{"id":19567,"date":"2026-09-03T09:42:24","date_gmt":"2026-09-03T13:42:24","guid":{"rendered":"https:\/\/web.uri.edu\/artsci\/?p=19567"},"modified":"2026-09-03T09:42:25","modified_gmt":"2026-09-03T13:42:25","slug":"ruyu-zhou","status":"publish","type":"post","link":"https:\/\/web.uri.edu\/artsci\/news\/ruyu-zhou\/","title":{"rendered":"Ruyu Zhou"},"content":{"rendered":"\n

What brought you to URI?
<\/strong>I was drawn to URI for the opportunity to build an independent research program within a collaborative, fast-growing department and to be part of a university expanding its research and interdisciplinary initiatives.I was also excited by the strong connections across computer science, statistics, and data science, as well as the many opportunities to collaborate across URI in areas such as pharmacy, health and medical research, and marine science. URI\u2019s breadth of expertise is a great match for the interdisciplinary nature of my research.<\/p>\n\n\n\n

How did you become interested in your field?<\/strong>
I actually started out in mathematics and, for a long time, thought I would stay in pure math. I really enjoyed the rigor and problem-solving side of mathematics, but over time, I became more interested in using those ideas to understand real-world data and problems. That led me to statistics, where I had the opportunity to work on a range of problems, especially those motivated by health and biomedical applications. Working with real-world data got me thinking about challenges that go beyond simply building a model or improving its accuracy \u2014 how to use sensitive data responsibly, what happens when data are incomplete or imperfect, and how much we can trust the results in practice. Those questions gradually shaped my interests in machine learning and eventually led to my current research on privacy, security, and robustness.<\/p>\n\n\n\n

What are you most excited about in your new role?
<\/strong>I’m most excited about having the opportunity to build my own research program and work closely with great students at URI as they develop their own interests and ideas. Starting a faculty position also gives me the freedom to explore new research directions and pursue questions I’ve been wanting to work on for a long time. I’m especially looking forward to mentoring students, building new collaborations, and seeing where those ideas take us.<\/p>\n\n\n\n

What are you currently researching?<\/strong>
My research is broadly at the intersection of statistics and machine learning. A major focus of my work is trustworthy machine learning, particularly data privacy, where I develop methods that allow us to learn from sensitive data while providing rigorous privacy guarantees. I\u2019m also interested in how ideas from statistics and mathematics can help us build better machine learning or AI methods, and vice versa. For example, some of my recent work looks at using generative models to handle missing data and using optimal transport in computer vision problems. I also collaborate extensively on cross-disciplinary research, particularly in epidemiological and biomedical applications.<\/p>\n\n\n\n

Is there a particular project you’re especially excited about right now?
<\/strong>One project I’m especially excited about looks at how privacy guarantees relate to robustness against data poisoning. Privacy limits how much the output of a learning algorithm can change when a single training record is modified, so it might seem natural to expect stronger privacy to also mean greater resistance to poisoning attacks. But we’re finding that this isn’t enough: two methods can have exactly the same record-level privacy guarantees and still respond very differently when an attacker changes multiple training records. Our work tries to understand what information is missing from the privacy guarantee, why these differences arise, and what we can still say about the worst-case effect of poisoning based on privacy alone.<\/p>\n\n\n\n

What do you enjoy most about teaching?
<\/strong>What I enjoy most is seeing the moment when something really clicks for a student. I like helping students move beyond memorizing formulas or following a set of steps to understand the ideas behind a method and why it works. It\u2019s especially rewarding when they start making connections on their own, asking questions I hadn\u2019t expected, or applying what they\u2019ve learned to a new problem. Those moments make teaching both fun and rewarding for me.<\/p>\n\n\n\n

Are there faculty or departments you’d especially like to collaborate with?<\/strong>
Although I’m on the Statistics track with a focus on Data Science, my research naturally overlaps with several areas in Computer Science, especially cybersecurity. I’m excited about the chance to collaborate with researchers in URI’s cybersecurity community on privacy, security, and trustworthy machine learning. Beyond the department, I’m particularly interested in collaborations in pharmacy, biomedical, and engineering. I’m also curious to explore areas that are newer to me at URI, like marine and environmental sciences. I’m looking forward to seeing what kinds of new research questions come out of those conversations.<\/p>\n\n\n\n

How can students best approach you if they’re interested in your research?<\/strong>
Email is always the best way to reach me. Students are welcome to introduce themselves and tell me a little about their background and interests. They don’t need to have a specific research idea in mind \u2014 I’m always happy to chat with students who are curious about my work and interested in getting involved.<\/p>\n\n\n\n

What do you enjoy doing outside of academia?<\/strong>
Hip-hop dance has been a big part of my life. I actually spent my whole gap year dancing full-time, and I still love dancing whenever I have the chance. I also enjoy traveling and, of course, spending time with my beautiful cat, Biubiu.<\/p>\n","protected":false},"excerpt":{"rendered":"

New faculty, Computer Science and Statistics\/Data Science<\/p>\n","protected":false},"author":5153,"featured_media":19568,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[7],"tags":[],"class_list":["post-19567","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"acf":[],"_links":{"self":[{"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/posts\/19567","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/users\/5153"}],"replies":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/comments?post=19567"}],"version-history":[{"count":1,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/posts\/19567\/revisions"}],"predecessor-version":[{"id":19569,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/posts\/19567\/revisions\/19569"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/media\/19568"}],"wp:attachment":[{"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/media?parent=19567"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/categories?post=19567"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/tags?post=19567"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}