This virtual event is part of the AI & Women initiative from the Computer Research Institute of Montreal, the WinAAA meetup and held in parallel to the 39e International Conference on Machine Learning.
4PM – 7PM (EST Time)
Artificial intelligence (AI) has made significant progress since its inception, and the industry has opened some coveted positions for professionals worldwide. Despite the shortage of qualified and experienced professionals, talented women who enable AI organizations to achieve their ambitions remain underrepresented in the area. The 2020 World Economic Forum report has shown that women represent only 26% of data and AI positions.
On the other hand, approximately 2% of the world’s population suffers from various types of mental health disorders. Psychological health problems such as depression are among the ten leading causes of disability all around the world. Due to the extent of the problem, the United Nations included it as part of the Health and Wellness goal for the 2030 Agenda for Sustainable Development. Thus, fostering research partnerships that result in the development of AI-driven solutions to measure, diagnose, and treat mental and neurodegenerative disorders is critical.
Supported by the International Machine Learning Society (IMLS), it is the leading international academic conference in machine learning and artificial intelligence research.
The 39th edition will be held from
July 17 to 23, 2022.
CRIM is a NPO that provides world-class IT expertise to create socio-economic value from scientific and technological advances in digital technology.
It connects academic research and industrial reality to deliver projects that have concrete results
This discussion group aims to bring together women who are passionate about Artificial Intelligence.
It encourages the discussion among its members to increase women's presence in the technology and research fields.
4 PM - Opening
4:10 PM - Ms. Anna Fellander
AI and Ethical AI in Practice
4:35 PM - Dr. Nevicia Case
Identifying mental health predictors of risky driving among first-time driving while impaired (DWI) offenders
5:00 PM - Dr. Saee Paliwal
AI Applications in Healthcare
5:25 PM - First Q&A period
5:30 PM - Panel discussion animated by Prof. April Khademi
Diversity and Mental Health in AI
6 PM - 15 minutes break
6:15 PM - Ms. Marilou Guillemette
Longitudinal Audio Data as a Core for Mental Health Treatment and Monitoring
6:30 PM - Ms. Yuexing Hao
Patient-Centered Frameworks for Clinical Decision Selections Employing Machine Learning Techniques
6:45 PM - Second Q&A period
6:50- PM - Closing Session
Mah Parsa is a postdoctoral researcher at CRIM focusing on developing and deploying machine learning-based speech and language assessment methods for neurodegenerative disease (e.g., Alzheimer's disease) and psychiatric disorders (e.g., schizophrenia).
Sepid Parsa is an independent architect and researcher who focuses on (1) the use of artificial intelligence for artistic applications, particularly art programs that help patients with mental illness and (2) the design of educational organizations to increase learners' creativity.
Anna is one of Sweden’s leading experts on the effects of digitalization on organisations, society and the economy. She was the Head of Financial Analysis of the Prime Minister of Sweden and an advisor to the Swedish government and the Chief Economist at Swedbank.
In 2016, Anna realized AI technology would drastically impact the economy, businesses, people and society at-large, all while causing a negative externality — a new type of digital pollution. No one was holding technology companies accountable for such impacts. Regulators have had difficulties interpreting AI in order to appropriately regulate it and customers didn’t understand how their data was being used in the black box of AI algorithms.
Anna’s multidisciplinary research group at the Royal Institute of Technology was the origin to anch.AI, which was founded in 2018 to investigate the ethical, legal and societal ramifications of AI. The anch.AI platform is an insight engine with a unique methodology for screening, assessing, mitigating, auditing and reporting exposure to ethical risk in AI solutions. anch.AI believes that all organisations must conform to their ethical values and comply with existing and upcoming regulation in their AI solutions, creating innovations that humans can trust. It is an ethical insurance for companies and organisations.
Nevicia completed her doctoral research in the Department of Psychiatry at McGill University, where she was awarded funding by Fonds de recherche du Québec Santé for her research on cognitive factors in risky driving.
Her findings improve the prediction of risky driving among male drivers with a first-time
conviction of driving while impaired. During her Master’s, Nevicia’s research also identified the neuropsychological profile of cerebral amyloid angiopathy.
Beyond her scientific research, Nevicia is a
One Young World Scholar at Johnson & Johnson, the interim Vice-Curator of the Montreal Hub of the World Economic Forum’s Global Shapers Community, and a co-founder of Health Innovation Initiative.
Saee has a background in Physics and Computational Neuroscience, focusing on computational cognitive science, trying to understand better how humans learn and make decisions in uncertain environments.
Her doctorate work centered on an algorithmic understanding of how learning and decision making differ in patients with Gambling Disorder and other behavioral addictions.
She is passionate about tech applications in healthcare and is currently working as a Lead AI Scientist at BenevolentAI, using machine learning to augment drug discovery. Saee cares deeply about empowering and uplifting underrepresented groups in STEM, and is active as a mentor and advocate at Benevolent.
Outside of work, Saee is an avid musician, focusing on European music from the medieval period, is an enthusiastic cook, and a new mom.
Marilou is a Chief of Research and Development Officer.
She is a PhD student in AI in Medical Sciences and a researcher at Neonous.ai focusing on Natural Language Processing (NLP), Natural Language Understanding (NLU), automatic speech recognition (ASR), Machine Learning, analytics and human behaviour applied to healthcare, specifically in mental health.
Yuexing Hao is a Ph.D. student in Human Behaviour Design at Cornell University. She holds two Computer Science degrees from Rutgers University (B.A.) and Tufts University (M.S). During her study, Yuexing won Meritorious Prize in the 2020 Interdisciplinary Contest in Modeling (ICM) and Graduate Student Research Competition Award at Tufts University. Yuexing also published several papers on Intelligent System Conference, HHAI, and Bioinformatics. Currently, her research focus is on Health Intelligence, Human-Computer Interaction, and VR/AR.
Lauren Erdman is the manager of the Machine Learning Core at the SickKids Hospital Center for Computation Medicine.
She is currently completing a PhD in Computer Science at University of Toronto and will be joining Cincinnati Children's Hospital as faculty in January.
Her research is primarily focused on developing and applying machine learning (ML) methods for data integration and improved translational discovery and technology development for genetics, genome biology, complex disease, and more recently, medical imaging.
Dr. Eirene Seiradaki is the Director of Research Partnerships for Borealis AI’s network of labs where she develops outreach strategies and drives collaborative research initiatives with leading academic institutions. Her vision has helped propel the momentum behind Borealis AI’s rapid growth across the country.
At Borealis AI, Eirene has established partnerships with research institutions, such as the University of Toronto, University of Waterloo, McGill, University of Alberta, University of British Columbia, Simon Fraser University, Vector Institute, MILA, Amii, MIT, Washington State University, and more.
Eirene’s portfolio also includes internal programs and external partnerships, supporting diversity and inclusion initiatives, AI for social good, talent deployment and more. With other team members, she designed and built the Let's SOLVE it undergraduate mentorship program for Borealis AI, which was supported by several universities and became part of the National AI Training Programs under the wing of CIFAR along programs, such as the AI4Good Lab and the DL/RL Summer School.
Eirene holds a Ph.D. from the University of Toronto and an M.A. from Princeton University. Prior to joining Borealis AI, she conducted research and taught a wide range of courses at both schools. Inspired by her doctoral research in Classical Economics, which focused on the dynamics of exchange and its implications in social institutions, relations and alliances, Eirene is passionate about meaningful exchanges and partnerships between universities and industry as a means to more efficiently address the challenges that both sides face.
Panel moderator
April Khademi is Associate Professor of Biomedical Engineering at Toronto Metropolitan University (formerly Ryerson University) and Principle Investigator of the Image Analysis in Medicine Lab (IAMLAB), which specializes in the design of machine learning algorithms for pathology and radiology images.
She is also an Affiliate Scientist at St. Michael’s Hospital and a Member of Institute for Biomedical Engineering, Science & Technology (iBEST). April holds a Ph.D. degree in Electrical Engineering from the University of Toronto and had previous roles in research at University of Guelph, GE Healthcare/Omnyx, Pathcore Inc., Sunnybrook Research Institute and Toronto Rehab Institute.
She is a licensed Professional Engineer in Ontario and IEEE Senior Member. More information: https://www.torontomu.ca/akhademi/ and twitter: @aprilkhademi.
The main goal of this social meeting is to promote women’s roles in AI for mental health applications through :
This allows women in AI and ML working for Mental Health applications to expand their knowledge regarding ongoing AI research projects and innovative AI applications. They can also receive valuable feedback from other AI communities worldwide.