Prof. Jude Dzevela Kong
Kong is a professor in the Dalla Lana School of Public Health, University of Toronto, where he serves as the director of the Laboratory for Artificial Intelligence (AI) and Mathematical Modeling. Additionally, he is the Director of the Africa-Canada Artificial Intelligence and Data Innovation Consortium and the Global South Artificial Intelligence for Pandemic and Epidemic Preparedness and Response Network. He is also the Regional Node Liaison to the steering committee of the Canadian Black Scientist Network. He obtained his Ph.D. in Mathematics with a certificate in AI from the University of Alberta, his MSc in Engineering Mathematics from the University of Hamburg, Germany, and the University of L’Aquila, Italy. His B.Sc. in Computer Science and Mathematics was acquired at the University of Buea, Cameroon, and his B.Ed. in Mathematics was earned at University of Yaounde I, Cameroon. He did a 2-years of postdoc at Princeton University. Dr. Kong is an expert in AI, data science, mathematical modeling, and mathematics education.
His principal research program focuses on designing and deploying AI, data science, and mathematical methodologies and technologies to build equitable, resilient governance strategies and increase societal preparedness for future global pandemics and climate disasters. During the COVID-19 pandemic, Dr. Kong led a team of 52+ researchers across nine African countries, using AI to help contain and manage the virus. In 2022, he founded the AI4PEP network, overseeing 160+ researchers from 16 countries. The network focuses on leveraging Southern-led responsible AI solutions to enhance public health systems for better prevention, preparedness, and response to disease outbreaks. Dr. Kong’s many research contributions and exceptional leadership have earned him several prestigious awards and recognitions.
These include the York University (YU) Research Leader Award in 2020; recognition as one of Canada’s Innovation Research Leaders in 2021, recognition as a Black Hero of Operational Research by the Operational Research Society in 2021, recognition as a YU Community Change Maker in 2022; recognition from YU Magazine for enumerating positive change by inspiring Black students to aspire in 2022; nomination for the 2022 Postdoc Supervisor of the Year Award; 2022 Faculty of Science, YU Early Career Researcher Award; YU 2023 Research Leader Award and the 2023 YU President’s Emerging Research Leadership Award. He is an Editor for Data & Policy Journal; Royal Society Science; Scientific Reports, and Big Data and Information Analytics.
Our Lab Objectives
- Design and deploy AI, data science, and mathematical methodologies and technologies
- To enhance public health preparedness and response to emerging and re-emerging infectious disease outbreaks
- For adaptations of fish and fishing communities to rapid climate velocities
- For greenhouse gas emission from oil sand tailings
- For Phytoplankton dynamics
2. Establish and maintain a dedicated group of academic researchers and train highly qualified individuals to address knowledge gaps, capacities, and generate solutions.
3. Inform community level, national, regional, and global policies, and practices on the use of AI, Mathematics, and data science methods to improve equity and to provide important insights into local and global-scale socio-ecological challenges.
Join us
We are actively looking for passionate undergraduate and graduate students, and postdocs to join our group. If our scientific interests overlap, and you will like to join us, please contact us before you apply so that we can discuss your application. In your email, please include a description of your interests and how they fit into our lab along with a CV, and unofficial transcripts. All students are welcome here regardless of race, religion, gender identification, sexual orientation, age, or disability status.
We train our postdocs, grad students and undergrad students to be experts in artificial intelligence, data science, mathematical and statistical modelling, computational modelling , data management, working with policy makers. Most of our graduates easily find jobs in the industry, governments, and academia.