Denis Nekipelov headshot

Denis Nekipelov

Associate Professor
Unit: College of Arts and Sciences
Department: Department of Economics
Office location and address
Monroe Hall, Room 254
248 McCormick Rd
Charlottesville, Virginia 22904
III: Small: Towards Explainable Personalization
Source: U.S. National Science Foundation (NSF)
October 01, 2020 – September 30, 2023
AS-ECON Econometric Inference and Aalgorithmic Learning in Games
Source: U.S. NSF - Directorate Computer & Info. Sciences
April 01, 2016 – March 31, 2023
DCL: SaTC: Early-Stage Interdisciplinary Collaboration: Econometrically Inferring and Using Individual Privacy Preferences
Source: U.S. National Science Foundation (NSF)
June 01, 2019 – May 31, 2022
RAISE: C-Accel Pilot - Track B2 (National Talent Ecosystem): Unpacking the Technology Career Path
Source: U.S. National Science Foundation (NSF)
September 01, 2019 – September 30, 2021
AS-ECON Toward Realistic Mechanism: Statistics, Inference and Approximation in Simple Bayes-Nash Implementation
Source: U.S. NSF - Directorate Computer & Info. Sciences
June 25, 2014 – August 31, 2016
AS-ECON Econometric Inference and Algorithmic Learning In Games
Source: Cornell University
August 01, 2014 – July 31, 2015
ECON 3720: Introduction to Econometrics
Credits: 4
Guides students in the use and interpretation of economic data, focusing on the most common issues that arise in using economic data, and the methodology for solving these problems. Prerequisite: STAT 2120, STAT 3120, APMA 3110, or APMA 3120
CS 4501: Special Topics in Computer Science
Credits: 1–3
Content varies annually, depending on instructor interests and the needs of the department. Similar to CS 5501 and CS 7501, but taught strictly at the undergraduate level. Prerequisite: Instructor permission; additional specific requirements vary with topics.
ECON 4559: New Course in Economics
Credits: 1–4
New course in the subject of economics.
ECON 4720: Econometric Methods
Credits: 3
Studies the application of statistical methods to the testing and estimation of economic relationships. Emphasizes applied econometric studies and the problems that arise when analyzing time series and cross section data by means of stochastic linear models. Prerequisite: ECON 3720 or STAT 3120 or STAT 3220 or APMA 3110 or APMA 3120; and MATH 3350 or MATH 3351 or APMA 3080.
ECON 4730: Markets, Mechanisms, and Machines
Credits: 3
This course will present a collection of topics from Economics and Computer Science that constitute the building blocks of modern user-facing electronic systems. Many examples will come from modern digital advertising platforms that have both created huge success in user reach and effectiveness for advertisers and, at the same time, have generated a trail of user privacy concerns. Prerequisites: ECON 3010 or 3110 and ECON 3720 or 4720.
CS 4980: Capstone Research
Credits: 1–3
This course is one option in the CS fourth-year thesis track. Students will seek out a faculty member as an advisor, and do an independent project with said advisor. Instructors can give the 3 credits across multiple semesters, if desired. This course is designed for students who are doing research, and want to use that research for their senior thesis. Note that this track could also be an implementation project, including a group-based project. Prerequisite: CS 2150 with a grade of C- or higher
CS 4993: Independent Study
Credits: 1–3
In-depth study of a computer science or computer engineering problem by an individual student in close consultation with departmental faculty. The study is often either a thorough analysis of an abstract computer science problem or the design, implementation, and analysis of a computer system (software or hardware). Prerequisite: Instructor permission.
CS 4998: Distinguished BA Majors Research
Credits: 3
Required for Distinguished Majors completing the Bachelor of Arts degree in the College of Arts and Sciences. An introduction to computer science research and the writing of a Distinguished Majors thesis. Prerequisites: CS 2150 with a grade of C- or higher and CS BA major status.
ECON 7710: Econometrics I
Credits: 4
Studies the concepts and basic techniques of probability theory and statistical inference. Prerequisite: Graduate standing or instructor permission.
CS 7993: Independent Study
Credits: 1–12
Detailed study of graduate course material on an independent basis under the guidance of a faculty member.
CS 7995: Supervised Project Research
Credits: 3
Formal record of student commitment to project research for the Master of Computer Science degree under the guidance of a faculty advisor.
ECON 8460: Econometrics Workshop
Credits: 3
Studies current research in econometrics. Prerequisite: Third-year status or instructor permission.
ECON 8730: Econometric Methods for Data-Rich Environments
Credits: 3
Traditional econometric inference is hard to implement in "big data" settings. This course provides a bridge between highly efficient scalable tools from Machine Learning and nonparametric econometric models. The focus will be on developing non-parametric models of large datasets, establishing uniform consistency results for the analyzed models, and bridging the computational efficiency and statistical properties of the estimators.
CS 8999: Thesis
Credits: 1–12
Formal record of student commitment to thesis research for the Master of Science degree under the guidance of a faculty advisor. May be repeated as necessary.
ECON 9999: Non-Topical Research
Credits: 1–12
For doctoral dissertation, taken under the supervision of the first reader or prospective first reader.