About Me

Publications

Invited Talks

Teaching

About Me

My name is Nikola B. Kovachki and I am a fourth year graduate student at Caltech studying Applied and Computational Mathematics (ACM) under the advisership of Professor Andrew M. Stuart. I was born in 1993 in Sofia, Bulgaria but relocated to the United States in March of 2005. I went to middle and high school in Duluth, Georgia and later obtained a B.Sc. in Mathematics from Caltech in 2016.

My research interests lie at the intersection of learning theory and inverse problems. I am keen on the development of the mathematical theory of learning and its implications for advancement of numerical algorithms. Further I am interested in the application of existing learning systems to physical problems arising in the sciences.

I love spending time with my beautiful wife and dog, traveling, hiking, and experiencing art.

Published

Kovachki N.B., Stuart A.M.; Ensemble Kalman Inversion: A Derivative-Free Technique For Machine Learning Tasks. Inverse Problems, Vol. 35, Number 9, (2019).

Cheng L., Kovachki N.B., Welborn M., and Miller T.F. III; Regression-clustering for improved accuracy and training cost with molecular-orbital-based machine learning. J. Chem. Theory Comput., Vol. 15, Number 6668, (2019).

Submitted

Kovachki N.B., Stuart A.M.; Continuous Time Analysis of Momentum Methods. 2019.

Submitted to: JMLR

In Preparation

Bhattacharya K., Kovachki N.B., Stuart A.M.; Model Reduction for Input-Output Maps. 2019

Baptista R., Hosseini B., Kovachki N.B., Youssef M.; Learning with Triangular Maps. 2019.

Azizzadenesheli K., Bhattacharya K., Kovachki N.B., Li Z., Liu B., Stuart A.M.; Graph networks for PDE(s). 2019.

Upcoming

SIAM Conference on Imaging Science (IS20). July 6-9th 2020. Toronto, Ontario, Canada.

SIAM Conference on Mathematics of Data Science (MDS20). May 5-8th 2020. Cincinnati, Ohio, USA.

Uncertainty quantification, stochastic modeling and machine learning for materials (Mach Conference). April 1-3rd 2020. Annapolis, Maryland, USA.

SIAM Conference on Uncertainty Quantification (UQ20). March 24-27th 2020. Munich, Germany.

Given

Center for Materials in Extreme Dynamic Environments Fall Meeting (MEDE-ARL). Model Reduction for Input-Output Maps. Talk. October 10th 2019. Baltimore, Maryland, USA.

International Congress on Industrial and Applied Mathematics (ICIAM). Model Reduction for Input-Output Maps. Talk. July 15-19th 2019. Valencia, Spain.

Applied Inverse Problems (AIP). EKI: A Derivative-Free Method for Machine Learning Tasks; Analysis of Momentum Methods. Talk(s). July 8th-12th 2019. Grenoble, France.

Workshop on Inverse Problems and Machine Learning (IPML). Analysis of Momentum Methods. Talk. May 27th-29th 2019. Montreal, Quebec, Canada.

SIAM Conference on Applications of Dynamical Systems (DS19). Analysis of Momentum Methods. Talk. May 19th-23rd 2019. Snowbird, Utah, USA.

SIAM Conference on Computational Science and Engineering (CSE19). EKI: A Derivative-Free Method for Machine Learning Tasks. Talk. February 25th - March 1st 2019. Spokane, Washington, USA.

Center for Materials in Extreme Dynamic Environments Fall Meeting (MEDE-ARL). Model Reduction for Input-Output Maps. Talk. October 10th 2018. Baltimore, Maryland, USA.

Southern California Applied Mathematics Symposium (SOCAMS). Derivative-Free Ensemble Methods for Machine Learning Tasks. Poster. April 28th 2018. Santa Barbara, California, USA.

UQ for Inverse Problems in Complex Systems (UNQW04). Derivative-Free Ensemble Methods for Machine Learning Tasks. Poster. April 9th-13th 2018. Cambridge, UK.

Workshop on Inverse Problems and Machine Learning (IPML). Derivative-Free Ensemble Methods for Machine Learning Tasks. Talk. February 9th-11th 2018. Pasadena, California, USA.

Teaching Assistantships

Linear Analysis with Applications (CMS/ACM/IDS 107). Computing and Mathematical Sciences/ Applied and Computational Mathematics/ Information and Data Sciences. Fall 2019. California Institute of Technology.

Instructor: Andrew M. Stuart

Linear Analysis with Applications (CMS/ACM/IDS 107). Computing and Mathematical Sciences/ Applied and Computational Mathematics/ Information and Data Sciences. Fall 2018. California Institute of Technology.

Instructor: Andrew M. Stuart

Linear Analysis with Applications (CMS/ACM 107). Computing and Mathematical Sciences/ Applied and Computational Mathematics. Fall 2017. California Institute of Technology.

Instructor: Andrew M. Stuart

Introduction to Probability Models (ACM/EE 116). Applied and Computational Mathematics/Electrical Engineering. Fall 2016. California Institute of Technology.

Instructor: Konstantin Zuev

Technical Seminar Presentations (E 10). Engineering. Fall 2016. California Institute of Technology. Instructor: Anthony Fender

Technical Seminar Presentations (E 10). Engineering. Spring 2016. California Institute of Technology.

Instructor: Anthony Fender

Nikola B. Kovachki