David Evans headshot
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David Evans

Professor
Unit: School of Engineering and Applied Science
Department: Department of Computer Science
Office location and address
85 Engineers Way
Charlottesville, Virginia 22903
supplement to SaTC CORE: Frontier: Collaborative: End-to-end Trustworthiness of Machine-Learning Systems_PSU
Source: Pennsylvania State University
October 01, 2018 – September 30, 2023
SaTC CORE: Frontier: Collaborative: End-to-end Trustworthiness of Machine-Learning Systems
Source: U.S. National Science Foundation (NSF)
October 01, 2018 – September 30, 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
Robust and Resilient Deep Learning Systems
Source: Intel Corporation
December 01, 2017 – November 30, 2021
Cross-enclave Learning using Encrypted Aggregation Techniques (CLEAT)
Source: Lockheed Martin Corporation
June 01, 2021 – November 29, 2021
SaTC: CORE: Small: Multi-Party High-dimensional Machine Learning with Privacy
Source: U.S. National Science Foundation (NSF)
September 01, 2017 – August 31, 2021
EN-CS-TWC: Small Automatic Techniques for Evaluating and Hardening Machine Leraning Classifiers in the Presence of Adversaries
Source: U.S. NSF - Directorate Computer & Info. Sciences
September 01, 2016 – August 31, 2019
EN-CS TWC: Small: Automated Security Testing for Applications Integrating Third-Party Services
Source: U.S. NSF - Directorate Computer & Info. Sciences
September 01, 2014 – August 31, 2019
TC: Large: Collaborative Research: Practical Secure Two-Party Computation: Techniques, Tools, and Applications
Source: U.S. NSF - Directorate Computer & Info. Sciences
August 15, 2011 – July 31, 2018
EN-CS EDU: Collaborative: PicoCTF 2014
Source: U.S. NSF - Directorate For Ed. & Human Resources
September 01, 2014 – August 31, 2017
EN-CS Designing for Measurable Security
Source: The Trustees of Columbia University in the City of
June 01, 2013 – May 31, 2017
EN-CS PI Meeting for Secure and Trustworthy Cyberspace
Source: U.S. NSF - Directorate Computer & Info. Sciences
May 01, 2014 – April 30, 2015
EN-CS Hardware, Languages, and Architectures for Defense Against Hostile Operating Systems
Source: University of California at Berkeley
August 01, 2009 – July 31, 2014
EN-CS CT-M: Implementable Privacy and Security for Resource-Constrained Devices
Source: U.S. NSF - Directorate Computer & Info. Sciences
September 01, 2008 – August 31, 2013
CS 1501: Special Topics in Computer Science
Credits: 1
Student led special topic courses which vary by semester.
CS 2102: Discrete Mathematics
Credits: 3
Introduces discrete mathematics and proof techniques involving first order predicate logic and induction. Application areas include finite and infinite sets, elementary combinatorial problems, and graph theory. Development of tools and mechanisms for reasoning about discrete problems. Prerequisite: CS 1110, 1111, 1112 or 1120 with a grade of C- or higher.
CS 3102: Theory of Computation
Credits: 3
Introduces computation theory including grammars, finite state machines, pushdown automata, and Turing machines. Prerequisites: CS 2102 and CS 2110 both with grades of C- or higher
CS 3501: Special Topics in Computer Science
Credits: 1–3
Content varies, depending on instructor interests and the needs of the Department. Taught strictly at the undergraduate level. Prerequisite: Instructor permission; additional specific requirements vary with topics.
PAVS 4500: Pavilion Seminar
Credits: 3
The Pavilion Seminars are open, by instructor permission, to 3rd and 4th year students. They are 3-credit, multidisciplinary seminars, focused on big topics and limited to max. 15 students each. For detailed descriptions of current offerings, see http://college.artsandsciences.virginia.edu/PAVS.
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 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.
CS 6501: Special Topics in Computer Science
Credits: 3
Course content varies by section and is selected to fill timely and special interests and needs of students. See CS 7501 for example topics. May be repeated for credit when topic varies. Prerequisite: Instructor permission.
CS 6890: Industrial Applications
Credits: 1
A graduate student returning from Curricular Practical Training can use this course to claim one credit hour of academic credit after successfully reporting, orally and in writing, a summary of the CPT experience to his/her academic advisor.
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.
CS 8897: Graduate Teaching Instruction
Credits: 1–12
For master's students who are teaching assistants.
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.
CS 9897: Graduate Teaching Instruction
Credits: 1–12
For doctoral students who are teaching assistants.
CS 9999: Dissertation
Credits: 1–12
Formal record of student commitment to doctoral research under the guidance of a faculty advisor. May be repeated as necessary.

ACM Conference on Computer and Communications Security PC Co-Chair 2017

Distinguished Research Award 2014

IEEE Technical Committee on Security and Privacy Award for Outstanding Community Service 2010

State Council of Higher Education for Virginia Outstanding Faculty Award 2009

Defense Science Study Group Fellow 2008–9

All-University Teaching Award 2008

Harold Morton Jr. Award for Teaching 2004

ACM Jefferson Undergraduate Teaching Award 2002

University Teaching Fellow 2001

National Science Foundation CAREER Award 2001