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.

Next Cohort Intake

September 2023

Location

Virtual & In-Person

Program Duration

One Year

Time Commitment

Part-time

Applications

Open in January 2023

Contact

3_Fellowship-Program

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.

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.