Thomas Lord Department of Computer Science

Return to: USC Viterbi School of Engineering  

Henry Salvatori Computer Science Center 104
(213) 740-4494
FAX: (213) 740-7285
Email: csdept@usc.edu
 

Chair: Nenad Medvidović, PhD

Faculty

Chan Soon-Shiong Chair: Maja Matarić, PhD (Neuroscience Center)

Andrew and Erna Viterbi Early Career Chair: Jernej Barbic, PhD

Philip and Cayley MacDonald Endowed Early Career Chair: Yan Liu, PhD

Gordon S. Marshall Chair in Engineering: Urbashi Mitra, PhD

Jack Munishian Early Career Chair; Zohrab A. Kaprielian Fellow in Engineering: Fei Sha, PhD

Niki and Max Nikias Chair in Engineering: Shrikanth (Shri) Narayanan, PhD

Northrup Grumman Chair in Engineering: Ramesh Govindan, PhD

Fletcher Jones Foundation Endowed Chair in Computer Science: Gaurav Sukhatme, PhD

David Packard Chair in Manufacturing Engineering: Stephen C-Y Lu, PhD (Mechanical Engineering, Industrial and Systems Engineering)

Charles Lee Powell Chair in Engineering: Viktor Prasanna, PhD (Electrical and Computer Engineering)

Henry Salvatori Chair in Computer Science: Leonard M. Adleman, PhD

Fletcher Jones Professor: Ramakant Nevatia, PhD

Helen N. & Emmett H. Jones Professorship in Engineering: Cyrus Shahabi, PhD (Electrical and Computer Engineering and Spatial Sciences)

Seeley G. Mudd Professor of Engineering: Shanghua Teng, PhD

WiSE Gabilan Assistant Professor: Heather Culbertson, PhD

Professors: Leonard Adleman, PhD (Molecular Biology); Jernej Barbic, PhD; Leana Golubchik, PhD (Electrical and Computer Engineering); Ramesh Govindan, PhD; Ellis Horowitz, PhD (Electrical and Computer Engineering); Ming-Deh Huang, PhD; Laurent Itti, PhD (Neuroscience Center); David Kempe, PhD; Sven Koenig, PhD; Yan Liu, PhD; Maja Matarić, PhD (Neuroscience Center); Nenad Medvidovic, PhD; Aiichiro Nakano, PhD (Biomedical Engineering, Materials Science, Physics); Ulrich Neumann, PhD (Electrical and Computer Engineering); Ramakant Nevatia, PhD (Electrical and Computer Engineering); Cyrus Shahabi, PhD (Electrical and Computer Engineering); Gaurav Sukhatme, PhD (Electrical and Computer Engineering); Shanghua Teng, PhD

Associate Professors: Bistra Dilkina, PhD; Shaddin Dughmi, PhD; Shahram Ghandeharizadeh, PhD; William GJ Halfond, PhD; Chao Wang, PhD

Assistant Professors: Heather Culbertson, PhD; Jyotirmony Vinay Deshmukh, PhD; Robin Jia, PhD; Aleksandra Korolova, PhD; Joseph Lim, PhD; Haipeng Luo, PhD; Muhammad Naveed, PhD; Stefanos Nikolaidis, PhD; Barath Raghavan, PhD; Mukund Raghothaman, PhD; Xiang Ren, PhD; Vatsal Sharan, PhD; Swabha Swayamdipta, PhD; Jesse Thomason, PhD; Dani Yogatama, PhD; Jiapeng Zhang, PhD

Joint Professors: Murali Annavaram, PhD (Electrical and Computer Engineering); Salman Avestimehr, PhD (Electrical and Computer Engineering); Irving Biederman, PhD (Psychology, Neuroscience); Todd Brun (Electrical and Computer Engineering, Physics and Astronomy); Emilio Ferrara, PhD (Annenberg); Satyandra K Gupta, PhD (Aerospace and Mechanical Engineering); Rahul Jain, PhD (Electrical and Computer Engineering); Rajiv Kalia, PhD (Physics); Carl Kesselman, PhD (Industrial and Systems Engineering); Bhaskar Krishnamachari, PhD (Electrical and Computer Engineering); C-C Jay Kuo, PhD (Signal and Image Processing); Stephen Lu, PhD (Industrial and Systems Engineering); Urbashi Mitra, PhD (Electrical and Computer Engineering); Shrikanth (Shri) Narayanan, PhD (Electrical and Computer Engineering); Hamid Nazerzadeh, PhD (Data Sciences and Operations); Andrew Nealen, PhD (Cinematic Arts); Pierluigi Nuzzo, PhD (Electrical and Computer Engineering); Viktor Prasanna, PhD (Electrical and Computer Engineering); Konstantinos Psounis, PhD; C.S. Raghavendra, PhD (Electrical and Computer Engineering); Meisam Razaviyayn (Industrial and Systems Engineering, Computer Science, and Electrical and Computer Engineering); Benjamin Reichardt, PhD (Electrical and Computer Engineering); Remo Rohs, PhD (Computational Biology); Nicolas Schweighofer, PhD (Biokinesiology and Physical Therapy); Neil Siegel, PhD (Industrial and Systems Engineering); Mahdi Soltanolkotabi, PhD (Electrical and Computer Engineering); Tianshu Sun, PhD (Data Sciences and Operations); Francisco Valero-Cuevas, PhD (Biomedical Engineering); Priya Vashishta, PhD (Chemical Engineering and Materials Science, Physics); Phebe Vayanos, PhD (Industrial and System Engineering); Richard Weinberg, PhD (Cinematic Arts); John Wilson, PhD (Spatial Sciences, Computer Science)

Adjunct Professor: Fei Sha, PhD

Adjunct Assistant Professor: Marco Papa, PhD

Research Professor of Computer Science with Distinction: Premkumar Natarajan, PhD

Research Professors: Ewa Deelman, PhD; Aram Galstyan, PhD; Yolanda Gil, PhD; Jonathan Gratch, PhD; John Heidemann, PhD; Randall Hill, PhD; Craig Knoblock, PhD; Kristina Lerman, PhD; William Swartout, PhD; David Traum, PhD

Research Associate Professors: Jose Luis Ambite, PhD; Kallirroi Georgila, PhD; Andrew Gordon, PhD; Jelena Mirkovic, PhD; Pedro Szekely, PhD; Gregory Ver Steeg, PhD

Research Assistant Professors: Muhao Chen, PhD; Gale Lucas, PhD; Xuezhe Ma, PhD; Jonathan May, PhD; Fred Morstatter, PhD; Jay Pujara, PhD; David Pynadath, PhD; Srivatsan Ravi, PhD; Mohammad Rostami, PhD; Mohammad Soleymani, PhD; Satish Kumar Thittamaranahalli PhD; Ning Wang, PhD

Adjunct Research Professor: Christian Mattmann, PhD

Adjunct Research Assistant Professors: Rafael Ferreira da Silva, PhD; Iacopo Masi, PhD; Nanyun Peng, PhD

Professors of Engineering Practice: Victor Adamchik, PhD; Jeffrey Miller, PhD; Mark William Redekopp, PhD (Electrical and Computer Engineering)

Associate Professors of Engineering Practice: Clifford Neuman, PhD; Saty Raghavachary, PhD; Wei-Min Shen, PhD; Wensheng Wu, PhD

Lecturers: Claire Bono (Senior Lecturer); William Cheng, PhD (Senior Lecturer); Aaron Cote, PhD (Senior Lecturer); Scott Easley, BA (Senior Lecturer); Andrew Goodney, PhD (Senior Lecturer); Mohammad Reza Rajati (Lecturer); Tatyana Ryutov, PhD (Senior Lecturer); Shawn Shamsian, PhD (Senior Lecturer)

Emeritus Professors: Michael A. Arbib, PhD (Biological Sciences, Biomedical Engineering, Electrical Engineering, Neuroscience and Psychology); George Bekey, PhD (Electrical Engineering, Biomedical Engineering); Jerry Hobbs, PhD; Gerard Medioni, PhD (Electrical and Computer Engineering); Aristides A.G. Requicha, PhD (Electrical Engineering); Michael S. Waterman, PhD (Biological Sciences, Mathematics)

Bachelor of Science

Undergraduate Program Educational Objectives

Graduates of the undergraduate program in Computer Science are expected to attain the following objectives within a few years of graduation:

1. Graduates apply the computational and analytical approaches of computer science to their chosen professions.
2. Graduates successfully engage in life-long learning to continue to be contributing members of their communities in fields within and outside the traditional scope of computer science.
3. Graduates exhibit high professional and ethical standards to become productive leaders in society.

Graduates of the Computer Engineering and Computer Science program are expected to attain the following educational objectives within a few years of graduation:

1. Graduates will apply analytical and critical thinking principles of both computer engineering and computer science to their chosen professions.
2. Graduates will successfully engage in life-long learning to continue to be contributing members of their communities in fields within and outside the traditional scope of computer engineering.
3. Graduates will exhibit high professional and ethical standards to become productive leaders in society.

Undergraduate Program Criteria

The program leading to a Bachelor of Science in Computer Science includes at least one and one-third years of computer science that covers the fundamentals of algorithms, data structures, software design, concepts of programming languages and computer organization and software; provides an exposure to a variety of programming languages and systems, including at least one higher-level language; and includes advanced course work that builds on the fundamental course work to provide depth.

The program includes at least one year of science and mathematics, including at least one-half year of mathematics, including discrete mathematics. Additional mathematics might consist of calculus, linear algebra, numerical methods, probability, statistics, number theory, geometry, or symbolic logic. The science component develops an understanding of the scientific method and provides an opportunity to experience this mode of inquiry in courses for science or engineering majors that provide some exposure to laboratory work.

The program leading to a Bachelor of Science in Computer Engineering and Computer Science provides both breadth and depth across the range of engineering topics implied by the title. The curriculum includes probability and statistics, including appropriate applications; mathematics, including discrete mathematics through differential and integral calculus; sciences (defined as biological, chemical or physical science) to develop an understanding of the scientific method and provide students with an opportunity to experience this mode of inquiry in courses for science or engineering majors that provide some exposure to lab work; and engineering topics (including computing science) necessary to analyze and design complex electrical and electronic devices, software and systems containing hardware and software components.

The computer science portion of the curriculum covers the fundamentals of algorithms, data structures, software design, concepts of programming languages and computer organization and software; provides an exposure to a variety of programming languages and systems, including at least one higher-level language; and includes advanced course work that builds on the fundamental course work to provide depth.

Physics/Computer Science Major Requirements for the Bachelor of Science

This program is intended for students with dual interests in physics and computer science who wish to complete the essential courses for both majors within their normal four-year career. See the Physics and Astronomy  Department section for course requirements.

Graduate Degrees

The requirements listed below are special to this department and must be read in conjunction with the general requirements  of the USC Viterbi School of Engineering for master’s degrees and the general requirements  of the USC Graduate School for PhD degrees. The graduate program in computer science provides intensive preparation in the basic concepts and techniques related to the design, programming and application of digital computers. Both the Master of Science and Doctor of Philosophy degrees are offered.

A Master of Science degree with specialization in software engineering is also offered. The program seeks to prepare students for an industrial leadership career in software engineering. It also serves as an introduction to this area for students who wish to pursue advanced studies and research leading to a PhD.

A Master of Science degree with specialization in intelligent robotics is also offered. This program seeks to prepare students for an industrial career in the development of computer systems for CAD/CAM (Computer-Aided Design and Manufacturing) and robotics. It also serves as an introduction to this area for students who wish to pursue advanced studies and research leading to a PhD. The emphasis is on the domain of mechanical, electromechanical and mechatronic products. (CAD for digital systems is covered by a separate program offered by the Electrical and Computer Engineering department.)

A Master of Science degree with a specialization in computer networks is offered. This specialization prepares students in the areas of computer communications, networks and distributed processing.

A Master of Science in Computer Science (Artificial Intelligence) is also offered.

A Master of Science in Computer Science (Multimedia and Creative Technologies) is also offered.

A Master of Science in Computer Science (High Performance Computing and Simulations) is also offered.

A Master of Science in Computer Science (Data Science) is also offered.

A Master of Science in Computer Science (Game Development) is also offered.

A Master of Science in Computer Science (Computer Security) is also offered.

A Master of Science in Computer Science Dual Degree with Tsinghua University School of Information Science and Technology – China is also offered.

A Master of Science in Computer Science (Scientists and Engineers) is also offered for students with limited background in computer science.

Admission and Prerequisites

Admission is determined by the Office of Admission and the Viterbi School of Engineering, in consultation with the Thomas Lord Department of Computer Science. The applicant is required to have a bachelor’s degree or its equivalent from an accredited college or university; satisfactory scores on the verbal and quantitative portions of the aptitude test of the Graduate Record Examinations (one advanced test from computer science, mathematics or engineering is recommended); and a substantial background in computing constitutes a minimum requirement. Foreign students must earn a satisfactory score on the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS).

Programs

• Computer Engineering and Computer Science (BS)
• Computer Science (BS)
• Computer Science Games (BS)
• Computer Science/Business Administration (BS)

• Computer Science Minor

• Computer Science Dual Degree with Tsinghua University School of Information Science and Technology (MS)

• Computer Science (Artificial Intelligence) (MS)
• Computer Science (Data Science) (MS)
• Computer Science (Game Development) (MS)
• Computer Science (MS)
• Computer Science (Scientists and Engineers) (MS)

• Software Architecture Graduate Certificate

• Computer Science (PhD)

Courses

• CSCI 100xg Explorations in Computing
• CSCI 101L Fundamentals of Computer Programming
• CSCI 102L Fundamentals of Computation
• CSCI 103L Introduction to Programming
• CSCI 104L Data Structures and Object Oriented Design
• CSCI 109 Introduction to Computer Science
• CSCI 170 Discrete Methods in Computer Science
• CSCI 201L Principles of Software Development
• CSCI 270 Introduction to Algorithms and Theory of Computing
• CSCI 281 Pipelines for Games and Interactives
• CSCI 310 Software Engineering
• CSCI 350 Introduction to Operating Systems
• CSCI 352L Computer Organization and Architecture
• CSCI 353 Introduction to Internetworking
• CSCI 356 Introduction to Computer Systems
• CSCI 360 Introduction to Artificial Intelligence
• CSCI 368 Cross-Platform App Development
• CSCI 380 Video Game Programming
• CSCI 390 Special Problems
• CSCI 401 Capstone: Design and Construction of Large Software Systems
• CSCI 402 Operating Systems
• CSCI 404 Capstone: Creating Your High-Tech Startup
• CSCI 410x Translation of Programming Languages
• CSCI 420 Computer Graphics
• CSCI 423 Native Console Multiplayer Game Development
• CSCI 426 Game Prototyping
• CSCI 430 Introduction to Computer and Network Security
• CSCI 431 Introduction to Functional Programming
• CSCI 435 Professional C++
• CSCI 439 Compiler Development
• CSCI 444 Natural Language Processing
• CSCI 445L Introduction to Robotics
• CSCI 450 Introduction to Computer Networks
• CSCI 452 Parallel and Distributed Computation
• CSCI 454L Introduction to System-on-Chip
• CSCI 455x Introduction to Programming Systems Design
• CSCI 457 Computer Systems Organization
• CSCI 458 Numerical Methods
• CSCI 459 Computer Systems and Applications Modeling Fundamentals
• CSCI 461 Artificial Intelligence for Sustainable Development
• CSCI 467 Introduction to Machine Learning
• CSCI 475 Theory of Computation
• CSCI 476 Cryptography: Secure Communication and Computation
• CSCI 477 Concepts of Programming Languages
• CSCI 485 File and Database Management
• CSCI 487 Programming Game Engines
• CSCI 490x Directed Research
• CSCI 491aL Final Game Project
• CSCI 491bL Final Game Project
• CSCI 495 Senior Project
• CSCI 499 Special Topics
• CSCI 501 Numerical Analysis and Computation
• CSCI 502a Numerical Analysis
• CSCI 502b Numerical Analysis
• CSCI 504a Numerical Solutions of Ordinary and Partial Differential Equations
• CSCI 504b Numerical Solutions of Ordinary and Partial Differential Equations
• CSCI 505a Applied Probability
• CSCI 505b Applied Probability
• CSCI 510 Software Management and Economics
• CSCI 511 Personal Software Process (PSP) and Project
• CSCI 512 Testing and Analysis of Software Systems
• CSCI 513 Autonomous Cyber-Physical Systems
• CSCI 517 Research Methods and Analysis for User Studies
• CSCI 520 Computer Animation and Simulation
• CSCI 521 Optimization Theory and Algorithms: Numerical Optimization
• CSCI 522 Game Engine Development
• CSCI 523L Networked Games
• CSCI 524 Networked Artificial Intelligence
• CSCI 526 Advanced Mobile Devices and Game Consoles
• CSCI 527 Applied Machine Learning for Games
• CSCI 529a Advanced Game Projects
• CSCI 529b Advanced Game Projects
• CSCI 530 Security Systems
• CSCI 531 Applied Cryptography
• CSCI 532 Innovation for Defense Applications
• CSCI 533 Algebraic Combinatorics
• CSCI 534 Affective Computing
• CSCI 535 Multimodal Probabilistic Learning of Human Communication
• CSCI 536 Linear Programming and Extensions
• CSCI 538 Augmented, Virtual and Mixed Reality
• CSCI 540 Self-Organization
• CSCI 542 Neural Computation with Artificial Neural Networks
• CSCI 544 Applied Natural Language Processing
• CSCI 545 Robotics
• CSCI 547 Robot Dynamics and Control
• CSCI 548 Information Integration on the Web
• CSCI 549 Nanorobotics
• CSCI 550 Advanced Data Stores
• CSCI 551 Computer Networking
• CSCI 553 Computational Solution of Optimization Problems
• CSCI 554 Cyber-Physical Systems: A Computing Perspective
• CSCI 555L Advanced Operating Systems
• CSCI 556 Introduction to Cryptography
• CSCI 557 Computer Systems Architecture
• CSCI 558L Internetworking and Distributed Systems Laboratory
• CSCI 559 Machine Learning I: Supervised Methods
• CSCI 561 Foundations of Artificial Intelligence
• CSCI 563 Building Knowledge Graphs
• CSCI 564 Brain Theory and Artificial Intelligence
• CSCI 565 Compiler Design
• CSCI 566 Deep Learning and Its Applications