Calling all female identifying technology enthusiasts
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RESEARCH MENTORSHIPS BROUGHT TO YOU BY THE SCHOOL OF COMPUTING 
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As of May 5th, Please note that due to the overwhelming interest, we are opening up the mentorship program to a variety of research topics.
The NSERC CREATE Medical Informatics and the NSERC CREATE Cybersecurity programs are 2 of only 98 projects across all of Canada endorsed by the Natural Sciences & Engineering Research Council (NSERC). These 2 programs, hosted by Queen's University and depicting "the experimental spirit of the modernist vanguard", deliver profound ground breaking knowledge and experiences that exponentially advances and protects humanity.
Beginning in May 2022, summer mentorships in the areas of Medical Informatics and Cybersecurity will be offered to a a select number of undergraduates across Canada interested in learning and contributing towards these 2 exclusive areas of research. Please see the numerous research project options below. To become an Undergraduate Research Mentee, please complete our application form!
Beginning in May 2022, summer mentorships in the areas of Medical Informatics and Cybersecurity will be offered to a a select number of undergraduates across Canada interested in learning and contributing towards these 2 exclusive areas of research. Please see the numerous research project options below. To become an Undergraduate Research Mentee, please complete our application form!
nserc create
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Developed in consultation with industry & government stakeholders who are facing HQP shortages in cybersecurity, the program components are:
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PRINCIPAL INVESTIGATOR - DR. DAVID SKILLICORN
NSERC CREATE CYBERSECURITY PROGRAM
NSERC CREATE CYBERSECURITY PROGRAM
Cybersecurity Research Projects
1. Distributed Security in Vehicular Communications
Internet of Vehicles (IoV) has evolved from the traditional Vehicular Ad hoc Networks (VANETs) and is receiving a great deal of research attention from both industry and academia. The lack of real implementation of VANET around the world and its inability to attract commercial interests have paved the way for IoV. The seemingly increasing number of connected and autonomous vehicles is also responsible for stimulating the demand for IoV. Communication in VANET is mainly divided into two categories: Vehicle-to-Vehicle (V2V) and Vehicle-to-Roadside Units (V2R).
To guarantee the global and sustainable services by Intelligent Transportation System (ITS) applications, these communications have emerged into three other categories: Vehicle-to-Infrastructure (V2I) of mobile networks, Vehicle-to-Personal devices (V2P) and Vehicle-to-Sensors (V2S). These communication perceptions have paved the way for the connected vehicle technologies where a vehicle includes different communication devices and sensors to be connected with its surroundings. With the help of vehicular communications, connected vehicles can provide effective transportation services and beneficial applications such as congestion avoidance, crash prevention, dynamic information exchange, intelligent vehicle monitoring and controlling to enhance the driving experience, and provide traffic safety.
2. Driver-Centric Vehicles to Intelligent Mechanical Devices
In an era of connectivity and automation, the vehicle industry is adopting various technologies to transfer driver-centric vehicles to intelligent mechanical devices driven by software components. However, software integration and network connectivity inherit numerous security issues. Internet exposure introduces a plethora of vulnerabilities and facilitates attackers' jobs. Hackers' threats in the vehicle's domain are not limited to a breach that only exploits personal data; they can amplify the risk by altering the vehicle software systems. There are currently many reported vehicle attacks initiated against different vehicle manufacturers. Our research offers methods and tools that collaboratively enhance vehicle software security, making vehicles more resilient to cyber incidents.
3. Access Control
Different services and applications available on the internet (e.g., video conferencing, remote printing) need secure interactions and authorization requirements. Sensitive data through web and distributed protocols also highlight the need for access control to restrict unauthorized access to resources.
Attribute-Based Access Control (ABAC) is the most widely used access control model to control access to resources. It provides a high level of flexibility and enhances security and information sharing in distributed multi-entity communications. However, the effectiveness and efficiency of the ABAC model depend on the correctness and strength of authorization policies. Moreover, manual ABAC policy development for large-scale organizations is expressive and time-consuming. Furthermore, tremendous advancements of technologies in smart mobile devices, sensors, and the Internet of Things (IoT) considerably increase the mobility and adaptability of systems.
4. Machine Learning
Cybersecurity is undergoing massive technological changes in the context of computing, data science, and machine learning. Machine learning has developed software applications for computer vision, speech recognition, natural language processing, robot control, and other applications. It has a powerful capability for cybersecurity as well to enhance malware detection, recognize breaches, and identify threats and vulnerabilities.
Networks and platforms are constantly under attack. These attacks are more effective given the number of tools to scan and evaluate targets. Machine learning offers a unique opportunity to close the cyber skills gap by reducing the number of cybersecurity personnel needed to research, analyze, and share malware detection information. In comparison to traditional computing processes, data science-based cybersecurity will be more intelligent and actionable.
Internet of Vehicles (IoV) has evolved from the traditional Vehicular Ad hoc Networks (VANETs) and is receiving a great deal of research attention from both industry and academia. The lack of real implementation of VANET around the world and its inability to attract commercial interests have paved the way for IoV. The seemingly increasing number of connected and autonomous vehicles is also responsible for stimulating the demand for IoV. Communication in VANET is mainly divided into two categories: Vehicle-to-Vehicle (V2V) and Vehicle-to-Roadside Units (V2R).
To guarantee the global and sustainable services by Intelligent Transportation System (ITS) applications, these communications have emerged into three other categories: Vehicle-to-Infrastructure (V2I) of mobile networks, Vehicle-to-Personal devices (V2P) and Vehicle-to-Sensors (V2S). These communication perceptions have paved the way for the connected vehicle technologies where a vehicle includes different communication devices and sensors to be connected with its surroundings. With the help of vehicular communications, connected vehicles can provide effective transportation services and beneficial applications such as congestion avoidance, crash prevention, dynamic information exchange, intelligent vehicle monitoring and controlling to enhance the driving experience, and provide traffic safety.
2. Driver-Centric Vehicles to Intelligent Mechanical Devices
In an era of connectivity and automation, the vehicle industry is adopting various technologies to transfer driver-centric vehicles to intelligent mechanical devices driven by software components. However, software integration and network connectivity inherit numerous security issues. Internet exposure introduces a plethora of vulnerabilities and facilitates attackers' jobs. Hackers' threats in the vehicle's domain are not limited to a breach that only exploits personal data; they can amplify the risk by altering the vehicle software systems. There are currently many reported vehicle attacks initiated against different vehicle manufacturers. Our research offers methods and tools that collaboratively enhance vehicle software security, making vehicles more resilient to cyber incidents.
3. Access Control
Different services and applications available on the internet (e.g., video conferencing, remote printing) need secure interactions and authorization requirements. Sensitive data through web and distributed protocols also highlight the need for access control to restrict unauthorized access to resources.
Attribute-Based Access Control (ABAC) is the most widely used access control model to control access to resources. It provides a high level of flexibility and enhances security and information sharing in distributed multi-entity communications. However, the effectiveness and efficiency of the ABAC model depend on the correctness and strength of authorization policies. Moreover, manual ABAC policy development for large-scale organizations is expressive and time-consuming. Furthermore, tremendous advancements of technologies in smart mobile devices, sensors, and the Internet of Things (IoT) considerably increase the mobility and adaptability of systems.
4. Machine Learning
Cybersecurity is undergoing massive technological changes in the context of computing, data science, and machine learning. Machine learning has developed software applications for computer vision, speech recognition, natural language processing, robot control, and other applications. It has a powerful capability for cybersecurity as well to enhance malware detection, recognize breaches, and identify threats and vulnerabilities.
Networks and platforms are constantly under attack. These attacks are more effective given the number of tools to scan and evaluate targets. Machine learning offers a unique opportunity to close the cyber skills gap by reducing the number of cybersecurity personnel needed to research, analyze, and share malware detection information. In comparison to traditional computing processes, data science-based cybersecurity will be more intelligent and actionable.
nserc create mEDICAL iNFORMATICS
Integration, Federation and Retrieval of Large-Scale Data Repositories in Canada
We collaborate with the Canadian Institute of Health Information (CIHI) and the Ontario Health Data Platform (OHDP) to tackle novel challenges in data management and devise evaluation frameworks that center on security, performance and fairness.
NEXT GENERATION OF ACTIONABLE PRESCRIPTIVE ANALYSIS USING MULTI-RESOLUTION, MULTI-MODALITY DATA
We build computation models of disease from multi-omics data using machine learning, deep learning and evolutionary algorithms, focusing on innovations that address the unique nature of health data and the unavailability and vagueness of gold-standard labels (e.g., pathology labels).
DEMOCRATIZATION OF AI, SOFTWARE AND DATA FOR HEALTHCARE
We're international leaders in developing and disseminating open source software using low-cost point-of-care imaging. Our positive impact on the global computer–assisted medical interventions community has is constantly expanding. We'll meet new challenges for discovery, refinement of methods and innovative AI-powered solutions using large open source data, hence democratizing access to care and positive outcomes of AI.
We collaborate with the Canadian Institute of Health Information (CIHI) and the Ontario Health Data Platform (OHDP) to tackle novel challenges in data management and devise evaluation frameworks that center on security, performance and fairness.
NEXT GENERATION OF ACTIONABLE PRESCRIPTIVE ANALYSIS USING MULTI-RESOLUTION, MULTI-MODALITY DATA
We build computation models of disease from multi-omics data using machine learning, deep learning and evolutionary algorithms, focusing on innovations that address the unique nature of health data and the unavailability and vagueness of gold-standard labels (e.g., pathology labels).
DEMOCRATIZATION OF AI, SOFTWARE AND DATA FOR HEALTHCARE
We're international leaders in developing and disseminating open source software using low-cost point-of-care imaging. Our positive impact on the global computer–assisted medical interventions community has is constantly expanding. We'll meet new challenges for discovery, refinement of methods and innovative AI-powered solutions using large open source data, hence democratizing access to care and positive outcomes of AI.
PRINCIPAL INVESTIGATOR - DR. PARVIN MOUSAVI
NSERC CREATE MEDICAL INFORMATICS
NSERC CREATE MEDICAL INFORMATICS
Medical Informatics Research Projects
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Digital health is transforming the way Canadians access health care, altering clinical workflows while providing unique opportunities for computing sciences to revolutionize health and operational decision making. The unprecedented impact of the COVID-19 pandemic has made clear the critical need to understand the significance of data and its interpretation for decision making.
We are hiring undergraduate students to contribute to projects that are built around decision making in medical informatics. Projects focus on: i) data acquisition, storage, preprocessing and visualization at the point of care; ii) data integration and integration from multiple medical modalities; and iii) data interpretation, predictive and prescriptive analysis. AI and informatics will form the basis for training of students in these projects. While these approaches have great promise in rapid analysis of next-generation large scale data, specialized training will also be provided in working with health data. Students will learn state of the art in computing and informatics, and develop a depth and breadth of understanding of the health data and a flexibility in approach that allows them to stay current in such a rapidly changing setting. Students will work in a multidisciplinary team of engineers, computer scientists, clinicians and clinical researchers. Several full time positions are available for the summer from May 2 to August 24. Funding is $5,000 + benefits. 
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If you have questions regarding the 2022 Research Mentorships for the CREATE Medical Informatics or CREATE Cybersecurity Programs, please contact us at cyber-info@cs.queensu.ca.
For detailed information on Queen's University NSERC CREATE Cybersecurity program, please visit cyber.cs.queensu.ca or https://medicreate.cs.queensu.ca for information on the NSERC Medical Informatics program.
For detailed information on Queen's University NSERC CREATE Cybersecurity program, please visit cyber.cs.queensu.ca or https://medicreate.cs.queensu.ca for information on the NSERC Medical Informatics program.
