printer friendly pageCS 148: Introduction to Computer Graphics and Imaging
This is the introductory prerequisite course in the computer graphics sequence which introduces students to the technical concepts behind creating synthetic computer generated images. The beginning of the course focuses on using Blender to create visual imagery, as well as an understanding of the underlying mathematical concepts including triangles, normals, interpolation, texture mapping, bump mapping, etc. Then we move on to a more fundamental understanding of light and color, as well as how it impacts computer displays and printers. From this we discuss more thoroughly how light interacts with the environment, and we construct engineering models such as the BRDF and discuss various simplifications into more basic lighting and shading models. Finally, we discuss ray tracing technology for creating virtual images, while drawing parallels between ray tracers and real world cameras in order to illustrate various concepts. Anti-aliasing and acceleration structures are also discussed. The
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This is the introductory prerequisite course in the computer graphics sequence which introduces students to the technical concepts behind creating synthetic computer generated images. The beginning of the course focuses on using Blender to create visual imagery, as well as an understanding of the underlying mathematical concepts including triangles, normals, interpolation, texture mapping, bump mapping, etc. Then we move on to a more fundamental understanding of light and color, as well as how it impacts computer displays and printers. From this we discuss more thoroughly how light interacts with the environment, and we construct engineering models such as the BRDF and discuss various simplifications into more basic lighting and shading models. Finally, we discuss ray tracing technology for creating virtual images, while drawing parallels between ray tracers and real world cameras in order to illustrate various concepts. Anti-aliasing and acceleration structures are also discussed. The final class project consists of building out a ray tracer to create a visually compelling image. Starter codes and code bits will be provided here and there to aid in development, but this class focuses on what you can do with the code as opposed to what the code itself looks like. Therefore grading is weighted towards in person "demos" of the code in action - creativity and the production of impressive visual imagery are highly encouraged.This is the first course in the computer graphics sequence at Stanford. Topics include: Scanline Rendering; Triangles; Rasterization; Transformations; Shading; Triangle Meshes; Subdivision; Marching Cubes; Textures; Light; Color; Cameras; Displays; Tone Mapping; BRDF; Lighting Equation; Global Illumination; Radiosity; Ray Tracing; Acceleration Structures; Sampling; Antialiasing; Reflection; Transmission; Depth of Field; Motion Blur; Monte Carlo; Bidirectional Ray Tracing; Light Maps.
Terms: Aut
| Units: 3-4
| UG Reqs: GER:DB-EngrAppSci, WAY-CE
Instructors:
Fedkiw, R. (PI)
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Akintan, M. (TA)
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Becker, N. (TA)
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Frausto, J. (TA)
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Halder, S. (TA)
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He, H. (TA)
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Jobalia, S. (TA)
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Kaputa, Z. (TA)
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Kuang, Z. (TA)
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Leanza, L. (TA)
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Li, J. (TA)
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Mandal, U. (TA)
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Omens, D. (TA)
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Patterson, K. (TA)
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Phan, K. (TA)
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Rodriguez, S. (TA)
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Ruban, R. (TA)
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Shubhangi, S. (TA)
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Tang, M. (TA)
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Xia, J. (TA)
CS 149: Parallel Computing
This course is an introduction to parallelism and parallel programming. Most new computer architectures are parallel; programming these machines requires knowledge of the basic issues of and techniques for writing parallel software. Topics: varieties of parallelism in current hardware (e.g., fast networks, multicore, accelerators such as GPUs, vector instruction sets), importance of locality, implicit vs. explicit parallelism, shared vs. non-shared memory, synchronization mechanisms (locking, atomicity, transactions, barriers), and parallel programming models (threads, data parallel/streaming, MapReduce, Apache Spark, SPMD, message passing, SIMT, transactions, and nested parallelism). Significant parallel programming assignments will be given as homework. The course is open to students who have completed the introductory CS course sequence through 111.
Terms: Aut
| Units: 3-4
| UG Reqs: GER:DB-EngrAppSci
Instructors:
Fatahalian, K. (PI)
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Granado, M. (TA)
;
Guo, M. (TA)
...
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Instructors:
Fatahalian, K. (PI)
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Granado, M. (TA)
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Guo, M. (TA)
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Hong, J. (TA)
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Hwa, J. (TA)
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Jiang, S. (TA)
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Kunjal, N. (TA)
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Mitchell, Y. (TA)
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Olukotun, O. (TA)
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Shen, T. (TA)
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Sundram, S. (TA)
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You, Z. (TA)
CS 151: Logic Programming
Logic Programming is a style of programming based on symbolic logic. In writing a logic program, the programmer describes the application area of the program (as a set of logical sentences) without reference to the internal data structures or operations of the system executing the program. In this regard, a logic program is more of a specification than an implementation; and logic programs are often called runnable specifications. This course introduces basic logic programming theory, current technology, and examples of common applications, notably deductive databases, logical spreadsheets, enterprise management, computational law, and game playing. Work in the course takes the form of readings and exercises, weekly programming assignments, and a term-long project. Prerequisite:
CS 106B or equivalent.
Terms: Spr
| Units: 3
Instructors:
Genesereth, M. (PI)
;
Lee, M. (TA)
CS 152: Trust and Safety (COMM 122, INTLPOL 267)
Trust and Safety is an emerging field of professional and academic effort to build technologies that allow people to positively use the internet while being safe from harm. This course provides an introduction to the ways online services are abused to cause real human harm and the potential social, operational, product, legal and engineering responses. Students will learn about fraud, account takeovers, the use of social media by terrorists, misinformation, child exploitation, harassment, bullying and self-harm. This will include studying both the technical and sociological roots of these harms and the ways various online providers have responded. The class is taught by a practitioner, a professor of communication, a political scientist, and supplemented by guest lecturers from tech companies and nonprofits. Cross-disciplinary teams of students will spend the quarter building a technical and policy solution to a real trust and safety challenge, which will include the application of AI
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Trust and Safety is an emerging field of professional and academic effort to build technologies that allow people to positively use the internet while being safe from harm. This course provides an introduction to the ways online services are abused to cause real human harm and the potential social, operational, product, legal and engineering responses. Students will learn about fraud, account takeovers, the use of social media by terrorists, misinformation, child exploitation, harassment, bullying and self-harm. This will include studying both the technical and sociological roots of these harms and the ways various online providers have responded. The class is taught by a practitioner, a professor of communication, a political scientist, and supplemented by guest lecturers from tech companies and nonprofits. Cross-disciplinary teams of students will spend the quarter building a technical and policy solution to a real trust and safety challenge, which will include the application of AI technologies to detecting and stopping abuse. For those taking this course for CS credit, the prerequisite is CS106B or equivalent programming experience and this course fulfills the Technology in Society requirement. Content note: This class will cover real-world harmful behavior and expose students to potentially upsetting material.
Terms: Spr
| Units: 3
Instructors:
Grossman, S. (PI)
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Hancock, J. (PI)
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Stamos, A. (PI)
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Instructors:
Grossman, S. (PI)
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Hancock, J. (PI)
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Stamos, A. (PI)
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Cheruiyot, I. (TA)
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Dash, A. (TA)
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Gupta, A. (TA)
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Obbad, E. (TA)
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Oyeniyi, T. (TA)
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Patterson, K. (TA)
CS 153: Applied Security at Scale
This course is designed to help students understand the unique challenges of solving security problems at scale, and is taught by senior technology leaders from companies tackling hardware and software security for hundreds of millions of people. The course is split into six parts covering major themes: Basics, Confidential Computing, Privacy, Trust, Safety and Real World. The format of the class will include guest lectures from experts in each theme, covering a blend of both theory and real world scenarios. Prerequisite:
CS110/
CS111. Recommended but not required:
CS155.
Terms: Win, Spr
| Units: 3
CS 154: Introduction to the Theory of Computation
This course provides a mathematical introduction to the following questions: What is computation? Given a computational model, what problems can we hope to solve in principle with this model? Besides those solvable in principle, what problems can we hope to efficiently solve? In many cases we can give completely rigorous answers; in other cases, these questions have become major open problems in computer science and mathematics. By the end of this course, students will be able to classify computational problems in terms of their computational complexity (Is the problem regular? Not regular? Decidable? Recognizable? Neither? Solvable in P? NP-complete? PSPACE-complete?, etc.). Students will gain a deeper appreciation for some of the fundamental issues in computing that are independent of trends of technology, such as the Church-Turing Thesis and the P versus NP problem. Prerequisites:
CS 103 or 103B.
Terms: Aut
| Units: 3-4
| UG Reqs: GER:DB-EngrAppSci
CS 155: Computer and Network Security
For juniors, seniors, and first-year graduate students. Principles of computer systems security. Attack techniques and how to defend against them. Topics include: network attacks and defenses, operating system security, application security (web, apps, databases), malware, privacy, and security for mobile devices. Course projects focus on building reliable software. Prerequisite: 110. Recommended: basic Unix.
Terms: Spr
| Units: 3
| UG Reqs: GER:DB-EngrAppSci
Instructors:
Boneh, D. (PI)
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Durumeric, Z. (PI)
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Anand, K. (TA)
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Bradfield, A. (TA)
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Kim, J. (TA)
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Saligrama, A. (TA)
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Saue- Fletcher, L. (TA)
CS 157: Computational Logic
Rigorous introduction to Symbolic Logic from a computational perspective. Encoding information in the form of logical sentences. Reasoning with information in this form. Overview of logic technology and its applications - in mathematics, science, engineering, business, law, and so forth. Topics include the syntax and semantics of Propositional Logic, Relational Logic, and Herbrand Logic, validity, contingency, unsatisfiability, logical equivalence, entailment, consistency, natural deduction (Fitch), mathematical induction, resolution, compactness, soundness, completeness.
Terms: Aut
| Units: 3
| UG Reqs: GER:DB-EngrAppSci, WAY-FR
Instructors:
Genesereth, M. (PI)
;
Hardy, A. (TA)
CS 161: Design and Analysis of Algorithms
Worst and average case analysis. Recurrences and asymptotics. Efficient algorithms for sorting, searching, and selection. Data structures: binary search trees, heaps, hash tables. Algorithm design techniques: divide-and-conquer, dynamic programming, greedy algorithms, amortized analysis, randomization. Algorithms for fundamental graph problems: minimum-cost spanning tree, connected components, topological sort, and shortest paths. Possible additional topics: network flow, string searching. Prerequisite: 106B or 106X; 103 or 103B; 109 or
STATS 116.
Terms: Aut, Win, Sum
| Units: 3-5
| UG Reqs: GER:DB-EngrAppSci, WAY-FR
Instructors:
Anari, N. (PI)
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Charikar, M. (PI)
;
Rubinstein, A. (PI)
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Instructors:
Anari, N. (PI)
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Charikar, M. (PI)
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Rubinstein, A. (PI)
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Sotoudeh, M. (PI)
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Conkey, A. (TA)
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Cussen, H. (TA)
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Dixit, A. (TA)
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Garg, R. (TA)
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Goyal, S. (TA)
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Hosgur, E. (TA)
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Ko, J. (TA)
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Kolichala, P. (TA)
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Li, W. (TA)
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Liu, S. (TA)
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Mayer, T. (TA)
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Namboothiry, B. (TA)
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Parada, R. (TA)
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Patterson, K. (TA)
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Rivkin, J. (TA)
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Roghani, M. (TA)
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Salahi, K. (TA)
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Singh, A. (TA)
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Singhal, A. (TA)
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Stearns, C. (TA)
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Wang, X. (TA)
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Z. HaoChen, J. (TA)
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Zhang, P. (TA)
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Zhao, J. (TA)
CS 161ACE: Problem-Solving Lab for CS161
Additional problem solving practice for
CS161. Sections are designed to allow students to acquire a deeper understanding of CS and its applications, work collaboratively, and develop a mastery of the material. Concurrent enrollment in
CS 161 required. Limited enrollment, permission of instructor, and application required.
Terms: Aut, Win
| Units: 1
Instructors:
Sharkov, S. (PI)
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