Special Topics

Special Topics courses cover some of our most innovative and promising research directions.  They are often prototypes of new courses that we are developing.

Special Topics courses offer variable course content, so each semester's offerings are unique.

Winter 2022

We aren't offering any courses in Winter 2022.

Spring 2022

CSE 410 Computer Security (Lecture)
Section: BLAN
Instructor: Marina Blanton
Description: This course introduces students to fundamentals of computer and information security, with the goals of developing a solid understanding of the principles of the security field and building knowledge of tools and mechanisms to safeguard a wide range of software and computing systems. Topics covered in the course include cryptographic background and tools, access control, authentication, software security, malware, Internet security protocols and standards (SSL/TLS, IPsec, secure email), intrusion detection and intrusion prevention systems (firewalls), database security, privacy, security management and risk assessment, and legal and ethical aspects (cybercrime, intellectual property). The undergraduate version is less work than graduate. CSE 565 generally covers similar topics to what CSE 365 covers, but doesn't spend as much time on the background and goes into more depth.
Prereqs: (CSE 331 or CSE 396) AND (CSE 220 or CSE 421 or CSE 365) AND (CSE 365 or CSE 489 or CSE 312), i.e., 3 courses are required (or 2 if one of them is CSE 365)
Instruction Mode: In person
Class #: 21892
Dates: 01/31/2022 - 05/13/2022
Days, Time: TR, 12:30PM-1:50PM
Location: Alumni 97, North Campus
Credit Hours: 1.00-3.00
Enrollment: 13/15 (0/15 seats reserved: force registration only) (Active)
Links: Registration: CSE 410LEC registration number 21892 calendar icon | Course Catalog: CSE 410LEC orange catalog icon
CSE 410 Machine Learning and Society (Lecture)
Section: JOS1
Instructor: Atri Rudra
Description: Machine Learning (ML) systems make decisions in all parts of our lives, starting from the mundane (e.g. Netflix recommending us movies/TV shows), to the somewhat more relevant (e.g. algorithms deciding which ads Google shows you) to the downright worrisome (e.g. algorithms deciding the risk of a person who is arrested committing a crime in the future). Whether we like it or not, ML systems are here to stay: the economic benefit of automation provided by ML systems means companies and even governments will continue to use algorithms to make decisions that shape our lives. While the benefits of using algorithms to make such decisions can be obvious, these algorithms sometimes have unintended/unforeseen harmful effects. This class will look into various ML systems in use in real life and go into depth of both the societal as well as technical issues. For students who are more technologically inclined, this course will open their eyes to societal implications of technology that such students might create in the future (and at the very least see why claiming "But algorithms/math cannot be biased" is at best a cop-out). For students who are more interested in the societal implications of algorithms, this class will give them a better understanding of the technical/mathematical underpinnings of these algorithms (because if you do not understand, at some non-trivial level, how these algorithms work you cannot accurately judge the societal impacts of an algorithm). The course will have separate sections for CSE majors and non-CSE majors since the expectations are different. CSE majors are expected to program ML systems in the project in the course while the non-CSE majors are expected to point out potential societal harms while their group creates an ML system in their project. CSE students cannot register for the non-CSE major section.
Prereqs: CSE 474 or (CSE 331 prior term and corequisite of CSE 474)
Instruction Mode: In person
Class #: 22879
Dates: 01/31/2022 - 05/13/2022
Days, Time: TR, 9:30AM-10:50AM
Location: Davis 101, North Campus
Credit Hours: 1.00-3.00
Enrollment: 0/12 (0/12 seats reserved: force registration only) (Active)
Links: Registration: CSE 410LEC registration number 22879 calendar icon | Course Catalog: CSE 410LEC orange catalog icon
CSE 410 Machine Learning and Society - non CSE section (Lecture)
Section: JOS2
Instructor: Atri Rudra
Description: Machine Learning (ML) systems make decisions in all parts of our lives, starting from the mundane (e.g. Netflix recommending us movies/TV shows), to the somewhat more relevant (e.g. algorithms deciding which ads Google shows you) to the downright worrisome (e.g. algorithms deciding the risk of a person who is arrested committing a crime in the future). Whether we like it or not, ML systems are here to stay: the economic benefit of automation provided by ML systems means companies and even governments will continue to use algorithms to make decisions that shape our lives. While the benefits of using algorithms to make such decisions can be obvious, these algorithms sometimes have unintended/unforeseen harmful effects. This class will look into various ML systems in use in real life and go into depth of both the societal as well as technical issues. For students who are more technologically inclined, this course will open their eyes to societal implications of technology that such students might create in the future (and at the very least see why claiming "But algorithms/math cannot be biased" is at best a cop-out). For students who are more interested in the societal implications of algorithms, this class will give them a better understanding of the technical/mathematical underpinnings of these algorithms (because if you do not understand, at some non-trivial level, how these algorithms work you cannot accurately judge the societal impacts of an algorithm). The course will have separate sections for CSE majors and non-CSE majors since the expectations are different. CSE majors are expected to program ML systems in the project in the course while the non-CSE majors are expected to point out potential societal harms while their group creates an ML system in their project. CSE students cannot register for the non-CSE major section.
Instruction Mode: In person
Class #: 24611
Dates: 01/31/2022 - 05/13/2022
Days, Time: TR, 9:30AM-10:50AM
Location: Davis 101, North Campus
Credit Hours: 1.00-3.00
Enrollment: 0/ 6 (0/6 seats reserved: force registration only) (Active)
Links: Registration: CSE 410LEC registration number 24611 calendar icon | Course Catalog: CSE 410LEC orange catalog icon
CSE 410 Software Security (Lecture)
Section: ZHAO
Instructor: Ziming Zhao
Description: This course is designed to provide students with good understanding of the theories, principles, techniques and tools used for software and system hacking and hardening. Students will study, in-depth, binary reverse engineering, vulnerability classes, vulnerability analysis, exploit and shellcode development, defensive solutions, etc. to understand how to crack and protect native software. In particular, this class covers offensive techniques including stack-based buffer overflow, heap security, format string vulnerability, return-oriented programming, etc. This class also covers defensive techniques including canary, shadow stack, address space layout randomization, control-flow integrity, etc. A key part of studying security is putting skills to the test in practice. Hacking challenges known as Capture The Flag (CTF) competitions are a great way to do this. In this class the progress of students are evaluated by lab assignment and in-class Capture-The-Flag (CTF) competitions.
Prereqs: CSE 220 Systems Programming
URL: https://zzm7000.github.io/teaching/2022springcse410510/index.html
Instruction Mode: In person
Class #: 24282
Dates: 01/31/2022 - 05/13/2022
Days, Time: MW, 5:00PM-6:20PM
Location: Obrian 109, North Campus
Credit Hours: 1.00-3.00
Enrollment: 20/30 (0/30 seats reserved: force registration only) (Active)
Links: Registration: CSE 410LEC registration number 24282 calendar icon | Course Catalog: CSE 410LEC orange catalog icon