CS294S is a research project course to explore how machine learning can revolutionize consumers' software experience. Students are invited to do quarter-long projects to answer questions such as those listed below or propose their own topics
CS294S is a cross-disciplinary research project course, designed to help students with their first research experience, emphasizing individual mentorship and learning through projects, rather than lecture-style learning. Students interested in AI, HCI, or programming systems, who have taken at least two computer science courses are welcome to attend.
Students, in groups of 1 to 3, can propose their projects or choose among suggested topics. Available to the students is the open-source Almond virtual assistant infrastructure, which can be used to prototype a natural language interface in just one day.
Students are required to come to campus for this course, where in-class participation and after-class project meetings are required. You can take this course multiple times for credit. CS 294S can be taken to fulfill the CS 194 requirement. Please sign up for CS 294W if you wish to fulfill your writing requirement as well.
Photo by Rakesh Ramesh
Sharpei: Your Go-To Shopper by Jeyla Aranjo
An automated service for finding dresses at Macys.com, given keywords and price points.
Dora by Eni Asebiomo, Kaylee Bunner, Meghana Rao
Don't know what to do when visiting a city? Dora can help you. Dora is a travel virtual assistant that plans your day in a new location given a price parameter!
WeSchedule by Tuan CaraballoWeSchedule is a platform to optimize and automate administrative operations at outpatient clinics. It leverages AI to compute optimal and realistic medical staff schedules and fair distributions of tasks across all team members. We aim to replace schedulers in the healthcare industry as well reduce the work of clinic managers by at least 50%.
Motif: Simple, Codeless, Demonstration-Based Programming for Creating Customized APIs for the Web by Allan Jiang, Albert FengMotif Automation enables an end-to-end, codeless system to create APIs for any set of web pages, which can later be used from a variety of interfaces, such as a voice-controlled personal assistant. The system has three stages: 1) recording a demonstration, 2) annotating the demonstration, and 3) executing the workflow as an API. Motif converts a typically arduous and manual task into a single API call, which can be created in a couple minutes via demonstration, rather than a couple hours of scripting and coding.
Almondify - Integrating Spotify into Almond by Hemanth Kini, Gabby WrightOur project provides best-in-class support for natural language control of Spotify. We enable advanced music playback control, playlist modification, and information retrieval features, and demonstrate that Almond can provide superior control of a third-party service over commercial voice assistants.
Cow: Transforming Almond by Jestin Ma, Sawyer BirmbaumWe investigate the application of Google's "Transformer" model to semantic parsing problems, comparing it with the traditional RNN-based model used to parse Almond commands. Our initial results are promising; the transformer model performs at and, in some case, even slightly above the existing Almond parser while significantly reducing training times.
Friendhub by Matt Millican, Michael Araya, Silei XuDo we really need to rely on Facebook or Twitter to stay connected with our local social groups? We think not. We introduce FriendHub, a concept for a series of user-programmable social hubs curated by users to reinforce the real-world communities they belong to.
Locus by Sam Premutico, Matthew Stewart, Oluremi OsoLocus ingests, analyzes, and reports your Google location history. With Locus, you can interface with your Google location data via natural language to learn about your location history, trends, and habits.
Hiya: Managing Construction Project Workflows by Haiyin WangHiya is a tool enabling construction project managers to handle task workflows between multiple parties and dependency relationships. Its main features include a natural language interface for establishing task dependency based notifications, access control for tasks, and a web application interface to relate tasks to 3D model components of a construction project.
Exhibit: Data-driven Approach for Generating Automatic GUI Layouts by Richard Yang, Yuguan XingIn the pursuit of automatically generating GUIs for virtual assistants, an important component of this task is to identify the locations of where GUI elements should be. Our project attempts to leverage a labeled dataset of existing GUIs and use machine learning models to learn how to predict the locations of elements.
The course meets Tuesday and Thursday, from 10:30 AM to 11:50 AM in Gates 100.
This schedule is tentative and subject to change. Please pay attention to emails sent to the student list.
|Tue April 3||Overview of the course (slides).|
|Thu April 5||Intro + brainstorming + demo (slides). Homework 1 released.|
|Tue April 10||Project discussions|
|Thu April 12||More ideas + in-class discussions. Project proposal meeting signup.|
|Tue April 17||Mini hackathon. Homework 1 due.|
|Thu April 19||Project proposal. [Discussions]
|Tue April 24||Project proposal. [Discussions]
|Thu April 26||Project proposal. [Discussions]
|Tue May 1||Guest lecture: Data programming (Alex Ratner)|
|Thu May 3||Tutorial: Semantic parsing (Giovanni Campagna)|
|Tue May 8||Student-led discussion: Multimodal user interface|
|Thu May 10||Student-led discussion: System concepts (crowdsourcing and software architecture)|
|Tue May 15||Mini hackathon / work session|
|Thu May 17||Student-led discussion: NLP (semantic parsing and question answering)|
|Tue May 22||Student-led discussion: Virtual assistant|
|Thu May 24||Student-led discussion: Virtual reality and augmented reality|
|Tue May 29||Final project discussion|
|Thu May 31||Final project discussion|
|Tue June 5||Final project discussion|
|Mon June 11: (1:30-3:15 pm)||Final project demo (3 minute video) and poster session (during the scheduled final exam period)|
|Tue June 12||Final report due|
10 minutes + 10 minutes for questions and discussion. Your proposal should include:
15 minutes + 3 minutes for questions. Your presentation should include:
A 3-minute video to show off your project!
There is no page limit (minimum or maximum), but CS294W students must have substantial writing. Your report should include:
Office hours: by appointment
Office hours: Wednesday and Friday, 2 PM to 4 PM (Gates 407)