristic search and holds the DeepMind Chair in Artificial Intelligence at the University of Alberta.

A professor at the University of Alberta, Martin is interested in developing efficient search methods for hard problems. He works on understanding and improving Monte Carlo tree search, exploring and sampling in reinforcement learning, exploration in SAT, search and deep learning for Hex, and combinatorial game theory.

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Patrick M. Pilarski

Patrick M. Pilarski

Patrick works with interdisciplinary teams to develop intelligent artificial limbs, launching an open-source community around the Bento Arm and HANDi Hand.

An associate professor at the University of Alberta, Patrick focuses on reinforcement learning, real-time machine learning, human-machine interaction, rehabilitation technology, and assistive robotics. He leads the Amii Adaptive Prosthetics Program – an interdisciplinary initiative focused on creating intelligent artificial limbs to restore and extend abilities for people with amputations.

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Dale Schuurmans

Dale Schuurmans

Dale tackles key machine learning challenges in knowledge representation for learning and in navigating complex model spaces.

A professor at the University of Alberta and Research Scientist at Google Brain, Dale has the long-term research goal of developing systems that learn predictive models from massive data sources when the requisite models are complex – for example: in perception, language interpretation, information extraction, bioinformatics, or robot learning.

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Matthew E. Taylor

Matthew E. Taylor

Matthew builds reinforcement learning systems with a focus on human-in-the-loop designs and application in real-world environments

An associate professor at the University of Alberta, Matt works to enable individual AI agents, and teams of agents, to learn tasks in real-world environments that are not fully known when the agents are designed; to perform multiple tasks, rather than just a single task; and to robustly coordinate with, and reason about, other agents.

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Osmar Zaiane

Osmar Zaïane

Osmar works on pattern discovery and information extraction from large databases and has helped to graduate more than 90 Master’s and Doctoral students and Postdoctoral Fellows.

A professor at the University of Alberta, Osmar works on data mining from disparate heterogeneous data sources, such as on the Internet, as well as the analysis of complex information networks, also known as social network analysis.

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Sandra Zilles

Sandra Zilles

Sandra develops methods for modelling and exploiting special types of interaction with machines to enable them to learn using less data than conventional approaches.

A professor at the University of Regina, Sandra focuses on theoretical aspects of machine learning. The models and algorithmic techniques that will ultimately arise from this research may provide efficient solutions to complex problems in artificial intelligence – at a lower cost and with less data than is currently possible.

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Collaborating with academic partners, Amii builds up the next generation of researchers and the workforce leaders of tomorrow by supporting grad students across Canada.

Amii’s Fellows & Canada CIFAR AI Chairs work out of the University of Alberta and institutions across Canada, including Carleton University, Simon Fraser University, the University of British Columbia and the University of Regina.

By advancing fundamental and applied research in AI and machine learning, Amii’s academic researchers train the world’s brightest minds to become leaders in the science and business of AI. Alumni have gone on to join and lead labs at many of the world’s most innovative organizations, including DeepMind, Google Brain and Amazon, and have been named Canada CIFAR AI Chairs at universities across Canada.

This past year, 371 early-career researchers studied with Amii’s primary researchers  – from Undergraduate to PhD-level.

Collaborating with academic partners, Amii builds up the next generation of researchers and the workforce leaders of tomorrow by supporting grad students across Canada.

Amii’s Fellows & Canada CIFAR AI Chairs work out of the University of Alberta and institutions across Canada, including Carleton University, Simon Fraser University, the University of British Columbia and the University of Regina.

By advancing fundamental and applied research in AI and machine learning, Amii’s academic researchers train the world’s brightest minds to become leaders in the science and business of AI. Alumni have gone on to join and lead labs at many of the world’s most innovative organizations, including DeepMind, Google Brain and Amazon, and have been named Canada CIFAR AI Chairs at universities across Canada.

This past year, 371 early-career researchers studied with Amii’s primary researchers  – from Undergraduate to PhD-level.

Amii researchers work at the foundations and forefront of scientific discovery.
Literacy Case Study

Literacy in a digital & multicultural world

Alona Fyshe (Fellow and Canada CIFAR AI Chair at Amii and assistant professor at the University of Alberta) was named a co-recipient of a $2.5 million grant to study literacy in a digital and multicultural world. The project, Ensuring Full Literacy in a Multicultural and Digital World, is led by Janet Werker of the University of British Columbia with Fyshe acting as Co-Director. The multidisciplinary team of experts brings together researchers from the disciplines of psychology, computing science, linguistics and anthropology, among others.

Over the next seven years, the project will study literacy across a variety of backdrops, including language acquisition and development, bilingualism, differences in culture, and the emergence and use of new technologies such as reading on tablets or learning to read with an app.

“We’ve brought together a truly cross-disciplinary team who are all so passionate about language learning and literacy. It was a great experience just writing the grant, and now I can’t wait to get started on this important work,” said Fyshe last May.

Advances in computational psychiatry

This past year, Russ Greiner (Fellow-in-Residence and Canada CIFAR AI Chair at Amii) and his collaborators continued to push the boundaries of computational psychiatry through their work on creating AI-based tools to predict schizophrenia by analysing brain scans. The tools can support clinical psychiatrists in diagnosing the disorder in patients and family members and in providing data-driven assessments of common symptoms.

Their latest tool, dubbed EMPaSchiz, was co-developed with teams from the University of Alberta, the National Institute of Mental Health and Neurosciences in India. The tool has since been developed with a machine learning algorithm to predict if an individual has schizophrenia, based on features extracted from MRI scans. According to the research team, this research “demonstrates the potential of machine-learned diagnostic models to predict state-independent vulnerability, even when symptoms do not meet the full criteria for clinical diagnosis.”

Advances in Psychiatry Case Study
Predicting Ethnicity Case Study

Predicting ethnicity to meet gaps in public health

Kai On Wong, working with Yutaka Yasui (Fellow at Amii and professor at the University of Alberta) and Osmar Zaïane (Fellow and Canada CIFAR AI Chair at Amii and professor at the University of Alberta), developed a machine learning approach to predicting ethnicity using personal name and census location in Canada. The researchers also collaborated with Faith Davis of the University of Alberta.

Together, the team conducted a large-scale machine learning framework to predict ethnicity using a novel set of name and census location features. Machine learning can help uncover missing information about ethnicity and indigenous status, key social determinants of health that often go unreported in large databases.

“If a database currently lacks ethnicity information, we will not be able to tell whether certain ethnic groups have higher rates of disease or worse clinical outcomes,” said Wong. “This is a way to unlock that missing dimension from existing data sources, which may help us understand, monitor and address issues such as social inequities and racism in Canada.”

Richard S. Sutton leads in reinforcement learning

In May 2021, Richard S. Sutton was elected a Fellow of the Royal Society, the world’s oldest scientific academy. Richard, who is Chief Scientific Advisor, Fellow and Canada CIFAR AI Chair at Amii and also a professor at the University of Alberta, was honoured for his long standing contributions to the development of the field of AI and for his pioneering leadership in the area of reinforcement learning.

“I am deeply humbled and honoured to join the ranks of Isaac Newton and Charles Darwin as a fellow of the Royal Society,” said Sutton, who is also a Distinguished Research Scientist at DeepMind in Edmonton.

Over his career, Sutton has made a number of significant contributions to the field, including the theory of temporal-difference learning, the actor-critic (policy gradient) class of algorithms, the Dyna architecture (integrating learning, planning and reacting), the Horde architecture, and gradient and emphatic temporal-difference algorithms – among other advancements.

Richard Sutton Case Study
Martha

Martha White receives Killam Accelerator Research Award

Martha White (Canada CIFAR AI Chair and Fellow at Amii and assistant professor at the University of Alberta) is a recipient of the prestigious Killam Accelerator Research Award to further support her leading-edge research on reinforcement learning. The Killam Trusts provide scholarships, fellowships and prizes to post-graduate scholars at Canadian universities, supporting research with a focus on social impact, accessibility, diversity, and making the world a better place.

The competitive award has a value of $75,000 per year for a three-year term based on outstanding promise shown by a faculty member in both their research output and impact of their scholarly activity.

“It's an honor to be selected amongst so many great researchers at the University of Alberta,” said White of the recognition. “My research is pushed forward by an amazingly talented group of graduate students. We are a collaborative team, and this award will directly fund several of those researchers, allowing them to focus on these hard and important research questions.”

Business
We empower competitive advantage in businesses, helping them build AI expertise and capabilities.
Amii helps clients grow, improve operations and solve complex problems using AI.
Roche Case Study

Roche partnership drives digital transformation in health

In November 2020, Roche Canada announced the launch of the Roche AI Centre of Excellence -- now called AI with Roche (AIR) -- the first collaborative centre to combine the expertise of all three national AI institutes under the CIFAR Pan-Canadian AI Strategy (Amii, Mila and the Vector Institute). The center works to deliver quality AI-based digital solutions that optimize and reduce the cost of healthcare delivery, improve health outcomes, and enable Canada to learn and nimbly respond to opportunities and potential challenges in the healthcare system. 

In March 2021, AIR collaborated with Answer ALS and EverythingALS to launch an initiative called the End ALS Challenge, with the support of ALS Society of Canada, Ontario Brain Institute (OBI) and NetraMark Corp. The project focused on surfacing insights through an open data competition that connects the global AI and neuroscience communities to better understand the overall biology of amyotrophic lateral sclerosis (ALS), and improve diagnosis and drug discovery for ALS patients.

OKAKI uses AI to address the opioid crisis

Amii supported public health informatics company OKAKI in pursuing their first AI project, using ML to save lives by preventing opioid overdoses. Amii provided support, guidance, mentorship and oversight to OKAKI as the team defined their ML problem and worked through their project.

The resulting paper Safe opioid prescribing: a prognostic machine learning approach to predicting 30-day risk after an opioid dispensation in Alberta, Canada was published in BMJ Open on May 26, 2021. The study concludes that ML classifiers are more effective than current approaches in predicting opioid-related adverse outcomes within the first 30 days.

The OKAKI team now has a solid foundational understanding of AL/ML, with the ability for technical teams and managers to communicate effectively about ML concepts and projects; they also have 11 employees working on ML projects and have learned how, and where, to access talent for future hires.

OKAKI Case Study
Matt Taylor Case Study

Matthew Taylor co-authors Harvard Business Review article on industrial applications of reinforcement learning

Earlier in 2021, Matthew Taylor (Canada CIFAR Chair in AI and Fellow-In-Residence at Amii, associate professor at the University of Alberta) co-authored a Harvard Business Review article on how companies may use reinforcement learning to power innovation. 

The article explains: “Companies such as Netflix, Spotify, and Google have started using it, but most businesses lag behind. Yet opportunities are everywhere.”

The driving force behind DeepMind’s AlphaGo program and a specialty of many Amii researchers, reinforcement learning is a branch of machine learning that enables AI systems to learn through experience. Reinforcement learning systems interact with their environments, often through trial and error, earning positive or negative rewards based on their actions. Humans define the overall task and relevant rewards that the system uses to discover the best action to take in a given situation.

“The technology shines when used to automate or optimize business processes that generate dense data, and where there could be unanticipated changes you couldn’t capture with formulas or rules. If you can spot an opportunity ... there’s a window to apply this technology to outpace your competition.”

The article provides a digestible overview of reinforcement learning, as well as examples of how companies are currently using the technique, and teaches business people how to spot an opportunity to apply reinforcement learning. 

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ISL Adapt launches RL-driven water treatment pilot project in Drayton Valley

When the Town of Drayton Valley needed to replace their aging water treatment plant, the Town commissioned ISL Engineering and Land Services to build a sustainable and environmentally conscientious facility. ISL Engineering created ISL Adapt to work specifically with experts at Amii and the University of Alberta to develop a reinforcement learning-based pilot project that aims to produce cleaner, safer drinking water, lower energy emissions and reduce chemical usage.

The system has been built to identify, predict and respond to trends in all stages of water treatment, tracking how events and changes affect each step of the process. For example, spring runoff produces particularly dirty raw water, resulting in tap water that requires more chemical intervention and may not always taste good after treatment. A reinforcement learning system could predict and respond to such seasonal changes by optimizing filtration processes and chemical usage, resulting in water that tastes good even after treatment.

Leading the research team is Martha White (Canada CIFAR AI Chair and Fellow at Amii and associate professor at the University of Alberta). She believes that this model is applicable to industrial plants, and has the potential to spark an entire industry of AI control in Alberta, with potential to improve environmental standards, energy use and human health. 

The pilot is set to end in 2022. The results will be used to set up ISL Adapt as a leader in bringing affordable, AI-driven filtered water to communities that struggle to meet ever-evolving demands of water treatment in Alberta and beyond.

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Imperial Oil Carolina Quiroz Juarez

Imperial Oil uses ML to predict pipeline incidents & optimize wellsite production

In 2020, Amii and Imperial Oil Limited (IOL) collaborated to investigate the feasibility of using machine learning to predict and prevent flow assurance events on pipelines, with the ultimate goal of improving pipeline operation and decreasing downtime. Amii guided an IOL Junior Data Scientist -- a recent graduate from Amii’s ML Technician I Course -- as she developed a proof-of-concept using data from an experimental pipeline. IOL and Amii also worked on a proof of concept for optimizing new well development. The early work suggests the potential to utilize mathematical optimization in this area.

IOL also leveraged Amii’s extensive machine learning expertise to complement their in-house capabilities. A series of eight whiteboarding sessions allowed IOL business units to brainstorm opportunities or troubleshoot current problems with Amii experts, fostering an understanding of the risks and challenges for each idea. Through quarterly research presentations, Amii researchers fostered knowledge exchange amongst IOL data scientists, leading them through discussions around specific research papers.

Workforce
& Talent
We nurture a globally-competitive talent pool and AI community.
Amii grows and diversifies the talent pool.
Kory Mathewson Case Study

Kory Mathewson develops first AI to perform improv

Amii alum Dr. Kory Mathewson’s research blends computing with improvisational theatre, focusing on the interaction between humans and machines. He applies this research in real life through performances with Improbotics, a multinational theatre company he co-founded with fellow researcher and improvisor Piotr Mirowski.

Under the supervision of Amii Fellow Patrick M. Pilarski, Mathewson’s PhD thesis focused on improvised theatre performed alongside intelligent machines. He developed A.L.Ex. (the Artificial Language Experiment), the first artificial improvisor, which uses advanced natural language processing and machine learning to perform alongside human performers. While live on stage, actors interact with the language model – trained on thousands of movie scripts and other sources – to co-create improv comedy.

Mathewson now works as a Research Scientist with DeepMind, a Lab Scientist with the Creative Destruction Lab, advises a number of venture-backed startups and performs on stage alongside humans and machines.

Leah Martin contributes to Sweden’s COVID-19 response

Amii alum Dr. Leah Martin completed her PhD at the University of Alberta’s School of Public Health followed by a Postdoctoral Fellowship under the supervision of Yutaka Yasui (Amii Fellow and professor at the University of Alberta). Together, they developed models to predict influenza-like emergency department visit volumes to support public health decision making.

Currently, Martin is working on Sweden’s response to COVID-19 at the Public Health Agency of Sweden as an infectious disease epidemiologist. Prior to the pandemic, she investigated novel approaches to surveillance of tick-borne encephalitis—a high-priority disease in Sweden with increasing incidence. She also investigates the impact of interventions aimed at infectious disease prevention, which has included work on hepatitis C and COVID-19.

Martin's efforts aim to improve health and prevent disease, while directly informing public health action and policies.

Leah Martin Case Study
Sarah Davis Case Study

From Undergrad interest to Masters program:
Sacha Davis joins the Greiner Lab

In the second year of Sacha Davis’ undergraduate program -- Biology major and Computing Science minor -- they began to seek research experience. Following an interview with Amii Fellow & Canada CIFAR AI Chair Russ Greiner, they were accepted into the Greiner Lab, a multidisciplinary group whose focus is machine learning research for medical applications. There, Davis began pursuing a summer research project.

"I was excited to have been accepted to the Greiner Lab as an undergraduate student. Whenever Russ is interviewing someone for the Lab or a project, I feel like he’s not just looking for technical computing science experience; he’s also seeing people’s personality, emotional intelligence, and skill sets from different disciplines. Even though I lacked the technical knowledge at the time, Russ saw my Biology background as a strength to help add more diversity to the research group," says Davis.

Davis now pursues a MSc in Computing Science with a research background in patient-specific survival and hospital readmission prediction, NLP-assisted cancer pattern recognition, and statistical heritability under the supervision of Greiner, among others during their undergrad research. They currently work at Amii as an ML Intern.

Carolina Quiroz Juarez builds network and AI knowledge at woman-focused program

Carolina Quiroz Juarez is currently studying at the University of Alberta, pursuing a Master’s degree in software and intelligent systems engineering. She was part of the inaugural cohort for the AlbertaWomen.AI program (recently evolving into the Kickstart Program), a career development initiative for women and female-identifying students at an Undergraduate to Postdoctoral level, as well as early-career STEM professionals .

“One thing I found particularly helpful from the program was the opportunity to ask questions to women working in the field, in both aspects -- professional and personal. Frequently, there is an almost indistinguishable border between both aspects at work, with the second aspect a difficult one to get insights as a student,” says Quiroz Juarez.

Through the program, she saw new career opportunities in Edmonton and increased her network of peers and mentors. Most notably, she was awarded a scholarship from Microsoft to attend Amii’s ML Technician Certificate course where she learned to construct machine learning models, make informed decisions related to data and articulate a machine learning framework to support business outcomes.

Quiroz Juarez continues to pursue research in intelligent control of Vanadium redox flow batteries for residential applications using Q-learning and neural networks, where the goal is to find battery optimal operational strategies that translate into monthly electricity bill savings for the household customer.

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Carolina Quiroz Juarez Carolina Quiroz Juarez
Alejandro Coy Case Study

ML Technician Certificate course turned Alejandro Coy’s programming hobby into a career

Alejandro Coy’s journey through Amii’s Machine Learning (ML) Technician Certificate course ultimately led him into a job in the field. He had been programming in his free time for a few years, which led him to consider a career in data science and machine learning. In the ML Technician Certificate course, he saw an opportunity to bring his passion into his day job.

As part of the course’s capstone project, each group was required to present their solution to industry and domain experts. This prepares students for delivering technical presentations to management in a compelling and informative way, explaining how the product works and its benefits.

Alejandro now works as a Senior Data Specialist, Data Efficiencies at Alberta Investment Management Corporation. His hobby, which he once pursued on evenings and weekends, has become his career.

“Amii training was a huge factor to my education and I learned about the job thanks to networking in the course ... In my job interview, I presented the capstone project and the employers were very impressed," says Coy.

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The Future
As leaders and innovators, we will continue to transform. What lies ahead?

The realities of the past year provided incredible opportunities for Amii to listen and learn from the community. With this new knowledge, Amii has transformed its offerings:

Economic Recovery

Reflecting on 2020/2021, one of the biggest challenges and opportunities facing Amii was the unanticipated disruption of the COVID-19 pandemic. The Amii team tackled complications head-on and worked to provide immediate value to the community, as well as pivoting business strategies to have a greater focus on economic recovery and growth going forward.

As Alberta navigates the current and long-term economic impacts of the pandemic and changes in the energy market, Amii leverages resources, expertise, and community to advance Alberta’s economic recovery. Artificial intelligence and machine learning are key strategic opportunities for long-term recovery from these crises and will accelerate the diversification of the Alberta economy.

By adopting and applying AI in their businesses, Alberta-based companies – from startups to small- and medium-sized businesses and multinational corporations – will gain a competitive advantage that can support their efforts to:

  • Rapidly innovate business models to adapt to new realities 
  • Develop a technology-first mindset to respond to business challenges 
  • Improve processes and work practices to improve financial performance
  • Strengthen resilience
Imperial Oil

Economic Recovery

Reflecting on 2020/2021, one of the biggest challenges and opportunities facing Amii was the unanticipated disruption of the COVID-19 pandemic. The Amii team tackled complications head-on and worked to provide immediate value to the community, as well as pivoting business strategies to have a greater focus on economic recovery and growth going forward.

As Alberta navigates the current and long-term economic impacts of the pandemic and changes in the energy market, Amii leverages resources, expertise, and community to advance Alberta’s economic recovery. Artificial intelligence and machine learning are key strategic opportunities for long-term recovery from these crises and will accelerate the diversification of the Alberta economy.

By adopting and applying AI in their businesses, Alberta-based companies – from startups to small- and medium-sized businesses and multinational corporations – will gain a competitive advantage that can support their efforts to:

  • Rapidly innovate business models to adapt to new realities 
  • Develop a technology-first mindset to respond to business challenges 
  • Improve processes and work practices to improve financial performance
  • Strengthen resilience

Our Vision for 2025

For the past twenty years, Alberta has invested in the foundations of AI research. In Amii’s first three years, we built the foundations for Alberta’s leadership in the business of AI. 

In the years to come, Amii is committed to securing Alberta’s AI Advantage to drive economic growth. By 2025, the Amii team envisions:

  • Global research recognition. Amii is recognized as a global exemplar of machine intelligence research and how it can generate a substantial positive impact on the economy and society.
  • Stronger startups. Startups connected to Amii are using ML to be world leaders to solve problems and build great companies.
  • AI essential to business. ML is a core competency in most Alberta companies that use it to build competitive advantage and create the future direction of Alberta.
  • Multinational corporate investment. Large companies worldwide want to set up in Edmonton and work with Amii to tap into cutting-edge talent and expertise.
  • High student retention. The majority of Alberta students stay within the province to take advantage of its great ML opportunities.