TI

Tariq Iqbal

Assistant Professor
Unit: School of Engineering and Applied Science
Department: Department of Systems and Information Engineering
Office location and address
351 McCormick Rd
Charlottesville, Virginia 22903
Education
Post-Doc, Massachusetts Institute of Technology, 2017-2019
Ph.D., University of California San Diego, 2017
M.S., University of Texas at El Paso, 2012
B.S., Bangladesh University of Engineering and Technology, 2007
Biography

I am an Assistant Professor of Systems Engineering at the University of Virginia. I also hold an appointment in the Department of Computer Science (courtesy). My research interests lie at the intersection of artificial intelligence and robotics. I lead the Collaborative Robotics Lab (CRL) at UVA. My group is interested in building robotic systems that are capable of working alongside people in complex human environments.

Prior to joining UVA, I was a Postdoctoral Associate in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at Massachusetts Institute of Technology (MIT), where I worked with Professor Julie Shah. I received my Ph.D. in Computer Science from the University of California San Diego (UCSD).

SYS 4053: Systems Design I
Credits: 3
A design project extending throughout the fall semester. Involves the study of an actual open-ended situation, including problem formulation, data collection, analysis and interpretation, model building for the purpose of evaluating design options, model analysis, and generation of solutions. Includes an appropriate computer laboratory experience. Prerequisite: SYS 3021, 3060, and fourth-year standing in the Systems Engineering major.
SYS 4054: Systems Design II
Credits: 3
A design project extending throughout the spring semester. Involves the study of an actual open-ended situation, including problem formulation, data collection, analysis and interpretation, model building for the purpose of evaluating design options, model analysis, and generation of solutions. Includes an appropriate computer laboratory experience. Prerequisite: SYS 4053.
ECE 4502: Special Topics in Electrical and Computer Engineering
Credits: 1–4
A fourth-level undergraduate course covering a topic not normally covered in the course offerings. The topic usually reflects new developments in the electrical and computer engineering field. Offering is based on student and faculty interests.
SYS 4582: Selected Topics in Systems Engineering
Credits: 1–3
Detailed study of a selected topic determined by the current interest of faculty and students. Prerequisite: As specified for each offering.
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 or CS 2501 topic DSA2 with a grade of C- or higher, and BSCS major
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.
SYS 4995: Supervised Projects in Systems Engineering
Credits: 1–6
Independent study or project research under the guidance of a faculty member. Offered as required. Prerequisite: As specified for each offering.
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 or CS 2501 topic DSA2 with a grade of C- or higher, and BSCS major
SYS 6005: Stochastic Modeling I
Credits: 3
Covers basic stochastic processes with emphasis on model building and probabilistic reasoning. The approach is non-measure theoretic but otherwise rigorous. Topics include a review of elementary probability theory with particular attention to conditional expectations; Markov chains; optimal stopping; renewal theory and the Poisson process; martingales. Applications are considered in reliability theory, inventory theory, and queuing systems. Prerequisite: APMA 3100, 3120, or equivalent background in applied probability and statistics.
SYS 6465: Robots and Humans
Credits: 3
Interactions between robots and humans are influenced by form, function and expectations. Quantitative techniques evaluate performance of specific tasks and functions. Qualitative techniques are used to evaluate the interaction and to understand expectations and perceptions of the human side of the interaction. Students use humanoid robots to develop and evaluate interactions within a specific application context.
SYS 6995: Supervised Project Research
Credits: 1–12
Formal record of student commitment to project research under the guidance of a faculty advisor. Registration may be repeated as necessary.
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 8897: Graduate Teaching Instruction
Credits: 1–12
For master's students who are teaching assistants.
SYS 8995: Supervised Project Research
Credits: 1–12
Formal record of student commitment to project research for Master of Engineering degree under the guidance of a faculty advisor. Registration may be repeated as necessary.
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.
SYS 9997: Graduate Teaching Instruction
Credits: 1–12
For doctoral students.
SYS 9999: Dissertation
Credits: 1–12
For doctoral students.