Anwar Hithnawi will join the Department of Computer Science as assistant professor in January 2025.
Get to know Anwar Hithnawi who will join the Department of Computer Science as assistant professor in January 2025.
Hithnawi received her PhD in Computer Science from ETH Zürich in 2017.
What attracted you to your specific area of research in computer science?
I work in the area of data privacy and security, a field that intersects with almost every aspect of computer science. Every new technology has security and privacy elements, making this area naturally interdisciplinary and constantly evolving. While it’s often grounded in a beautiful mathematical foundation, as in cryptography, as you move higher up the security stack or apply these techniques in practice, you encounter increasingly interesting challenges in systems, usability, and programmability. There’s always something new to learn, which keeps the work exciting.
Beyond the technical aspects, what drives me also are the social implications of data privacy and security. As our world becomes more data-driven, the potential for data misuse and abuse is a growing concern. I’m dedicated to ensuring that the technologies we create also respect and protect individual privacy and that we develop the technical means that allow us to do so effectively. Upholding these values is what keeps me moving forward in this field.
Tell us about some of the key questions you’re looking to answer through your research in data privacy, applied cryptography, and systems, as well as the possible practical applications of your work.
My research is about building computer systems that do a much better job of protecting our data and privacy, all while maintaining the functionality and performance of our systems. One of the key areas I’m focused on is securing data not just when it’s being collected, stored, and transmitted but also while it’s being actively used. This is a challenging but crucial part of data security that’s still evolving. I’m particularly interested in making techniques that allow us to secure data while in use, like Homomorphic Encryption, Secure Multi-Party Computation, and Zero-Knowledge Proofs, more practical and accessible. These tools are powerful, but they’re not yet easy to implement or efficient enough for all situations. I’m broadly tackling two main questions in this space: How can we make these techniques applicable to more use cases, especially in resource-constrained environments, and how can we make them easier to use so they’re accessible to more people?
One specific project I’m currently working on, with potential practical applications, focuses on auditing privacy-preserving machine learning systems. These systems maintain privacy by keeping both the model and data encrypted, using secure computation techniques. As machine learning is increasingly applied in sensitive fields like health care and finance, it’s crucial to ensure these systems are both transparent and secure. Typically, transparency and security are studied separately, but they need to work together in practice. The challenge here lies in the ability to audit these systems without compromising their confidentiality. To address this, we are developing a new framework that allows for private, robust auditing of machine learning models, ensuring they are accountable while still protecting the privacy of the model and the data they’re trained on. The practical applications of this work are significant, particularly in sectors where data privacy is paramount, and could influence how we securely and responsibly use machine learning in the future.
What’s one thing you hope students who study or work with you will come away with?
Making a meaningful impact on data privacy can be challenging but incredibly rewarding. It requires time, patience, persistence, strategic thinking, and the courage to stand up for what’s right. I hope my students leave with the determination to navigate these complexities and the resilience to keep pushing forward, even when the path is difficult. On a personal level, I want them to value and uplift those they work with and to recognize that people are their most invaluable asset. And I hope they remember to have fun along the way.
What drew you to the Department of Computer Science at the University of Toronto?
What drew me to the department was its strong academic and research excellence, with faculty and students doing cutting-edge research across many areas. Having spent a significant part of my research career at technical institutions and later at a broad-based university during my postdoc, I’ve come to appreciate how important it is to work in an environment that encourages openness to unconventional research questions. Broad-based universities like U of T naturally facilitate the kind of interdisciplinary interactions that are crucial for impactful research. This is particularly important in areas like data privacy, where making a meaningful impact requires collaboration and dialogue with fields such as law, policy, and social sciences.
But it wasn’t just that—U of T checked off many personal and professional boxes for me as well. Living in a diverse and vibrant city is important to me, and Toronto offers all of that. I love the energy of big cities; they’re stimulating and full of interesting, like-minded people, as well as those with different perspectives, which I find interesting. Also, Toronto is one of the fastest-growing tech hubs, making it easier to attract talented students, many of whom I hope will stay in the area.
What are you looking forward to doing or experiencing in Toronto?
I’m looking forward to exploring Toronto and getting to know its neighbourhoods. The city’s diversity is beautifully reflected in the character of its neighbourhoods, and I got a taste of that during my visit. The food scene and cultural events are also on my radar. I’m excited to meet my new colleagues and students at U of T and be part of the collaborative environment there. And, of course, I can’t wait to experience the beauty of Canadian nature.
What do you enjoy doing outside of your work as a computer scientist?
Outside of work, I love spending time in nature. Whether hiking, swimming, or riding my bike. I’m also an avid traveller—whenever I can, I love exploring new cities and experiencing different cultures and new foods. Travelling has also been a big part of my life; in fact, Toronto will be the 11th city I’ve called home, spread across three continents!