Contact
Associate Professor, Faculty of Science - Mathematics & Statistical Sciences
- kashlak@ualberta.ca
Overview
About
PhD, University of Cambridge (2017)
MSc, Johns Hopkins University (2011)
BSc, McGill University (2008)
Research
Nonasymptotic Statistics, High Dimensional & Functional Data, Concentration Inequalities, Stochastic processes, Nonparametric Statistics, Mathematical Statistics
Teaching
Stat 378/502: Applied Regression Analysis
Stat 568: Design and Analysis of Experiments
Courses
MATH 497 - Reading in Mathematics
This course is designed to give credit to mature and able students for reading in areas not covered by courses, under the supervision of a staff member. A student, or group of students, wishing to use this course should find a staff member willing to supervise the proposed reading program. A detailed description of the material to be covered should be submitted to the Chair of the Department Honors Committee. (This should include a description of testing methods to be used.) The program will require the approval of both the Honors Committee, and the Chair of the Department. The students' mastery of the material of the course will be tested by a written or oral examination. This course may be taken in Fall or Winter and may be taken any number of times, subject always to the approval mentioned above. Prerequisite: Any 300-level MATH course.
STAT 413 - Computing for Data Science
Survey of contemporary languages/environments suitable for algorithms of Statistics and Data Science. Introduction to Monte Carlo methods, random number generation and numerical integration in statistical context and optimization for both smooth and constrained alternatives, tailored to specific applications in statistics and machine learning. Prerequisites: One of STAT 265 or MATH 281, or consent of the Department.
STAT 497 - Reading in Statistics
This course is designed to give credit to mature and able students for reading in areas not covered by courses, under the supervision of a staff member. A student, or group of students, wishing to use this course should find a staff member willing to supervise the proposed reading program. A detailed description of the material to be covered should be submitted to the Chair of the Department Honors Committee. (This should include a description of testing methods to be used.) The program will require the approval of both the Honors Committee, and the Chair of the Department. The students' mastery of the material of the course will be tested by a written or oral examination. This course may be taken in Fall or Winter and may be taken any number of times, subject always to the approval mentioned above. Prerequisite: Any 300-level STAT course.
STAT 571 - Probability and Measure
Measure and integration, Laws of Large Numbers, convergence of probability measures. Conditional expectation as time permits. Prerequisites: STAT 471 and STAT 512 or their equivalents.