Catalyst Fellowship Program
Advancing the Catalyst’s mission through original research and industry engagement.
Overview
The Catalyst Fellowship Program is a major initiative dedicated to advancing the Catalyst’s mission — to empower Canadians and Canadian businesses to seize the opportunities and tackle the challenges of cybersecurity — through original research and industry engagement.
Selected from academics at Toronto Metropolitan University and professionals working in a wide variety of organizations and sectors, Catalyst Fellows will undertake original research and other projects related to the Catalyst’s work; engage closely with Catalyst program participants and staff; and share their expertise in an environment dedicated to innovation and collaboration in cybersecurity.
The fellowship cohort for 2022-2023 is filled. Please check back in January 2023 for application information.
Research Stream:
This stream is open to any faculty member currently employed at Toronto Metropolitan University. Catalyst Fellows in this stream will advance their academic research in cybersecurity or related topics, while engaging with the Catalyst’s work, program participants and staff as described above.
Industry Stream:
This stream is open to professionals from all industry sectors and across all career stages, including private industry, government and government agencies, and not-for-profit organizations. Catalyst Fellows in this stream will advance projects of their own design in cybersecurity or related topics, while engaging with the Catalyst’s work, program participants and staff as described above.
Next Cohort Intake
September 2023
Location
Virtual & In-Person
Program Duration
One Year
Time Commitment
Part-time
Applications
Open in January 2023
Contact
Next Cohort Intake
September 2023
Location
Virtual & In-Person
Program Duration
One Year
Time Commitment
Part-time
Applications
Open in January 2023
Contact
Overview
The Catalyst Fellowship Program is a major initiative dedicated to advancing the Catalyst’s mission — to empower Canadians and Canadian businesses to seize the opportunities and tackle the challenges of cybersecurity — through original research and industry engagement.
Selected from academics at Toronto Metropolitan University and professionals working in a wide variety of organizations and sectors, Catalyst Fellows will undertake original research and other projects related to the Catalyst’s work; engage closely with Catalyst program participants and staff; and share their expertise in an environment dedicated to innovation and collaboration in cybersecurity.
The fellowship cohort for 2022-2023 is filled. Please check back in January 2023 for application information.
Research Stream:
This stream is open to any faculty member currently employed at Toronto Metropolitan University. Catalyst Fellows in this stream will advance their academic research in cybersecurity or related topics, while engaging with the Catalyst’s work, program participants and staff as described above.
Industry Stream:
This stream is open to professionals from all industry sectors and across all career stages, including private industry, government and government agencies, and not-for-profit organizations. Catalyst Fellows in this stream will advance projects of their own design in cybersecurity or related topics, while engaging with the Catalyst’s work, program participants and staff as described above.
Current Fellows
The Catalyst is excited to announce the inaugural cohort of the Catalyst Fellowship Program for the 2022-23 academic year.
Burcu Bulgurcu
Dr. Burcu Bulgurcu is an Associate Professor at Toronto Metropolitan University, Department of Information Technology Management. Her research and teaching interests are cybersecurity, information privacy, social media and business analytics, and data visualization. As a Catalyst Fellow, Dr. Bulgurcu will carry out a groundbreaking investigation on cybersecurity management for remote workforce, offering insight on emerging and escalating cybersecurity challenges when employees are outside corporate firewalls.
Burcu Bulgurcu
Dr. Burcu Bulgurcu is an Associate Professor at Toronto Metropolitan University, Department of Information Technology Management. Her research and teaching interests are cybersecurity, information privacy, social media and business analytics, and data visualization. As a Catalyst Fellow, Dr. Bulgurcu will carry out a groundbreaking investigation on cybersecurity management for remote workforce, offering insight on emerging and escalating cybersecurity challenges when employees are outside corporate firewalls.
Monika Freunek
Dr.-Ing Monika Freunek is an experienced researcher and lecturer, project manager and executive leader in the fields of critical infrastructure and cybersecurity. Dr.-Ing Freunek has more than 15 years of experience in IoT systems, microsystem technologies, cybersecurity, data science and machine learning. As a Catalyst Fellow, Dr.-Ing Freunek will investigate available approaches to IoT-security in research and industry and determine theoretical limits of achievable security in distributed systems.
Monika Freunek
Dr.-Ing Monika Freunek is an experienced researcher and lecturer, project manager and executive leader in the fields of critical infrastructure and cybersecurity. Dr.-Ing Freunek has more than 15 years of experience in IoT systems, microsystem technologies, cybersecurity, data science and machine learning. As a Catalyst Fellow, Dr.-Ing Freunek will investigate available approaches to IoT-security in research and industry and determine theoretical limits of achievable security in distributed systems.
Rasha Kashef
Dr. Rasha Kashef is an Assistant Professor at Toronto Metropolitan University, Department of Electrical, Computer, and Biomedical Engineering. Her scholarship on machine learning focuses on unlocking the hidden meaning in big data, with applications in marketing, e-commerce, security, software systems and health care. As a Catalyst Fellow, Dr. Kashef will develop effective models for improving the robustness of recommendation systems using advances in adversarial machine learning.
Rasha Kashef
Dr. Rasha Kashef is an Assistant Professor at Toronto Metropolitan University, Department of Electrical, Computer, and Biomedical Engineering. Her scholarship on machine learning focuses on unlocking the hidden meaning in big data, with applications in marketing, e-commerce, security, software systems and health care. As a Catalyst Fellow, Dr. Kashef will develop effective models for improving the robustness of recommendation systems using advances in adversarial machine learning.
A.J. Khan
A.J. Khan is Co-Founder and Chief Executive Officer of Vehiqilla Inc. Vehiqilla aims to meet today’s changing threat landscape in in-vehicle security and supply chain security. A.J. is a recognized leader in the automotive security field who has collaborated with the Automotive Parts Manufacturing Association of Canada, the European Union Information Security Agency and Transport Canada. As a Catalyst Fellow, A.J. will develop a Virtual Security Operations Center for cyber threat monitoring of connected and autonomous vehicles.
A.J. Khan
A.J. Khan is Co-Founder and Chief Executive Officer of Vehiqilla Inc. Vehiqilla aims to meet today’s changing threat landscape in in-vehicle security and supply chain security. A.J. is a recognized leader in the automotive security field who has collaborated with the Automotive Parts Manufacturing Association of Canada, the European Union Information Security Agency and Transport Canada. As a Catalyst Fellow, A.J. will develop a Virtual Security Operations Center for cyber threat monitoring of connected and autonomous vehicles.
Reza Samavi
Dr. Reza Samavi is an Assistant Professor at Toronto Metropolitan University, Department of Electrical, Computer, and Biomedical Engineering where he runs the Trustworthy Artificial Intelligence research Lab (TAILab). As a Catalyst Fellow, Dr. Samavi will investigate the characteristics of machine learning systems when incorporating privacy and security requirements by design into the model, and assessing the trustworthiness of such learning systems.
Reza Samavi
Dr. Reza Samavi is an Assistant Professor at Toronto Metropolitan University, Department of Electrical, Computer, and Biomedical Engineering where he runs the Trustworthy Artificial Intelligence research Lab (TAILab). As a Catalyst Fellow, Dr. Samavi will investigate the characteristics of machine learning systems when incorporating privacy and security requirements by design into the model, and assessing the trustworthiness of such learning systems.
Jeff Schwartzentruber
Dr. Jeff Schwartzentruber is a Senior Machine Learning Scientist at eSentire – a Canadian cyber-security company specializing in Managed Detection and Response. His research interests and private sector work include the development and application of machine learning models for threat detection and security analytics. As a Catalyst Fellow, Dr. Schwartzentruber will develop an AI-based method to reduce the complexity and manual effort of building a robust security operations pipeline for extracting a variety of data sources, transforming this data, and obtaining relevant security analytics.
Jeff Schwartzentruber
Dr. Jeff Schwartzentruber is a Senior Machine Learning Scientist at eSentire – a Canadian cyber-security company specializing in Managed Detection and Response. His research interests and private sector work include the development and application of machine learning models for threat detection and security analytics. As a Catalyst Fellow, Dr. Schwartzentruber will develop an AI-based method to reduce the complexity and manual effort of building a robust security operations pipeline for extracting a variety of data sources, transforming this data, and obtaining relevant security analytics.
