Independent Work Seminar Offerings - Spring 2024
Full details about the COS IW seminar offerings for the Spring 2024 semester can be found below.
Please note that enrollment process of the the spring independent work seminars differs from that of the fall. Students will rank seminars, and will then be assigned to one.
Click here for information on how to enroll in a Spring 2024 independent work seminar.
COS IW 01: Digital Humanities [FULL - This seminar has reached capacity]
Instructor: Brian Kernighan
Meeting Time: Fridays, 11:00am - 12:20pm
Location: Friend Center, Room TBA
Abstract:
"Digital humanities" covers a wide variety of ways in which scholars in the humanities – literature, languages, history, music, art, religion, and many other disciplines -- collect, curate, analyze and present information about their fields, using digital representations and technology.
Digital humanities data is intrinsic1:30-2:50pmally messy, and there is always a considerable effort devoted to cleaning it up even before study can begin. There is also much effort devoted to figuring out how to present it effectively and make it accessible to others.
This seminar is aimed at building tools and developing techniques that will help humanities scholars work more effectively with their data. This might include machine learning, natural language processing, data visualization, data cleaning, and user interface design for making the processes available to scholars just starting out in technology.
A typical project might begin with a humanities dataset or a focus on a CS technique. In the former case, the goal would be to explore the data to learn and present new and interesting things about it. In the latter case, the goal would be to create or improve tools, languages, and interfaces that help scholars in the humanities.
No particular background is required beyond COS 217 and 226 and an interest in learning new things and applying that knowledge usefully.
COS IW 02: Digital Humanities [FULL - This seminar has reached capacity]
Instructor: Brian Kernighan
Meeting Time: Fridays, 1:30 - 2:50pm
Location: Friend Center, Room TBA
Abstract:
"Digital humanities" covers a wide variety of ways in which scholars in the humanities – literature, languages, history, music, art, religion, and many other disciplines -- collect, curate, analyze and present information about their fields, using digital representations and technology.
Digital humanities data is intrinsic1:30-2:50pmally messy, and there is always a considerable effort devoted to cleaning it up even before study can begin. There is also much effort devoted to figuring out how to present it effectively and make it accessible to others.
This seminar is aimed at building tools and developing techniques that will help humanities scholars work more effectively with their data. This might include machine learning, natural language processing, data visualization, data cleaning, and user interface design for making the processes available to scholars just starting out in technology.
A typical project might begin with a humanities dataset or a focus on a CS technique. In the former case, the goal would be to explore the data to learn and present new and interesting things about it. In the latter case, the goal would be to create or improve tools, languages, and interfaces that help scholars in the humanities.
No particular background is required beyond COS 217 and 226 and an interest in learning new things and applying that knowledge usefully.
COS IW 03: Invention and Innovation: Entrepreneurial Lessons for Computer Scientists [FULL - This seminar has reached capacity]
Instructor: Robert Fish
Meeting Time: Tuesdays, 3:00 - 4:20pm
Location: CS 402
Abstract:
How does an idea for an invention actually become an innovation in the marketplace? You may be a computer programming wizard, but there is a lot more to it than just fingers on the keyboard. This seminar, in concert with your building an independent prototype of your choice, introduces some of the elements of thinking and developing an idea into a budding concern. Your project will include a software prototype, a presentation, and a paper that explores the feasibility of your idea as a business. To help you frame and complete your project, we will discuss distinctions between invention and innovation, various brainstorming and invention methodologies, the DARPA methodology for idea screening, an introduction to intellectual property including patents, aspects of a simple business plan, project planning and management, and the elements of a “pitch deck.” Typically, we have some interaction with one of Princeton’s programs for entrepreneurial activities. For the more adventurous, the possibility exists for you to share your idea in a real “virtual” startup pitch event and report on the results.
Students may pair up in these projects, creating a joint idea for an enterprise, with each student concentrating on some aspect of the software with a division of labor of front-end, back-end, mobile app, data analysis, marketing, finance, etc. This IW seminar is complementary to COS 448 (Innovating across Technology, Business, and Marketplaces) and would be appropriate both before and after taking COS 448. If you’ve started a project with some entrepreneurial aspects in COS 333, you might want to consider developing it further in this IW Seminar. Also, given the extraordinary circumstances created by the pandemic over the last few years, you might want to think about some entrepreneurial project that addresses issues of remote work and learning, pandemic responses, or remedying social, economic, or political issues.
COS IW 04: Machine Learning and Algorithms for Medicine [FULL - This seminar has reached capacity]
Instructor: Mona Singh
Meeting Time: Mondays, 1:30 - 2:50pm
Location: CIL 200
Abstract:
Do you want to learn how to use the awesome power of computer science to learn more about or help treat cancer, COVID, or other diseases? The large amounts of data collected about patients with diseases such as cancer—from their genome sequences to medical images—opens up new opportunities for computer scientists to contribute to medicine, including developing individualized treatments for patients (i.e., precision health). At the same time, biases in existing biomedical datasets raises questions about how best to advance computational medicine while striving towards equitable health outcomes. In this seminar, students will work on projects where algorithms and/or machine learning techniques can be applied to biomedical and related datasets, and will include projects broadly addressing health equity.
This course has no prerequisites beyond COS126 and COS226. No prior biological or medical background will be assumed, and the necessary biomedical background will be presented in the seminar. Students may work on projects individually or in pairs. Class meetings will primarily be used for presentations and discussions of ongoing projects.
COS IW 05: Artificial Intelligence for Engineering and Physics [FULL - This seminar has reached capacity]
Instructor: Ryan Adams
Meeting Time: Mondays, 11:00am - 12:20pm
Location: CS 402
Abstract:
There have been exciting recent developments in artificial intelligence for things like images and natural languages, but what about interfacing with the real world? Deep learning, automatic differentiation, Bayesian optimization and other tools from machine learning are starting to impact the way we think about many physical systems, from modeling quantum mechanics to constructing buildings. We’re unlocking new ways to accelerate simulations, come up with new designs, fabricate complex structures, and control the behavior of embodied systems. In this seminar, students can work on a variety of problems, from neural network solutions of partial differential equations for nonlinear elasticity to generative models for distant galaxies to differentiable simulation of soft robots. Students don’t need to already be experts in these topics but will need to bring enthusiasm to dive into areas outside their computer science expertise.
We will meet weekly and students will be expected to give short presentations on the progression of their projects. The first couple of class meetings will survey different areas at the interface between machine learning and physical systems, brainstorm ideas, and develop project proposals. The semester will culminate with a presentation and a final paper.
Note that generic machine learning topics are not in scope for the seminar, and neither are projects on, e.g., biology, healthcare, or the social sciences.
COS IW 06: Artificial Intelligence for Engineering and Physics [FULL - This seminar has reached capacity]
Instructor: Ryan Adams
Meeting Time: Mondays, 1:30 - 2:50pm
Location: CS 402
Abstract:
There have been exciting recent developments in artificial intelligence for things like images and natural languages, but what about interfacing with the real world? Deep learning, automatic differentiation, Bayesian optimization and other tools from machine learning are starting to impact the way we think about many physical systems, from modeling quantum mechanics to constructing buildings. We’re unlocking new ways to accelerate simulations, come up with new designs, fabricate complex structures, and control the behavior of embodied systems. In this seminar, students can work on a variety of problems, from neural network solutions of partial differential equations for nonlinear elasticity to generative models for distant galaxies to differentiable simulation of soft robots. Students don’t need to already be experts in these topics but will need to bring enthusiasm to dive into areas outside their computer science expertise.
We will meet weekly and students will be expected to give short presentations on the progression of their projects. The first couple of class meetings will survey different areas at the interface between machine learning and physical systems, brainstorm ideas, and develop project proposals. The semester will culminate with a presentation and a final paper.
Note that generic machine learning topics are not in scope for the seminar, and neither are projects on, e.g., biology, healthcare, or the social sciences.
COS IW 07: Reimagining Robotics Through Art [FULL - This seminar has reached capacity]
Instructor: Radhika Nagpal
Meeting Time: Tuesdays, 11:00am - 12:20pm
Location: CS 402
Abstract:
In her book Race After Technology, author Ruha Benjamin reminds us how the historical origins of robotics have centered our current visions around colonial and patriarchal themes: military and policing, industrial labor, and housework. Indeed the word robot itself is derived from the Czech word for slave. But the future of robotics could be envisioned differently, e.g. joyous, uplifting, and challenging the past. In this IW seminar, we will collectively explore a vision of robotics that enhances life through art. Students will be encouraged to imagine, design, and build hardware prototypes of robotic works of art, in small teams with support from teaching staff. Special emphasis will be put on art that centers and celebrates non-western culture, art forms, history, artists, and lived experiences (e.g. Black, LatinX, Asian, etc). In addition, we will read and discuss chapters from two books, Race After Technology and Design Justice, to think about how robotics can play a role in engineering equity. The seminar will not require prerequisites beyond COS 217 and COS 226. Students with experience in art, hardware, equity, and diverse cultures are strongly encouraged to apply.
COS IW 08: Reimagining Robotics Through Art
Instructor: Radhika Nagpal
Meeting Time: Thursdays, 11:00am - 12:20pm
Location: CS 402
Abstract:
In her book Race After Technology, author Ruha Benjamin reminds us how the historical origins of robotics have centered our current visions around colonial and patriarchal themes: military and policing, industrial labor, and housework. Indeed the word robot itself is derived from the Czech word for slave. But the future of robotics could be envisioned differently, e.g. joyous, uplifting, and challenging the past. In this IW seminar, we will collectively explore a vision of robotics that enhances life through art. Students will be encouraged to imagine, design, and build hardware prototypes of robotic works of art, in small teams with support from teaching staff. Special emphasis will be put on art that centers and celebrates non-western culture, art forms, history, artists, and lived experiences (e.g. Black, LatinX, Asian, etc). In addition, we will read and discuss chapters from two books, Race After Technology and Design Justice, to think about how robotics can play a role in engineering equity. The seminar will not require prerequisites beyond COS 217 and COS 226. Students with experience in art, hardware, equity, and diverse cultures are strongly encouraged to apply.
COS IW 09: Operating Systems Hacking for Fun and Profit
Instructor: Amit Levy
Meeting Time: Thursdays, 11:00am - 12:20pm
Location: Friend Center, Room TBA
Abstract:
There is renaissance of operating systems. New programming languages enable new operating system designs, open and specialized hardware calls for rethinking basic operating system interfaces, and new modalities for using computers---in the cloud, on mobile devices, and in embedded contexts---constrains and enables operating systems in new ways.
This seminar explores how contemporary operating systems are being built. We will learn the basics of operating systems, including the particular challenges of building or contributing to an operating system. Projects may apply broad areas of systems to these operating systems. For example, projects may choose to build a networking stack for a particular operating system, build an operating system for some exotic hardware platform, analyze or improve their security, formally prove correctness properties, or apply data-driven techniques to improve performance.
Recommended background includes COS 316.
COS IW 10: Molecular Machine Learning
Instructor: Ellen Zhong
Meeting Time: Thursdays, 3:00 - 4:20pm
Location: CS 402
Abstract:
Recent breakthroughs in machine learning algorithms have transformed the study of proteins and other biomolecules. Deep learning algorithms designed for molecular data are advancing key scientific questions relating to molecular properties, 3D shape, interactions, and molecular design. This seminar will explore computational applications to the study of molecular systems with a focus on proteins and structural biology. We will take a holistic approach when considering problems in this domain. Students are encouraged to develop projects pursuing either classical algorithms or the latest deep learning approaches. Recommend background include COS 324 and an introductory biology class (or a willingness to learn).
COS IW 11: Wrestling with Distributed Systems
Instructor: Mae Milano
Meeting Time: Thursdays, 11:00am - 12:20pm
Location: CS 302
Astract:
The future is distributed: applications that once ran on individual local machines have become collaborative, featuring cloud-backed services, in-browser options and real-time collaboration. Making collaborative applications work in a distributed setting can be quite challenging for programmers! One common paradigm in use is the "application server" model. This approach separates concerns between the "application" layer and the "communication" layer, using a single general-purpose distributed system to handle communication. Programmers then write a custom application server which relies on this general system to handle storage and communication. Crucially, these application servers are lightweight and store no state on their own; rather, the system state is always referenced via the backing distributed system. In this setting, the challenge is not in writing correct distributed protocols; instead, it is in carefully selecting and tuning the correct backing system for the job.
In this seminar, each student will write a collaborative distributed application using the "application server" paradigm. They will carefully choose the appropriate backing server, balancing the need for performance with the need for correctness. Along the way, students will learn about how to understand and correctly choose consistency guarantees, how to detect and defeat scaling bottlenecks, how to deploy and debug distributed systems, and several popular distributed systems frameworks.
Enrollment Information, Spring 2024
Enrollment in the IW seminars for the spring is different that enrollment in the fall.
To enroll in a COS IW seminar for Spring 2024:
- AB juniors: no enrollment in TigerHub required. Login to the COS IW portal and rank your IW seminars in the Spring 2024 IW Sign-Up form
- BSE juniors: enroll in COS 398, S99 AND login to the COS IW portal and rank your IW seminars in the Spring 2024 IW Sign-Up form
- BSE seniors: enroll in COS 498, S99 AND login to the COS IW portal and rank your IW seminars in the Spring 2024 IW Sign-Up form
Students will be assigned to a spring IW seminar. We try our best to accommodate students into one of their top three seminar preferences, but this is subject to available seats and student interest. Students are not guaranteed a spot into a particular seminar. If you have a question about this, please email Mikki Hornstein at mhornstein@princeton.edu.
