Autumn 2022

CSE P 504 Advanced Topics in Software Systems: State of the Art Testing and Debugging
Instructor: René Just
Schedule: Mondays, 6:30-9:20pm
Place: Gates Center (CSE2) room G10 (map)
Principles of effective software testing and debugging, emphasizing state-of-the-art approaches. Topics include mutation-based testing, constraint-based testing, automated test generation, and probabilistic debugging.
Course video description available
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CSE P 521 Applied Algorithms
Instructor: Anup Rao
Schedule: Tuesdays, 6:30-9:20pm
Place: Gates Center (CSE2) room G10 (map)
Principles of design of efficient algorithms with emphasis on algorithms with real world applications. Examples drawn from computational geometry, biology, scientific computation, image processing, combinatorial optimization, cryptography, and operations research. Prerequisites: none.

CSE P 564 Computer Security
Instructor: David Kohlbrenner
Schedule: Wednesdays, 6:30-9:20pm
Place: Gates Center (CSE2) room G20 (map) + livestream to Microsoft Redmond campus, Building 99 room 1915
Examines the fundamental of computer security including: human factors; attack detection, measurements, and models; cryptography and communications security; system design and implementation; and side channels. Prerequisites: none.
Course video description available.

CSE P 590 section A Special Topics: AI for Medicine
Instructor: Sheng Wang
Schedule: Thursdays, 6:30-9:20pm
Place: Gates Center (CSE2) room G10 (map)
Developing artificial intelligence methods for medicine and drug discovery is an emerging topic. In this course, we will cover different parts of drug discovery that have benefited greatly from machine learning methods. Our lectures are divided into 4 parts: genomics for drug discovery, sequence for drug discovery, graph for drug discovery and structure for drug discovery.

The autumn 2022 colloquia sections for PMP students are:

CSE 519 D: Current Research in Computer Science
Tuesdays, 3:30-5:20
Grading: CR/NC

CSE 520 D: Computer Science Colloquium
Thursdays, 3:30-5:20
Grading: CR/NC

SLN codes for PMP colloquia sections are viewable on the autumn PCE time schedule.

All colloquia resources, including the colloquia search and reporting tools and requirements for earning credit, appear in the PMP student handbook under Academics - colloquium requirements and access.

Autumn 2022 registration is open for new and continuing PMP students.

Find a registration process overview, relevant links, and troubleshooting assistance in the Registration and Financials section of the PMP student handbook.

Autumn course and colloquium schedules and SLN codes are viewable on the time schedule:

> CSEP course time schedule and SLN codes

> PMP colloquium time schedule and SLN codes

Students may also locate SLN codes in MyPlan. The most straightforward way to locate PMP/CSEP courses is to search for 'CSE P' with the 'find PCE sections only' box checked. This will display only the PMP sections of CSEP courses, which are nearly always numbered CSE P 5XX A and displayed on the 'Professional & Continuing Education' tab. Courses numbered CSEP 5XX M and displayed on the 'Seattle' tab are jointly-listed sections for the Allen School's fifth-year MS students only.

A step-by-step registration guide is available for student review. It describes the pre-registration steps required before first-time registration for a quarter, locating SLN codes, and completing registration transactions.

Winter 2023

CSE P 505 Programming Languages
Instructor: James Wilcox
Schedule: Tuesday, 6:30-9:20pm
Place: Gates Center (CSE2) room G01 (map)
A study of non-imperative programming paradigms such as functional, object-oriented, logic, and constraint programming. Programming language semantics and type theory. Prerequisites: none.
Course video description from 2021 (same instructors)

CSE P 546 Machine Learning
Instructor: Kevin Jamieson
Schedule: Wednesday, 6:30-9:20pm
Place: Gates Center (CSE2) room G20 (map) + livestream to Microsoft campus, B99 room 1915.
Methods for designing systems that learn from data and improve with experience. Supervised learning and predictive modeling; decision trees, rule induction, nearest neighbors, Bayesian methods, neural networks, support vector machines, and model ensembles. Unsupervised learning and clustering.
Course video description available

CSE P 557 Current Trends in Computer Graphics
Instructor: Zoran Popović
Schedule: Thursday, 6:30-9:20pm
Place: Gates Center (CSE2) room G10 (map)
Introduction to computer image synthesis, modeling, and animation emphasizing the state-of-the-art algorithm applications. Topics may include visual perception, image processing, geometric transformations, hierarchical modeling, hidden-surface elimination, shading, ray-tracing, anti-aliasing, texture mapping, curves, surfaces, particle systems, dynamics, realistic character animation, and traditional animation principles. Prerequisites: none.

CSE P 590 Special Topics: Entrepreneurship
Instructor: Greg Gottesman (LinkedIn) and Ed Lazowska
Schedule: Wednesday, 6:00-9:20pm
Place: Paccar Hall (PCAR) room 291 (map)
Company-building from formation to successful exit. This course is about entrepreneurship and specifically about starting, growing, managing, leading, and ultimately exiting a new venture. Prerequisites: none; enrollment by instructor permission.
Instructor permission required to enroll; please see course website for link to enrollment application.

CSE P 590 Special Topics: The Future of Accessible Technology
Instructor: Jen Mankoff
Schedule: Tuesday, 5:30-8:20pm
Place: Gates Center (CSE2) room G10 (map)
Access technology (AT) has the potential to increase autonomy, and improve millions of people’s ability to live independently. This potential is currently under-realized because the expertise needed to create the right AT is in short supply and the custom nature of AT makes it difficult to deliver inexpensively. How can computing enable new solutions to accessibility, including both access to the world and access to computers? Similarly, how can a disability studies perspective guide us in developing empowering and relevant solutions to accessibility problems? This course explores both of those questions through a combination of discussions, reading, and building.
Course video description available

The winter 2023 colloquia sections for PMP students are:

CSE 519 C: Current Research in Computer Science
Tuesdays, 3:30-5:20
Grading: CR/NC

CSE 520 C: Computer Science Colloquium
Thursdays, 3:30-5:20
Grading: CR/NC

SLN codes for PMP colloquia sections are viewable on the winter PCE time schedule.

All colloquia resources, including the colloquia search and reporting tools and requirements for earning credit, appear in the PMP student handbook.

Winter 2023 registration opens on November 4, 2022.

Winter course and colloquium schedules and SLN codes are viewable on the time schedule:

> CSEP course time schedule and SLN codes

> PMP colloquium time schedule and SLN codes

Students may also locate SLN codes in MyPlan. The most straightforward way to locate PMP/CSEP courses is to search for 'CSE P' with the 'find PCE sections only' box checked. This will display only the PMP sections of CSEP courses, which are nearly always numbered CSE P 5XX A and displayed on the 'Professional & Continuing Education' tab. Courses numbered CSEP 5XX M and displayed on the 'Seattle' tab are jointly-listed sections for the Allen School's fifth-year MS students only.

Find a registration process overview, relevant links, and troubleshooting assistance in the Registration and Financials section of the PMP student handbook.

Spring 2023

CSE P 590 Special Topics: Robotics (section A)
Instructor: Dieter Fox
Schedule: Wednesday, 6:30-9:20pm
Place: Gates Center (CSE2) room G10 (map)
This class will provide an overview of the fundamental problems and techniques in robotics by covering three broad areas with applications in mobile robotics, manipulation, and autonomous driving:

  • State Estimation: How can a robot understand the world around it, both spatially and conceptually? Topics include sensor and motion models, Bayesian filtering, localization, and mapping.
  • Planning: How can a robot use its understanding of the world to plan actions and accomplish objectives? Topics include motion planning, heuristic and sampling-based planning, and manipulation.
  • Learning: How can a robot learn to interpret its sensor data and perform actions to solve tasks? Topics include Gaussian processes, neural networks, and vision for robotics.
This class will use the basic tools of probability and linear algebra. Prior exposure to AI techniques, such as those discussed in CSE 473, is very helpful. The programming assignments will use Python and Numpy. Familiarity with these concepts and tools is recommended, but we will make every effort to get students up to speed who need extra background. The assignments use the PyBullet simulator, and are designed to run in Ubuntu, but we will provide a VM for students who do not have access to their own Ubuntu machine, and will help students navigate this infrastructure. Some assignments will also use Pytorch for machine learning. Familiarity with this is helpful, but not expected. We will provide tutorial sessions during some lectures to help students understand the tools as they become necessary for the assignments.

CSE P 590 Special Topics: Enterprise Chatbots (section B)
Instructor: Andi Gavrilescu (LinkedIn); email: andig (at) cs (dot) wash...
Schedule: Tuesday, 6:30-9:20pm
Place: Gates Center (CSE2) room G10 (map)
Theoretical and practical aspects of building chatbots for enterprises. Topics will include understanding natural language queries, extracting user intent, enterprise knowledge building from unstructured and semi structured content, querying databases, personalization, and dialog management. Prerequisites: none, but Natural Language Processing or Machine Learning are recommended.
Course video description available.

CSE P 590 Special Topics: Neural Devices, Systems, and Computation (section C, meets with EEP 598)
Instructors: Raj Rao and Jeff Herron
Schedule: Thursday, 6:30-9:20pm
Place: Gates Center (CSE2) room G10 (map)
In this projects-based course, students will be introduced to the system integration practices for neural-interfacing devices with a focus on application programming interface (API) design to support closed-loop neural systems. Students will be introduced to applications of neural-interfacing devices such as Brain Computer Interfaces (BCIs) and commercial neuromodulation medical devices such as Deep Brain Stimulation (DBS). With these applications in mind, projects will focus on the development and design of APIs to continuously communicate, stream and process neural data, and control device functionality in real-time. Through these projects and class lectures, students will learn about the qualities of neural signals, data preprocessing and signal processing techniques, classifier development using machine learning methods, principles of real-time closed-loop control, and computer engineering concepts related to the integration of hardware and software for neural systems development.

Prerequisites: Students are expected to have some previous experience in programming, though only basic familiarity is required. Class projects will be written in C#, so familiarity with C#, Java, or C++ is highly recommended. Machine learning concepts will be learned using Python via off-line post-hoc analysis; no previous experience is necessary. An Arduino (provided) will be used in course projects as a surrogate for a remotely connected real-time device running class-provided code.

CSE P 590 Special Topics: Applied Cryptography (section D)
Instructor: Huijia (Rachel) Lin
Schedule: Monday, 6:30-9:20pm
Place: Gates Center (CSE2) room G20 (map) + livestream to Microsoft campus, B99 room 1915.
Introduction to cryptography, with a focus on applications to real-world systems. Topics will include classical primitives and goals (hash functions, block ciphers, secret- and public-key encryption, message authentication, authenticated encryption, key establishment, etc), as well as common attacks and implementation issues. Case studies will cover widely deployed protocols like TLS, as well as blockchains. Advanced cryptographic techniques like multi-party computation, homomorphic encryption, and zero-knowledge proofs will also be covered.

The spring 2023 colloquia sections for PMP students are:

CSE 519 C: Current Research in Computer Science
Grading: CR/NC

CSE 520 D: Computer Science Colloquium
Grading: CR/NC

SLN codes for PMP colloquia sections are viewable on the spring PCE time schedule.

All colloquia resources, including the colloquia search and reporting tools and requirements for earning credit, appear in the PMP student handbook.

Spring 2023 registration opens on February 10, 2023.

Spring course and colloquium schedules and SLN codes are viewable on the time schedule:

> CSEP course time schedule and SLN codes

> PMP colloquium time schedule and SLN codes

Students may also locate SLN codes in MyPlan. The most straightforward way to locate PMP/CSEP courses is to search for 'CSE P' with the 'find PCE sections only' box checked. This will display only the PMP sections of CSEP courses, which are nearly always numbered CSE P 5XX A and displayed on the 'Professional & Continuing Education' tab. Courses numbered CSEP 5XX M and displayed on the 'Seattle' tab are jointly-listed sections for the Allen School's fifth-year MS students only.

Find a registration process overview, relevant links, and troubleshooting assistance in the Registration and Financials section of the PMP student handbook.

Summer 2023

No PMP courses or colloquia offered in summer.


Course Offerings from Previous Academic Years:

2011-2012 offerings, 2012-2013 offerings, 2013-2014 offerings, 2014-2015 offerings, 2015-2016 offerings, 2016-2017 offerings, 2017-2018 offerings, 2018-2019 offerings, 2019-2020 offerings, 2020-2021 offerings, and 2021-2022 offerings are also available for review.