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.

Spring 2021

CSE 410 Blockchain Advanced Concepts (Lecture)
Section: BINA
Instructor: Bina Ramamurthy
Description: The blockchain stack has five layers: decentralized application, smart contracts, protocol, operating system, and network layers. This course focuses on the blockchain protocol layer, the support provided by the layers below it, and the algorithms and techniques supporting its design and implementation. Topics include Bitcoin and Ethereum blockchain protocols, state management using Merkle trees; consensus algorithms: proof of work, proof of authority, proof of stake, and practical byzantine fault tolerance methods; scalability issues and solutions: side channel, block size, sharding, network-layer solutions such as Tx and block relays; Universal digital identity and self-management of identity; Confidentiality, security, and privacy methods: zero-knowledge proofs, Zcash shielded transactions; Interoperability among protocols: baseline protocol; tokenization with fungible and non-fungible tokens; Ethereum standards and protocol improvement methods; private, public and permissioned blockchains. Upon completing the course, a student will be able to apply protocol level features in application development and contribute to protocol improvements.
Notes: Blockchain protocol level design and development
Prereqs: CSE250 Data Structures, equivalent, or permission of the instructor
Instruction Mode: Remote: real time and recorded
Class #: 25091
Dates: 02/01/2021 - 05/07/2021
Days, Time: MW, 12:40PM-2:00PM
Location: Remote
Credit Hours: 1.00-3.00
Enrollment: 5/50 (0/50 seats reserved: force registration only) (Active)
Links: Registration: CSE 410LEC registration number 25091 calendar icon | Course Catalog: CSE 410LEC orange catalog icon
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).  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.
Notes: A computer security course traditionally offered as CSE 565, but now is also cross-listed as an undergraduate course.
Prereqs: (CSE 331 or CSE 396) AND (CSE 220 or CSE 421 or CSE 365) AND (CSE 365 or CSE 489 or CSE 312)
Instruction Mode: Remote class, in person exam
Class #: 23809
Dates: 02/01/2021 - 05/07/2021
Days, Time: TR, 9:35AM-10:50AM
Location: Remote
Credit Hours: 1.00-3.00
Enrollment: 2/ 5 (0/5 seats reserved: force registration only) (Active)
Links: Registration: CSE 410LEC registration number 23809 calendar icon | Course Catalog: CSE 410LEC orange catalog icon
CSE 410 Machine Learning and Society (Lecture)
Section: JOSE
Instructor: Kenneth A. Joseph
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). 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 majors section.
Prereqs: CSE 474 (or satisfy co-requisite)
Coreqs: CSE 474 AND CSE 331 (or satisfy prerequisite
URL: http://www-student.cse.buffalo.edu/~atri/algo-and-society/spr20/index.html
Instruction Mode: Remote: real time
Class #: 23810
Dates: 02/01/2021 - 05/07/2021
Days, Time: TR, 9:35AM-10:50AM
Location: Remote
Credit Hours: 1.00-3.00
Enrollment: 4/20 (0/20 seats reserved: force registration only) (Active)
Links: Registration: CSE 410LEC registration number 23810 calendar icon | Course Catalog: CSE 410LEC orange catalog icon
CSE 410 Introduction to Matlab (Lecture)
Section: RUSS
Instructor: Russ Miller
Description: This course focuses on an introduction to Matlab for students in the Department of Computer Science and Engineering. Students will learn the basics of Matlab, they will work on weekly reading, homework, and programming assignments, as well as a semester-long project of their choosing (as approved by the instructor).
Notes: This course focuses on an introduction to Matlab for students in the Department of Computer Science and Engineering. Students will learn the basics of Matlab, they will work on weekly reading, homework, and programming assignments, as well as a semester-long project of their choosing (as approved by the instructor).
Prereqs: CSE250 or CSE331 or CSE529 or CSE531 AND permission of instructor.
Instruction Mode: Remote: real time
Class #: 22128
Dates: 02/01/2021 - 05/07/2021
Days, Time: T, 5:00PM-7:50PM
Location: Remote
Credit Hours: 1.00-3.00
Enrollment: 18/25 (0/25 seats reserved: force registration only) (Active)
Links: Registration: CSE 410LEC registration number 22128 calendar icon | Course Catalog: CSE 410LEC orange catalog icon
CSE 410 Computational Investment 2 (Lecture)
Section: ZHEN
Instructor: Zhen Liu
Description: Built on the first course of the sequence, CSE 478, this course will focus on "live" trading with Paper Money on defined portfolios, and modeling, testing, and implementing trading systems with advanced computer techniques (such as data preparation and analysis, simulation, performance monitoring and evaluation). The goal is to empower students to become investors with real confidence in conservative investment decisions. Guest lectures on Machine Learning based techniques will also be offered.
Prereqs: CSE 478 or ECO 531
Instruction Mode: Remote: real time and recorded
Class #: 25273
Dates: 02/01/2021 - 05/07/2021
Days, Time: R, 6:30PM-8:00PM
Location: Remote
Credit Hours: 1.00-3.00
Enrollment: 2/10 (0/10 seats reserved: force registration only) (Active)
Links: Registration: CSE 410LEC registration number 25273 calendar icon | Course Catalog: CSE 410LEC orange catalog icon