Domenic Rosati Computer Science PhD Candidate, Dalhousie University Head of Artificial Intelligence, Scite
In 2023, senior AI (Artificial Intelligence) researchers and company executives, including Nobel Prize winner Geoffrey Hinton, Yoshua Bengio and Sam Altman, signed a statement noting that “mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.” Domenic Rosati, Computer Science PhD candidate at Dalhousie University in Halifax, is an early-career researcher whose work focuses on understanding these AI safety risks, both current and potential, and to constructing and measuring future defenses against bad actors who might purposely fine-tune Large Language Models to achieve harmful goals.
As the son of tech entrepreneurs, Domenic grew up around computers, attended summer computer camp and learned to program while very young. “At the time, personal computers weren’t what they are now. With no apps to work with, I naturally picked up programming at a very early age,” he says.
As a teenager, Domenic’s enthusiasm for technology waned and he became more interested in the humanities. “I was really good at programming and already knew the material that my high school offered in computer sciences courses. I took history courses instead,” he adds.
Domenic studied history at Carleton University in his hometown of Ottawa. “For most of my course work, I employed methods using computational linguistics. That got me back into computing,” he explains.
After completing an undergraduate degree in linguistics, Domenic applied to conduct graduate work in history using these methods. After rejections from the University of Toronto and McGill University, he applied to and was accepted to the library and information science program at Dalhousie. He says, “I very quickly understood that working as a library or archivist wasn’t for me. I wanted to do deeper technical work, so I started taking masters’ level computer science courses. By the final year of my program, I was exclusively studying computer science.”
Domenic’s masters’ research was in machine learning for natural language processing, conducted at a time when deep learning was quite new and was being used primarily for computer vision tasks.
“In 2016, I had a moment where I had to choose between pursuing a PhD in computer science or continuing to work in industry,” he says. With a young family to support, he decided to move from academia to industry, where he joined a start-up company doing machine learning for video analysis for movie studios. As Director of Machine Learning and Natural Language Processing, Domenic worked for two years in both research and engineering roles.
In 2018, Domenic founded a start-up that focused on reinforcement learning. “It didn’t work out but was a really good experience,” he notes.
In 2020, Domenic joined Scite, a platform that uses deep learning, natural language processing to deliver a new type of citation index for literature discovery tasks, as one of the first employees. He says, “We were lucky to build a generative AI experience for doing research tasks, including writing, before ChatGPT.”
Domenic’s work at Scite attracted him back to his roots in computational linguistics. “The motivation to pursue my PhD studies was having industry experience with generative AI, early on before the emergence of ChatGPT, and understanding that customers could use it in really unsafe and irresponsible ways. I knew that someone needs to think, on a regulatory and ethical level, about the safety implications of using these models,” he adds.
His work as an early provider of a generative AI solution for research writing tasks led him to think about the next generation of technology, prior to its development and release. Domenic says, “I’m really concerned about the use of large language models, not as they are today, but as they start to be used to accomplish tasks autonomously, as agents in the world. That very strongly motivated me to try to resolve some of the AI safety issues.”
The main focus of Domenic’s PhD research is a very particular type of threat around the ability of large language models and other neural networks to be trained to competently conduct a wide spectrum of tasks. “Some of the tasks that you can make large language models do are very harmful. For example, autonomously hacking websites, developing security exploits, generating hate speech or misinformation campaigns,” he says.
He notes that the problem with large language model research is that some classify it as a dual use risk problem. “The better you make the technology, the easier it is to use for harmful purposes. There is a massive market incentive for commercial companies and the research community to develop more and more capable large language models. This comes at the risk of those models being able to autonomously perform harmful tasks much better. Completely autonomous agents could take a series of harmful actions.”
Safety guards are the mainstream method used for AI safety. With the use of safety guards, if a model in a commercial or research application is tasked to perform a harmful action, it will refuse and will explain why it’s harmful. The standard AI paradigm is to develop better and better safety guards that refuse more and more harmful tasks.
Domenic’s research is not about better safety guards, but how to prevent their removal through training. If safety guards can be easily removed, they don’t matter.
Domenic will continue to work on his PhD for the next several years. When considering his next career steps, he notes that his focus will be on foundational rather than applied research. That work could be conducted as a university researcher, in industry or as a technical voice to help inform government regulations to build AI for the future.
This early-career researcher’s work in machine learning, natural language generation systems and AI safety is truly pioneering and key to defending against the risks of advanced AI systems.
Health Informatics – Digital Health Research and Applications
On March 11, 2020, the World Health Organization (WHO) declared COVID-19 a pandemic, sending the world into lockdown. After just over three years, 5 million cases and over 52,000 deaths from COVID-19 confirmed in Canada, the WHO downgraded the pandemic on May 4, 2023, determining that COVID-19 is now an established and ongoing health issue that no longer constitutes a public health emergency of international concern.
As the country dealt with a record number of hospitalizations, ICU capacity crises, scarcity of PPE for healthcare workers, and ongoing lockdowns, the innovative delivery of healthcare in Canada became vital. In its report, Onward and Upwards, Digital Talent Outlook 2025, ICTC, the Information and Communications Technology Council, notes that Canada has experienced a significant increase in the adoption of digital healthcare since the advent of COVID-19. And in 2020, the federal government announced an investment of $240.5 million to accelerate the use of virtual tools and digital approaches to support Canadians to meet healthcare needs.
The Canadian Medical Association defines three classes of health technology: virtual care, analysis of large amounts of health data to support diagnoses and treatment decision-making, and the use of technology in the delivery of healthcare. Telehealth services, centralized electronic healthcare records, wearables and sensors, cloud technology, and the use of big data, machine learning, and artificial intelligence are becoming core elements of healthcare in Canada. When lockdowns necessitated virtual care sessions with physicians, visits to doctors’ offices in Ontario declined by almost 80%. Virtual care accounted for 70% of all primary care physician appointments, establishing virtual healthcare as a norm.
Information and communication technologies are key to the management of all aspects of healthcare, including patient records, laboratory and radiology information systems, physician order entry, and clinical monitoring. And an extraordinary amount of complex data is generated as the health technology sector becomes more digitized. According to the Competition Bureau of Canada, approximately 30% of all data in the world is generated by the healthcare industry. With this expansion of the use of technology and resulting data comes the need for health information users with the expertise to make the best use of the data and ensure its reliability and security.
The National Institutes of Health Informatics (NIHI), Canada’s first national organization dedicated to fostering Health Informatics innovation, research, and education, notes the need for fundamental and applied research in Health Informatics on “the definition of the content of the electronic health record, mechanisms for deriving, representing, and executing care guidelines, usable technologies for knowledge-guided order entry, effective and usable clinical decision support systems, methods for customizing interactive systems to different user-types and individuals, automated chart extraction, medical literature summarization, and hundreds of other areas.” Also required are prototypes, effective user interfaces, and an evaluation of the applications of Health Informatics to innovative delivery methods and clinical systems.
At the University of Toronto, the Institute of Health Policy, Management and Evaluation (IHPME) conducts research and offers professional graduate degree programs that focus on evidence-based research in Health Informatics. The program, which is recognized by the Vector Institute for Artificial Intelligence, offers a professional Master of Health Informatics which provides graduates with expertise in clinical information and communication technologies and prepares health informaticians to bridge the gaps between clinicians and ICT professionals.
The University of Toronto IHPME research team focuses on topics including the impacts of utilizing technology to transform healthcare delivery, the role of digital health in improving health outcomes, workflow, and process design, clinical decision support using AI and machine learning, data-driven personalized medicine, ubiquitous sensors and the design of health technologies.
At the Cumming School of Medicine at the University of Calgary, the Centre for Health Informatics (CHI) research and innovation centre was launched in 2018 to improve health and healthcare through data-driven innovation and collaborative research. Research within CHI focuses on the development of efficient and accurate handling of digital health data for personalized disease prevention and treatment and the identification of comorbidities and adverse events in electronic medical record (EMR) data. Researchers are also working to use linked data to develop a clinical decision support tool to both reduce heart failure hospital readmissions and predict readmission for heart failure patients. And CHI researchers with expertise in qualitative data analysis and natural language processing are developing methods to automate qualitative analysis of large amounts of free text data, including patient interviews.
Carleton University’s Department of Health Sciences was founded to conduct interdisciplinary research via the integration of knowledge and methods from across disciplines, including biomedicine, mathematics, and environmental and political sciences. Researchers from across fields of expertise work together on three main research themes: life course approach to health, environmental and global health, and big data. The department’s Science, Technology and Policy program, designed to meet a growing need for interdisciplinary health research, and skills in knowledge translation and data analysis, provides graduate students with the opportunity to conduct major research projects to develop solutions to critical and timely issues like health care for rural communities and the development and deployment of vaccines.
Health Informatics is one of the research focus areas of the School of Public Health Sciences at the University of Waterloo. Researchers with expertise in statistics, engineering, the social sciences, rehabilitation science, mathematics, and computer science work to develop and use information and communication technologies to support and advance individual and community health.
In the school’s Ubiquitous Health Technology Lab (UbiLab), the research team studies wearables and zero-effort sensors for remote patient monitoring, the use of IoT (Internet of Things) technology for large-scale, population-level studies and the use of big data, AI, and health data analytics to evaluate the technology. The Professional Practice Centre in Health Systems works with client partners, including major teaching hospitals, community hospitals, public health units, community-based agencies, physician groups, pharmacies, government agencies, and NGOs on real-world health information technology problems. Projects have included the design and implementation of a pharmacy nomenclature standardization program, the implementation of an information system to automate data extraction and reporting, the creation of a data migration strategy and specification for a major hospital information system, and the prototyping of medical devices and applications.
As Canada’s population ages, with those aged 85 and older being one of the fastest-growing groups, the research conducted in the school’s Aging and Innovation Research Program (AIRP) becomes more relevant. AIRP research focuses on the acceptance and adoption of innovations, including technologies for the assessment and management of risks of going missing in persons living with dementia, by older adults, their care partners, and healthcare professionals. The goal of this work is the development, application, and evaluation of strategies to advance dementia-friendly communities.
Canada Health Infoway, an independent, not-for-profit organization established and funded by the Canadian federal government, works with governments, healthcare organizations, clinicians, and patients to make healthcare more digital. The organization’s goal of ensuring that all Canadians have online access to personal health information, test results, prescriptions, and appointment booking services are central to ensuring that technology is as transformative to the country’s health system as it has been to all other aspects of daily life. Digital health initiatives include collaborative projects on virtual care, accessibility of health information, e-prescribing, standards in patient record data, privacy and security, and the adoption and use of innovative technologies.
COVID-19 highlighted issues in collecting, sharing, and using health data to help public health officials provide advice and information during public health emergencies. The rapid growth of cross-disciplinary research and innovation in health informatics and the adoption and use of digital technologies in healthcare are leading to improved access to healthcare, more accurate and timely diagnoses and treatments, and meaningful improvements in the quality of care.
Dr. Helen Chen Professor of Practice and Director Professional Practice Centre
Health care is evolving, and health informatics is at the forefront of the transformation. Health informatics combines communication, information technology, and health care and is used for vital functions that range from sharing information to personalizing medicine. With effective use, health informatics has the potential to vastly improve patient care.
Dr. Helen Chen is the Professor of Practice and the Director of the Professional Practice Centre with a cross-appointment at the School of Public Health Sciences and with a cross-appointment at the Cheriton School of Computer Science at the University of Waterloo. Dr. Chen teaches courses related to health informatics, information system design and management, health data standards, and health data analytics.
The Professional Practice Centre provides experiential learning opportunities for students of the professional graduate programs within the School of Public Health Sciences. By working with healthcare sector partners as well as professional staff and faculty from the University of Waterloo, the centre tackles challenging and important real-world problems.
“Working closely with industry is in my blood. I want to see the tangible impact of the research,” says Dr. Chen. Her education includes a BA and MS in Engineer Mechanics from Tsinghua University in Beijing and a Ph.D. in Computational Biomechanics from the University of Waterloo. It was a position sponsored by Agfa HealthCare that brought Dr. Chen to her current role at the University of Waterloo.
Dr. Chen’s research focuses on health data quality and analytics, health information system integration and interoperability, healthcare decision support, and Machine Learning and AI in Public Health, which is a perfect complement to the work she leads at the Professional Practice Centre.
In many ways, the centre acts like a consulting firm where students and faculty offer their expertise to health organizations and hospitals to solve problems. The organization can choose to hire a student directly to work on a specific issue or can hire the centre to manage the entire project. With the experience of working on a large project, combined with a professional degree, students gain an upper hand as they enter or return to industry.
“After they finish a project, students may be hired by the organization to continue the work. This experience makes them highly employable. The collaborative environment is extremely good for our students to learn. For our partners, they have an opportunity to experiment and take on problems they may not have the resources or expertise to tackle on their own at a significantly lower price than working with a large consulting firm.”
In one example, the centre worked with the Ontario Health Team to create its digital transformation roadmap.
“The Professional Practice Centre pulled in 10 students and 2 professors to work on the project. We were able to help them generate the inventory of their digital assets, identify information and technology gaps, and create the digital transformation roadmap, which has helped them move to the next stage of the project,” Chen said.
In healthcare, digital transformation is a continuous pursuit as technology and the need for quality and secure information increases. As health informatics moves into the area of advanced analytics, the need for specialized expertise will only increase. Fortunately, research and programs like the one offered by the School of Public Health Sciences and the Professional Practice Centre in Health Systems are seeing an increase in funding and demand in both the healthcare industry and the student population. These factors will play an important role as health organizations and students prepare for the future.
