## Luis RademacherAssociate Professor of Mathematics Office: Mailing Address: Phone: 530-754-0209 E-mail: |

Theoretical computer science. Data science. Matrix computations. Machine learning. Convex geometry.

- NSF: "AF: Small: High-dimensional geometry and probability for efficient inference"
- NSF: "AF: Small: Geometry and High-dimensional Inference" (with co-PI Mikhail Belkin)
- NSF Early CAREER award: "CAREER: Transforming data analysis via new algorithms for feature extraction"

- The centroid body: algorithms and statistical estimation for
heavy-tailed distributions.

AMS Sectional Meeting, University of Georgia, March 2016. PDF

Oberwolfach, December 2015. - The more the merrier: the blessing of dimensionality for learning
large Gaussian mixtures

Banff International Research Station. Banff, Canada, 2014. PDF - Sections of convex bodies, statistical estimation and (in)stability.

American Institute of Mathematics, Palo Alto CA, 2013: PDF - Simplicial polytopes that maximize the isotropic constant are highly
symmetric.

AMS Sectional Meeting, Akron OH, 2012: PDF - Randomized algorithms for the approximation of matrices

FoCM 2011, Learning theory workshop: PDF

IMA, High dimensional phenomena: PDF

- Aakash Prabhu (PhD)
- Haolin Chen (PhD)
- Brett Leroux (PhD)
- Chang Shu (PhD)
- Anupama Nandi (PhD, former)
- James Voss
(PhD, jointly advised with Mikhail Belkin, graduated, at Google)

- Joseph Anderson
(PhD, graduated, assistant professor at Salisbury University)

- Abhisek Kundu (MS, graduated)
- Jie Cui (MS, graduated)