In August 2021 CAIDA was successfully awarded the Faculty of Science Hiring Cluster Grant, resulting in the formation of a new interdisciplinary hiring cluster in the Faculty of Science, named "Artificial Intelligence Methods for Scientific Impact” (AIM-SI, pronounced “aim sci”).
Composed of AI methods researchers who have an interest in achieving scientific impact via interdisciplinary collaborations, AIM-SI aspires to help fuel artificial intelligence innovation and research excellence. The cluster currently consists of 18 existing UBC faculty members spanning Computer Science, Statistics, Math, and Earth, Ocean and Atmospheric Sciences--including UBC’s existing six Canada CIFAR AI chairs.
Over the past several years, the university has faced unprecedented demand for AI teaching and AI research collaborations across all scientific disciplines. Better meeting this demand will lead to more scientific breakthroughs across the university and produce a much larger pool of highly-qualified graduates for Vancouver’s red-hot tech sector. The Faculty of Science hiring cluster grant makes filling this demand possible: UBC will hire five new assistant professors across the Departments of Computer Science (2 faculty members), Statistics (2 faculty members) and Mathematics (1 faculty member). In spring 2022 AIM-SI hired one new assistant professor Geoff Pleiss (Statistics), and in spring 2023 AIM-SI hired Ahmet Alacaoglu (Mathematics). The remaining three hires will occur next academic year across the Departments of Computer Science (2) and Statistics (1). The new hires for the cluster will be funded as part of the President’s Academic Excellence Initiative (PAEI), which is driving the largest recruitment of faculty in UBC history.
AIM-SI strives to increase UBC's strength in AI methods beyond the "steady state" we’ve been maintaining, thereby meeting the immediate demand for teaching, supervision, and collaboration in AI at UBC, and making us more comparable to other top institutions both in Canada and worldwide. By building a strong interdisciplinary center on the base of AI methods we hope to fuel artificial intelligence innovation and research excellence in Vancouver’s AI community. These hires are a great first step in actualizing this vision.
Meet our new hire: Geoff Pleiss, Assistant Professor, Statistics
Dr. Geoff Pleiss received his Ph.D. from the Computer Science department at Cornell University in August 2020. In 2020 he began his work as a Postdoctoral Research Scientist in the Department of Statistics at the Zuckerman Institute at Columbia University, where he remained until his start date of July 1, 2023 at UBC as an Assistant Professor for the Statistics Department, and a member of both CAIDA and AIM-SI.
Dr. Geoff Pleiss’s work is broadly situated in the union of deep learning neural networks and probabilistic methods. What makes this really exciting is that these fields represent two very distinct strengths of AI-methods that are available: deep learning methods offer this predictive power and scalability that allows the algorithm to crunch through complex data sets, and probabilistic methods give us the ability to reason about our data and make decisions. Bridging these two worlds both provides the capacity for this power while still having the capability to reason. Dr. Pleiss has worked on a variety of interdisciplinary projects, from working with Quantum physicists to working with health care researchers, he’s helped to find the needle in the haystack within massive amounts of data.
The two major themes Dr. Pleiss plans to focus on throughout his research is accessibility and reliability. He believes there is a real need to make tools accessible and reliable. Whereas in the past you had to be an absolute expert to use these AI tools, AI has spread into our daily lives and with it comes a greater need for individuals without coding expertise to use these tools. Being able to move beyond just providing a code to run a model to scientific researchers outside of the coding disciplines towards giving them the ability to explore, rapidly prototype, debug, and test robustness themselves breeds creativity and revolutionizes scientific potential. This interdisciplinary drive that Dr. Pleiss has captures the spirit of AIM-SI itself and why the cluster was formed.
For Dr. Pleiss, AI methods for scientific impact is more than just developing technology that can impact one field or even two, but instead can impact the way research is done or products are developed in every field. By opening new avenues for different ways of making data-driven discoveries, essentially at a speed and scale that hasn’t been done before, this work has the potential to revolutionize research in different areas and accelerate action. With AIM-SI’s initiative to break down these barriers between departments and Dr. Pleiss’ passion to help build this new interdisciplinary cluster, we’re excited to see what he does next. Welcome to UBC Dr. Geoff Pleiss!