Independent Work Seminars

Independent work seminars are a way to provide students working on similar projects with assistance and feedback from their peers. We encourage all students who plan to do independent work for the first time to consider signing up for an independent work seminar. 

The independent work seminars bring together groups of students working on related problems. The content of the independent work seminars includes not only independent work on a project, but also guidance about how to choose projects, evaluate progress, design experiments, collaborate with others, make presentations, and other project management skills.

While every student is responsible for writing a paper and making presentations individually, within these seminars it is possible for groups of 2-3 students to work on different parts of the same large-scale project. For example, a few students might work together on a system for collaborative grading of assignments in large online courses, with one student developing the user interface, another designing the algorithms for assigning problems to graders, and a third implementing a system for integrating grader responses in the back-end server. 


How to enroll in a COS IW seminar for Spring 2026: 

Enrollment in the IW seminars for spring differs from enrollment in the fall. The COS IW portal will open for sign-ups on December 2.

Students will be assigned to a spring IW seminar via an algorithm. We try our best to accommodate students into one of their top three seminar preferences, but this is subject to available seats, seminar popularity, and individual IW requirements. Students are not guaranteed a spot in a particular seminar. If you have a question about this, please email Mikki Hornstein at mhornstein (at) princeton.edu.

  • AB juniors: No enrollment in TigerHub required. The Registrar will place COS 981 on your schedule before classes start in the spring.
  • BSE juniors:
    • Enroll in COS 399, S99 in TigerHub,
    • Wait 24-hours for the IW Portal to sync with your TigerHub enrollment, and
    • Login to the COS IW portal and rank your IW seminars in the Spring 2026 IW Sign-Up form by December 12, 2025.
  • BSE seniors:
    • Enroll in COS 497, S99 in TigerHub,
    • Wait 24-hours for the IW Portal to sync with your TigerHub enrollment, and
    • Login to the COS IW portal and rank your IW seminars in the Spring 2026 IW Sign-Up form by December 12, 2025.

  • COS IW is not available to sophomores.

     

Spring 2026 Independent Work Seminars

COS IW 01: Natural Language Processing

Instructor: Christiane Fellbaum
Meeting Time: Fridays, 10:40 am - 12:00 pm
Location: Computer Science Building, Room TBD
Capacity: 12 students


Abstract: 
Natural Language Processing aims to understand and model properties of human language and the ways it is produced and interpreted. The focus of this seminar will be on the analysis of explicit or implicit meaning in texts--on the word, sentence or document level. Each student will identify or acquire, scrape, clean and pre-process a dataset appropriate for their chosen research topic, using standard available tools and ßresources. Data may come from available text corpora, news outlets, blogs, tweets, topic-specific forums (sports, food), etc. For a semantic analysis, different approaches (using lexical resources, embeddings, n-grams, etc.) will be considered and applied.

Participants in the seminar will choose from a wide range of topics including but not limited to sentiment and opinion analysis, gender/nationality/religious/age/racial bias detection and mitigation, identification of fake news, computational humor, question answering and automated reasoning, financial market prediction, language puzzle generation, in English or another natural language. Students in past seminars have also pursued projects in computational analyses of music, classifying composers or musical style.

Projects usually (but not necessarily) include a machine learning component; COS324 is recommended but not required. Students are not expected to have prior independent research experience.

We meet weekly as a group and discuss everyone's project, progress, challenges and findings. Students may work in pairs so long as each student covers a separate aspect of the project.
 

COS IW 02: Robotics

Instructor: David August
Meeting Time: Fridays, 9:00 am - 10:20 pm
Location: Computer Science Building, Room TBD
Capacity: 12 students


Abstract: 
Working individually or in a team, you will build a working robot.  The instructor will help you apply what you have learned in your COS classes to construct a system that interacts with the physical world.
Past projects include:

  1. A robot that identifies the type of a presented article of clothing and folds it accordingly. Demo: https://drive.google.com/file/d/1X08P_QlFdtBe1H3nGtwBAmUpVwEIfEA-/view
  2. A friendly robot that autonomously delivers coffee to people in the CS building, using the elevator if necessary.
  3. A drone capable of quickly navigating through a thick forest.
COS IW 03: The Ethics of Evaluations

Instructor: Steven Kelts
Meeting Time: Tuesdays, 10:40 am - 12:00 pm
Location: Computer Science Building, Room TBD
Capacity: 12 students

Abstract:

When we think about evaluating ML models, our first thoughts might go to accuracy and precision (or confusion matrices, sensitivity, AUC, and so on).  But as ML is increasingly used in sensitive contexts – provision of vital government services, generating text and images for use in social life, etc. – the next generation of computing professionals has to also be aware of things like fairness, factuality and safety metrics (or measures of hallucinations, harmful content, bias, and so on).

Why do we need these evaluations?  How do they help us create better model performance?  What sort of society do we want to live in, and how can we use careful evaluation of models to help get us there?  The question of model evaluation now lives squarely at the intersection of ethics and computer science.  And so does this seminar.

Each week, we will explore one set of ethical ideas that might help us know what counts as “good” model performance, and even design evaluations that measure that good.  And students will share technical presentations of existing evaluation frameworks they have researched.  Sources will include Princeton’s Holistic Agent Leaderboard, Stanford’s Holistic Evaluation of Language Models, Arvind Narayanan and Sayash Kapoor’s AI Snake Oil, Mark Coeckelbergh’s AI Ethics, as well as various sources in ethics and fair machine learning.

The prerequisites for this seminar are COS217, COS226, and COS324. Students should know Python already and understand the basic tasks of machine learning: classification, regression, and clustering, etc. You can use existing machine learning packages in Python and develop your own library if needed.

This seminar will meet once a week on Tuesdays. Class times are used to discuss tech ethics concepts, present evaluations, and discuss students’ project progress. Each student will report their weekly progress on their project and present their project in class once during the semester.  Each student will also do a presentation on an evaluation they have researched, ideally with a small team of others (though solo presentations are acceptable).  on most of the weeks either in small groups or to the whole class. Students are expected to give feedback on projects being done by their peers; including the social impact of the projects, the ethics of that impact, and the technical methods being used.

Students should have their project chosen by the third week, with the help of the professor and peers. The professor will help students find individual projects which are doable within a semester, but are also suitable to be expanded into a senior thesis.  The professor will also help students write their paper in an accepted professional format, so they could be submitted for publication.

COS IW 04: AR Meets AI – Augmenting Humans in the Physical World

Instructor: Parastoo Abtahi
Meeting Time: Wednesdays, 10:40 am - 12:00 pm
Location: Computer Science Building, Room TBD
Capacity: 18 students

Abstract:

Augmented Reality (AR) applications seamlessly blend digital content into our physical spaces. How can we leverage AR to enrich everyday life—enhancing our perception, amplifying our intelligence, and extending our capabilities in the physical world? In this IW seminar, AR meets AI to examine how intelligent, interactive systems can augment humans. 


You’ll explore new possibilities by creating AR applications that (1) incorporate some form of intelligence, (2) are interactive and responsive to user input, and (3) are situated in the physical space rather than isolating users from their surrounding environment and people around them. 


You’ll take a user-centered approach to design, implement, and evaluate your application, engaging in need-finding, rapid low-fidelity prototyping, AR development, and usability testing. You’ll have the flexibility to choose your system’s output modality (e.g., visual, auditory, or haptic), as well as your development platform (e.g., Meta Quest headsets, Aria Glasses, Snap Spectacles). We’ll meet weekly to discuss progress updates. There will be a live demo, a recorded video for the final presentation, and a short final paper due at the end of the term. 


Reference: Programmable Reality


Required courses: COS 217 and COS 226 


Recommended courses: COS 333 or COS 436 


Helpful skills: programming in C# or JavaScript, experience with Unity or Lens Studio, 3D modeling, OpenAI APIs, expertise in a domain of interest (e.g., health, education, art, culture).

COS IW 05:  Technology Policy

Instructor: Mihir Kshirsagar
Meeting Time: Thursdays, 10:40 am - 12:00 pm
Location: Sherrerd Hall, Room TBD
Capacity: 12 students

Abstract:

In this IW seminar students get to work on crafting concrete policy responses to challenges posed by emerging computer and network technologies. There is a renewed sense of urgency to understand the implications of how these technologies are transforming public life and to craft practical solutions that address the difficult tradeoffs we need to make. Students in past seminars have worked on a variety of different projects, including those related to machine learning, social media, video game design, communication policy, competition, privacy, and cryptocurrencies, among other issues.

The first half of the seminar will focus on introducing students to policy challenges in different domains to help them explore potential topics for their final project. The second half of the seminar is devoted to workshopping the final projects and helping students develop workable proposals.

The final project will be student-driven, with the opportunity to create a real-world policy work product. Policymakers need thoughtful, technically sophisticated voices to help them develop evidence-based policies. This seminar helps students prepare to play that vital role. All students are expected to attend all weekly meetings and work collaboratively on shared projects. There are no prerequisites for taking this seminar.

COS IW 06: Language and Computation

Instructor: Suma Bhat
Meeting Time: Fridays, 10:40 am - 12:00 pm
Location: Computer Science Building, Room TBD
Capacity: 12 students

Abstract:
This is an intensive, project-based course exploring the foundational intersection of human language use and computational models, such as Large Language Models (LLMs). The course has two core objectives—using theory (e.g., cognitive, social, linguistic or computational theory) to critically analyze and understand how LLMs work, and conversely, leveraging LLMs as powerful tools to investigate and model complex phenomena in language use. Projects may study different language varieties (e.g., spoken languages of the world, dialects or synthetic languages) and language use cases (e.g., sign language).

Prerequisites and Course Format
Prerequisites: Students should have a solid foundation in programming and introductory machine learning (e.g., demonstrated via a good grade in COS 324). In the event that the project involves a theory-driven exploration, the student must similarly demonstrate familiarity with the theory (e.g., demonstrated by a good grade in a course that covered the theory).

Format: Student projects, planned and finalized via a project proposal in the first 10 days of class), are expected to meet one of the two objectives mentioned above. The projects will be carried out in a data-driven manner, using publicly available datasets and university computing resources. Seminar participants will share weekly project updates in class, present their final project outcomes, and submit a written final report. The core of the course grade is the semester-long, project performance.

COS IW 07: Technology Design for Sports, Health, and Assistive Applications

Instructor: Kyle Jamieson
Meeting Time: Fridays,  1:20 pm - 2:55 pm
Location: Computer Science Building, Room TBD
Capacity: 18 students

Abstract:

Wearable/augmented-reality platforms, sports and medical sensors, wireless radar, and other technologies are creating new opportunities to help athletes excel in their sports, keep us healthy, and assist persons with disabilities. At the same time, these exciting technologies also create new opportunities to help doctors, coaches, and therapists in the clinic and the home. Participants in this seminar will choose an assistive, sport, or medical application and develop a solution that will have real impact on peoples’ lives.

Possible assistive applications include hearing impairment, cognitive impairment (aphasia, autism spectrum, Parkinson's disease, prosopagnosia), and vision impairment. Other in-scope applications targeted on medical, sports, and psychological contexts include fall detection, vital sign monitoring, dermatology (melanoma detection and diagnosis, jaundice), pulmonary spirometry, physical/occupational therapy (stroke rehabilitation), sports medicine and performance analysis, and health monitoring (blood glucose, respiration rate, heart rate, blood pressure, EKG, seismocardiography, blood oxygenation). Possible hardware platforms include mobile devices, wearable health monitors, augmented reality devices (Microsoft HoloLens, Fove VR), 360-degree cameras (Google), wearable body-cams, and a variety of new-to-market medical, wireless, radar, and sports performance sensor technology (Garmin, Apple, Polar, and others).

COS IW 08: Algorithmic Diversity

Instructor: Adji Buosso Dieng
Meeting Time: Tuesdays, 2:55 pm - 4:15 pm
Location: Computer Science Building, Room TBD
Capacity: 18 students

Abstract:

In this seminar, you will explore the fundamental problem of rigorously quantifying the diversity of a given collection, e.g a dataset or outputs of a generative model. This is a crucial task for building robust machine learning models, analyzing social systems, and accelerating scientific discovery. In your project, you will choose one domain of interest in the natural sciences, machine learning, or the social sciences and identify a problem of interest to you in that domain. You will then study how to use the Vendi Scores, a family of flexible diversity metrics, to solve the problem.

The goal of this seminar is to help students reason with diversity and build algorithms using it to solve concrete problems. Students are strongly encouraged to explore any domain they are interested in.

The prerequisites for this seminar are linear algebra, calculus, and introductory optimization as well as COS 217 and COS 226. Students should know Python already. No background in advanced mathematical analysis or machine learning is required.

This seminar will meet once a week. Class times are used to discuss students' project progress. Each student will report their weekly progress on their project and present in class on most of the weeks, either in small groups or to the whole class. Students are expected to participate in class in both presenting their own projects and giving constructive feedback to projects by their peers.

The first class will be used to introduce the Vendi Scores and for discussing potential project ideas. Each student should develop an individual project which is suitable for one semester's work and may have the potential to extend to a senior thesis. A thorough, solid project may also lead to publication in some conference or workshop in the field.

Questions? Please email Mikki Hornstein at mhornstein (@princeton.edu).