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Associate Professor of Mathematics
Associate Professor of Mathematics
KTH Royal Institute of Technology
KTH Royal Institute of Technology
Kathlén Kohn is an Associate Professor of Mathematics at KTH in Stockholm. Dr. Kohn's research focuses on the applications of nonlinear algebra to data science, with major contributions linking algebraic geometry to machine learning, statistics, computer vision, discrete geometry, combinatorics, and particle physics. She has received numerous distinctions, including the Wallenberg Prize (Sweden’s most prestigious award for mathematicians under 40), the 2024 SIAM SIGEST Award and the 2023 L'Oréal-UNESCO for Women in Science Prize in Sweden. Dr. Kohn has recently co-authored the book Metric Algebraic Geometry. She is a WASP Fellow and the Chair of the Working Group "Learn" at the Digital Futures institute in Stockholm.
Assistant Professor of Mathematics
Assistant Professor of Mathematics
Georgia Tech
Georgia Tech
Julia Lindberg is an Assistant Professor in the School of Mathematics at Georgia Tech. She previously held a Bing Postdoctoral Instructor position at the University of Texas at Austin and was a postdoctoral researcher in the Nonlinear Algebra group at the Max Planck Institute for Mathematics in the Sciences in Leipzig. She earned her PhD from the University of Wisconsin–Madison in 2022. Her research focuses on applied algebra and convex geometry, with applications to statistics, optimization, and power engineering. Dr. Lindberg has received multiple prestigious awards recognizing her outstanding research, including the John Nohel Award for Outstanding Thesis, the Excellence in Mathematical Research Award, and the Grainger Graduate Student Fellowship. Her work has also been supported by competitive funding from NSF and SIAM, reflecting her standing as a leading young researcher.
Professor of Mathematics
Professor of Mathematics
University of California, Los Angeles
University of California, Los Angeles
Deanna Needell is a Professor in the Department of Mathematics at UCLA, where she also holds the Dunn Family Endowed Chair in Data Theory. She serves as the Executive Director of the Institute for Digital Research and Education at UCLA and the Co-Director, Programs, for the Pacific Institute for the Mathematical Sciences. Her research focuses on randomized algorithms, computational mathematics, machine learning, and data scaience. Dr. Needell’s work has been recognized with different awards such as the Sloan Fellowship, NSF Career award, the IMA Prize and grants from the NSF and DoD. She is a Fellow of both the Society for Industrial and Applied Mathematics (SIAM, class of 2024) and the American Mathematical Society (AMS, class of 2022).
Deanna Needell is a Professor in the Department of Mathematics at UCLA, where she also holds the Dunn Family Endowed Chair in Data Theory. She serves as the Executive Director of the Institute for Digital Research and Education at UCLA and the Co-Director, Programs, for the Pacific Institute for the Mathematical Sciences. Her research focuses on randomized algorithms, computational mathematics, machine learning, and data scaience. Dr. Needell’s work has been recognized with different awards such as the Sloan Fellowship, NSF Career award, the IMA Prize and grants from the NSF and DoD. She is a Fellow of both the Society for Industrial and Applied Mathematics (SIAM, class of 2024) and the American Mathematical Society (AMS, class of 2022).
Associate Professor of Mathematics
Associate Professor of Mathematics
University of British Columbia
University of British Columbia
Elina Robeva is an Associate Professor of Mathematics at UBC. Her research lies at the intersection of mathematical statistics, machine learning, combinatorics, multilinear algebra, and applied algebraic geometry. She develops machine learning and optimization methods for inference in models that depict complex dependencies in data. Her work spans causal inference, graphical models, tensor decomposition, non-parametric density estimation, and super-resolution imaging. Dr. Robeva is a recipient of the SIAM Algebraic Geometry Early Career Prize, CAIMS/PIMS Early Career Research Award, and the André-Aisenstadt Prize. She is a fellow of the Alberta Machine Intelligence Institute and a Canada CIFAR AI Chair.
Professor of Mathematics
Professor of Mathematics
University of Texas at Austin
University of Texas at Austin
Rachel Ward is the W.A Tex Moncrief Distinguished Professor in Computational Engineering and Sciences — Data Science and Professor of Mathematics at UT Austin. From 2017 to 2018, she was a visiting research scientist at Facebook AI Research. She is recognized for her contributions to sparse approximation, stochastic optimization, and numerical linear algebra. Prior to joining UT Austin in 2011, Dr. Ward received her PhD in Computational and Applied Mathematics at Princeton in 2009 and was a Courant Instructor at the Courant Institute, NYU, from 2009 to 2011. Motivated by applications in signal and image processing, dynamical systems, and biology, her work often synthesizes tools from optimization, numerical linear algebra, dynamical systems, scientific computing, sparse approximation, random matrix theory, and machine learning. Dr. Ward's outstanding research was recognized by an Alfred P. Sloan Research Fellowship in Mathematics in 2012. She was named as a Simons Fellow in 2020, and was an invited speaker at the 2022 International Congress of Mathematicians.
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