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Undergraduate Research Topics

 

Suggested Undergraduate Research Topics

Links to many research areas in the department may be found at http://www.cs.princeton.edu/research/areas/ while links to projects may be found at http://www.cs.princeton.edu/research/projects/.

 

 

 

 

 

 

 

Computer Science Faculty:

Prof. Ryan Adams, Room 411

Prof. Ibrahim Albluwi, 221 Nassau Street, Room 101

Prof. Andrew Appel, Room 209

Prof. Sanjeev Arora, Room 407

Prof. David August, Room 221 Independent Work Seminar Instructor Fall 2019

Dr. Jack Brassil, On Leave

Prof. Mark Braverman, 194 Nassau St.,  Room 231

Prof. Bernard Chazelle, 194 Nassau St. Room 301 

Asst. Prof. Jia Deng, Room 423

Prof. David Dobkin, Room 419 

Dr. Robert Dondero, Corwin Hall, Room 038

Prof. Zeev Dvir,194 Nassau St.  Room 250

Prof. Barbara Engelhardt, Room 322 Sabbatical during the 2019-2020 AY

Dr. Christiane Fellbaum, Room 1-S-14 Green  - Independent Work Seminar Instructor Fall 2019

Prof. Edward Felten, Sherrerd Hall -  Room 302

Prof. Adam Finkelstein, Room 424 

Dr. Robert S. Fish, Corwin Hall, Room 037  - Independent Work Seminar Instructor Fall 2019

Prof. Michael Freedman, Room 308 

Prof. Tom Griffiths, Room 405

Prof. Aarti Gupta, Room 220 

Prof. Elad Hazan, Room 409 

Assoc. Prof. Kyle Jamieson, Room 306 -  Independent Work Seminar Instructor Fall 2019 On Leave Spring 2020 

Dr. Alan Kaplan, 221 Nassau Street - Room 105 

Prof. Brian Kernighan, Room 311

Asst. Prof. Zachary Kincaid, Room 219 - On Leave Fall 2019 

Assst. Prof. Gillat Kol, 194 Nassau St. -  Room 230

Asst. Prof. Amit Levy, Room 307

Dr. Dan Leyzberg, Corwin Hall, Room 034

Prof. Kai Li, Room 321 - On Leave Fall 2019 

Dr. Xiaoyan Li, 221 Nassau Street - Room 104

Asst. Prof. Wyatt Lloyd, Room 323 - On Leave Spring 2019 

Dr. Jérémie Lumbroso, Corwin Hall Room 035

Prof. Margaret Martonosi, Room 208 

Asst. Prof. Jonathan Mayer, Sherrerd Hall,  Room 307

Dr. Christopher Moretti, Corwin Hall, Room 036

Dr. Chris Musco, Room 417

Asst. Prof. Karthik Narasimhan, Room 422

Dr. Arvind Narayanan, Sherrerd Hall, Room 308 -  On leave Fall 2019 

Dr. Iasonas Petras, Corwin Hall Room 033

Prof. Benjamin Raphael, Room 309 - Independent Work Seminar Instructor Fall 2019

Prof. Ran Raz, 194 Nassau St.,  Room 240

Prof. Jennifer Rexford, Room 222

Prof. Szymon Rusinkiewicz, Room 406 - Sabbatical during the 2019-2020 AY

Asst. Prof. Olga Russakovsky, Room 408

Prof. Robert Sedgewick, Room 319

Prof. Sebastian Seung, Princeton Neuroscience Institute Room 153

Prof. Yoram Singer, Room 421 - On Leave Fall 2019 

Prof. Jaswinder Pal Singh, Room 324

Prof. Mona Singh, Room 420

Dr. Sahil Singla, Room 219

Prof. Robert Tarjan, Room 308

Prof. Olga Troyanskaya, Room 320

Prof. David Walker, Room 211 - Sabbatical during the 2019-2020 AY

Dr. Kevin Wayne, Corwin Hall, Room 040

Asst. Prof. Matt Weinberg, 194 Nassau St. Room 222

Asst. Prof. Mark Zhandry, 194 Nassau St. Room 242 

Opportunities outside the department:

Prof.Branko Glisic, Engineering Quad, Room E330
Prof. Sharad Malik, Engineering Quad, Room B224
Prof. Prateek Mittal, Engineering Quadrangle, Room B236
Prof. Ken Norman, PNI 137 Neuroscience Institute
Caroline Savage, Office of Sustainability Phone: (609) 258-7513, cs35@princeton.edu
Asst. Prof.Janet Vertesi, Sociology Dept, Wallace Hall 122 
Prof. David Wentzlaff, Engineering Quadrangle, Room 228

Prof. Ryan Adams, Room 411

  • Machine learning driven design
  • Generative models for structured discrete objects
  • Approximate inference in probabilistic models
  • Accelerating solutions to partial differential equations
  • Innovative uses of automatic differentiation
  • Modeling and optimizing 3d printing and CNC machining

Dr. Ibrahim Albluwi221 Nassau Street, Room 101

Prof. Andrew Appel, Room 209 

  • Research Areas: Formal methods, programming languages, compilers, computer security.
  • Independent Research Topics:
    • Software verification (for which taking COS 326 / COS 510 is helpful preparation)
    • Game theory of poker or other games (for which COS 217 / 226 are helpful)
    • Computer game-playing programs (for which COS 217 / 226)
    •  Risk-limiting audits of elections (for which ORF 245 or other knowledge of probability is useful)

Prof. Sanjeev Arora, Room 407 

  • Theoretical machine learning, deep learning and its analysis, natural language processing. My advisees would typically have taken a course in algorithms (COS423 or COS 521 or equivalent) and a course in machine learning.
  • Independent Research Topics: 
    • Show that finding approximate solutions to NP-complete problems is also NP-complete (i.e., come up with NP-completeness reductions a la COS 487). 
    • Experimental Algorithms: Implementing and Evaluating Algorithms using existing software packages. 
    • Studying/designing provable algorithms for machine learning and implementions using packages like scipy and MATLAB, including applications in Natural language processing and deep learning.
    • Any topic in theoretical computer science.

Prof. David August, Room 221

  • Research Areas: Computer Architecture, Compilers, Parallelism, Security, Performance.
  • Independent Research Topics:
    • Containment-based approaches to security:  We have designed and tested a simple hardware+software containment mechanism that stops incorrect communication resulting from faults, bugs, or exploits from leaving the system.   Let's explore ways to use containment to solve real problems.  Expect to work with corporate security and technology decision-makers.
    • Parallelism: Studies show much more parallelism than is currently realized in compilers and architectures.  Let's find ways to realize this parallelism.
    • Any other interesting topic in computer architecture or compilers. 

Prof. Mark Braverman194 Nassau St. Room 231

  • Research Areas: computational complexity, algorithms, applied probability, computability over the real numbers, game theory and mechanism design, information theory, applications of machine learning in healthcare and medicine. 
  • Independent Research Topics: 
    • Topics in computational and communication complexity.
    • Applications of information theory in complexity theory.
    • Algorithms for problems under real-life assumptions.
    • Game theory, network effects, and mechanism design.
    • Computation involving dynamical systems, fractals, and cellular automata. 
    • Game theory applied to problems in healthcare.

Prof. Bernard Chazelle, 194 Nassau St. Room 301

  • Research Areas: Natural Algorithms, Computational Geometry, Sublinear Algorithms. 
  • Independent Research Topics
    • Natural algorithms (flocking, swarming, social networks, etc).
    • Sublinear algorithms
    • Self-improving algorithms
    • Markov data structures

 

Asst. Prof. Jia Deng, Room 423

  •  Research Areas: Computer Vision, Machine Learning.
  • Independent Research Topics:
    • 3D Vision
    • Object recognition and action recognition
    • Deep Learning, autoML, meta-learning
    • Geometric reasoning, logical reasoning.

 

Prof. David Dobkin, Room 419 

  • Research areas:  processing and machine learning in public data sets, information visualization
    • Visualizing and learning from public data sets
    • Sports analytics
    • Development of interesting mobile phone apps

 

Dr. Robert Dondero, Corwin Hall, Room 038

  • Research Areas:  Software engineering; software engineering education.
  • Independent Research Topics:
    • Develop or evaluate tools to facilitate student learning in undergraduate computer science courses at Princeton, and beyond.
    • In particular, can code critiquing tools help students learn about software quality?

Prof. Zeev Dvir, 194 Nassau St. Room 250

  • Research Areas:  Research Areas: computational complexity, pseudo-randomness, coding theory and discrete mathematics.
  • Independent Research: I have various research problems related to Pseudorandomness, Coding theory, Complexity and Discrete mathematics - all of which require strong mathematical background.

Prof. Barbara Engelhardt, Room 322- On sabbatical during the 2019-2020 AY. 

  • Research Areas: Machine Learning, Statistics, Statistical Genomics
  • Independent Research Topics:
    • Development of statistical and ML models for large scale data analysis
      • fMRI data analysis
      • genetic, epigenetic, and organismal data
      • medical data: EMRs, time series, longitudinal studies
      • Other: music, movie ratings, recipes, text
    • Statistical models for specific questions:
      • Causal inference and instrumental variable analysis
      • Model checking with posterior predictive checks
      • Inference of undirected network from observational and time-series data

 

Dr. Christiane Fellbaum, 1-S-14 Green

  • Research Areas: theoretical and computational linguistics, word sense disambiguation, lexical resource construction, English and multilingual WordNet(s), ontology
  • Fall 2017 IW Seminar:
  • Independent Research Topics:
    • Anything having to do with natural language--come and see me with/for ideas suitable to your background and interests. Some topics students have worked on in the past:
    • Developing parsers, part-of-speech taggers, morphological analyzers for underrepresented languages (you don't have to know the language to develop such tools!)
    • Quantitative approaches to theoretical linguistics questions
    • Extensions and interfaces for WordNet (English and WN in other languages),
    • Applications of WordNet(s), including:
    • Foreign language tutoring systems,
    • Spelling correction software,
    • Word-finding/suggestion software for ordinary users and people with memory problems,
    • Machine Translation 
    • Sentiment and Opinion detection
    • Automatic reasoning and inferencing
    • Collaboration with professors in the social sciences and humanities ("Digital Humanities")

Prof. Edward Felten, Sherrerd Hall -  Room 302 

  • Research Areas: Computer security and privacy; Internet software; technology law and policy.

  • Independent Research Topics:

    • Technology for open government.
    • Computer security and privacy.
    • Digital media distribution.
    • Copy protection and peer to peer technologies.
    • Electronic voting.
    • Technology, society and public policy.
    • Any other interesting or offbeat topic.

Prof. Adam Finkelstein, Room 424 

  • Research Areas: computer graphics, audio.
  • Fall 2018 Seminar - Deep Learning
  • Ideas for independent Research Topics:
    • Any interesting project in computer graphics.
    • Tools for manipulating photos
    • Tools for anlyzing or manipulating recorded human speech.

Dr. Robert S. Fish, Corwin Hall, Room 037

Prof. Michael Freedman, Room 308 

Prof. Aarti Gupta, Room 220

  • Research Areas: Formal methods, program analysis, logic decision procedures
  • Independent Research Topics:
    • Finding bugs in open source software using automatic verification tools
    • Software verification (program analysis, model checking, test generation)
    • Decision procedures for logical reasoning (SAT solvers, SMT solvers)

Prof. Elad Hazan, Room 409  

  • Research interests: machine learning methods and algorithms, efficient methods for mathematical optimization, regret minimization in games, reinforcement learning, control theory and practice
  • Machine learning, efficient methods for mathematical optimization, statistical and computational learning theory, regret minimization in games.
  • Independent Research Topics:
    • Implementation and algorithm engineering for control, reinforcement learning and robotics
    • Implementation and algorithm engineering for time series prediction

Assoc. Prof. Kyle Jamieson, Room 306

  • Research areas: Wireless and mobile networking; indoor radar and indoor localization; Internet of Things
  • See other topics on my independent work ideas page (campus IP and CS dept. login req'd)

 

Dr. Alan Kaplan, 221 Nassau Street - Room 105 -

  • Research Areas: mobile app/technology,  programming language interoperability
  • Independent Research Topics:
    • Random Apps of Kindness - Effective communication and information sharing are vital during any natural disaster. For example: first responders need to communicate routes for finding people and delivering supplies; survivors need to be able to quickly share their locations and conditions; families and friends need to be able to rapidly contact and locate missing loved ones; government agencies need to be able to effectively coordinate logistics; local community members need to identify and share locations of shelters, safe sources of drinking water, etc.  Mobile technology can play a critical role in helping address these, and other, needs. Smartphones, for example, have multiple network interfaces, high-resolution cameras, and various position, motion and environmental sensors. However, smartphone apps are generally not tailored to emergency situations. They assume, for example, the availability of network infrastructure and unlimited battery power. Even in situations where network and/or battery is not an issue, today's apps are mostly limited in their support for effective communication and information sharing during disasters. The goal of these projects is to design and develop mobile solutions that can be used to help various stakeholders during emergency events. The goal is not just to "write an app," but rather to create an innovative approach to a problem and demonstrate/evaluate its utility and benefits. 
    • Smart Cities - Today's mobile devices and sensors provide opportunities to help better monitor and manage our communities.   Programmable/networked devices that measure, for example, humidity, temperature, volatile organic compounds (VOCs), particulate matter (PM2.5), and CO2, can generate valuable data.  The goal of these IW projects is to develop and evaluate platforms based on these technologies to help improve an understanding of our environment. 
    • Automated Multi-Language Toolset - Design, develop and evaluate a toolset that helps automate the development of multi-language software 

Prof. Brian Kernighan, Room 311-

  • Research Areas: application-specific languages, document preparation, user interfaces, software tools, programming methodology
  • Fall 2017 IW Seminar - Computer Science Tools and Techniques for Digital Humanities 
  • Independent Research Topics: 
    • Application-oriented languages, scripting languages.
    • Tools; user interfaces
    • Digital humanities

Asst. Prof. Zachary Kincaid, Room 219

Research areas: programming languages, program analysis, program verification, automated reasoning 

Independent Research Topics:

  • Develop a practical algorithm for an intractable problem (e.g., by developing practical search heuristics, or by reducing to SAT, or by identifying a tractable sub-problem, ...).
  • Design a domain-specific programming language, or prototype a new feature for an existing language.
  • Any interesting project related to programming languages or logic.
  •  

Asst. Prof. Amit Levy, Room 307

  • Research Areas: Operating Systems, Distributed Systems, Embedded Systems, Internet of Things
  • Independent Research Topics:
    • Distributed hardware testing infrastructure
    • Second factor security tokens
    • Low-power wireless network protocol implementation
    • USB device driver implementation

Dr. Dan Leyzberg, Corwin Hall, Room 034

  • Research Areas: human-robot interaction, human-computer interaction, online tools for computer science education.
  • Independent Research Topics:
    • How do people actually interact with technology? Investigate human-computer or human-robot interaction with experimental methodologies from the social sciences, including psychology and cognitive science. First step: identify the technology and usage/engagement metrics you might be interested in studying. You will write code that collects and analyzes this data.
    • Help me build tools for computer science education at Princeton and beyond. I taught high school computer science for many years and if you took any computer science at the high school level, you know that the tools available to teachers are relatively primitive. Princeton has a few internal tools developed for COS 126 that would be great to make available to high school students or to other colleges students such as the Java Visualizer and Websheets. You are not limited to these existing tools; propose a tool that might be useful to students and we'll try to make it work!

Prof. Kai Li, Room 321

  • Research Areas: Distributed systems; storage systems; content-based search and data analysis of large datasets.
  • Independent Research Topics:
    • Fast communication mechanisms for heterogeneous clusters.
    • Approximate nearest-neighbor search for high dimensional data.
    • Data analysis and prediction of in-patient medical data.
    • Optimized implementation of classification algorithms on manycore processors.

Dr. Xiaoyan Li, 221 Nassau Street - Room 104

  • Research areas: Information retrieval, novelty detection, question answering, AI, machine learning and data analysis.
  • Independent Research Topics:
    • Explore new statistical retrieval models for document retrieval and question answering.
    • Apply AI in various fields.
    • Apply supervised or unsupervised learning in health, education, finance, and social networks, etc.
    • Any interesting project related to AI, machine learning, and data analysis.

 

Asst. Prof. Wyatt Lloyd, Room 323

  • Research areas: Distributed Systems
  • Independent Research Topics:
    • Caching algorithms and implementations
    • Storage systems
    • Distributed transaction algorithms and implementations

 

Dr. Jérémie Lumbroso, Corwin Hall, Room 035

  • Research areas: Probabilistic algorithms (data streaming algorithms & random generation), data analysis, data structures, analysis of algorithms,  analytic combinatorics.
  • Possible Independent Research Topics:
    • Develop new algorithms for the distinct sampling problem (useful to in data analysis to get fast representative histograms of a large set of data).
    • Extend existing universal random generation framework (such as Boltzmann Samplingdemo here), or improve their implementation.
    • Design an optimized algorithm for a specific combinatorial class.
    • Analyze an algorithm using precise analytic combinatorics.
    • Text (or data) clustering and processing; linguistic analysis (especially with French, German, Spanish, etc.).
    • ...
  • I am also coordinating the development of new grading and assessment infrastructure at Princeton, that will eventually be open-source and deployed at other universities. These projects focus on automation, using various techniques - such as OCR or OMR -, smart heuristics, and creative UI design, to streamline most tasks associated with a university. The goal is to be more efficient, to collect more data, and to better understand what makes a good course. You would have the opportunity to contribute to something that will be used at Princeton's CS department (of which the intro course has the highest enrollment on campus) and beyond for years to come. Here are some example projects:
    • Design/improve an OMR (Optical Mark Recognition) project that is currently being deployed for the computer assisted grading of exams.
    • Integrate handwritten character recognition to the OMR component.
    • Analyze large quantities of secondary data collected (for example, do students that do the programming assignments in pairs do better in the course or not? how many hours in COS Lab are helpful on average, and when do we hit a point of diminishing returns).
    • Design heuristics and interfaces to spot students in difficulty much earlier in the term, when there is some hope of helping them.
    • Extend the COS Lab Queue so it may be used out of the box in all labs accross campus.
    • Develop a robust testing infrastructure using virtual machines, secure threads, and intelligent feedback to supplant the run-script system currently used.
    • Develop an interface to make grading of assignment done online.
    • Integrate hardware solutions (cardswipe, barcode scanning, etc.) to many of these tools to make them even more frictionless.
    • Some related crowd-sourcing projects...
  • A lot of these projects can include some Big Data component, and involve analyzing data and drawing some observations from it.
  • Finally, I am always up for any ambitious coding project, or survey project in preparation (or not) to an undergrad thesis.

Prof. Margaret Martonosi, Room 208

  • Research Areas: Evaluating the performance of different hardware synchronization instructions (fences and atomic memory operations) in highly parallel benchmark applications, across different implementations and instruction sets (eg: comparing x86 processors from Intel and AMD, ARM processors from Samsung, Qualcomm, etc).
  • Designing a specialized hardware accelerator for modern workloads (e.g., graph analytics, machine learning algorithms, mobile applications)
  • Investigating security and privacy vulnerabilities in IoT devices, particularly Smart Home architectures.  Particularly interested in solutions for detection and mitigation of race conditions and inconsistent state in IoT devices.
  • Other topics in computer architecture or mobile / IoT systems also possible.
  • Testing techniques for Distributed Systems. If you've ever had trouble debugging code, imagine how hard it is to find obscure bugs when the code is running on multiple servers and even multiple data centers! Our work studies verification and testing methods to automate concurrency and consistency tests for IoT and distributed systems. Come join us!

Asst. Prof. Jonathan Mayer, Sherrerd Hall - Room 307 

  • Research areas: Technology law and policy, with emphasis on national security, criminal procedure, consumer privacy, network management, and online speech.
  • Independent Research Topics:
    • Assessing the effects of government policies, both in the public and private sectors.
    • Collecting new data that relates to government decision making, including surveying current business practices and studying user behavior.
    • Developing new tools to improve government processes and offer policy alternatives.

Dr. Christopher Moretti, Corwin Hall, Room 036

  • Research areas: Distributed systems, high-throughput computing, computer science/engineering education
  • Independent Research Topics:
    • Expansion, improvement, and evaluation of open-source distributed computing software.
    • Applications of distributed computing for "big science" (e.g. biometrics, data mining, bioinformatics)
    • Software and best practices for computer science education and study, especially Princeton's 126/217/226 sequence or MOOCs development
    • Sports analytics and/or crowd-sourced computing

Karthik Narasimhan,  Room 422

  • Research areas: Natural Language Processing, Reinforcement Learning
  • Independent Research Topics:

Dr. Arvind Narayanan308 Sherrerd Hall 

Research areas: privacy, fairness in machine learning, cryptocurrencies & blockchains,.

Some topics and questions I'm interested in:

1. What can be inferred about people based on publicly available online data?
 
Did you know that computer vision techniques are capable of analyzing YouTube videos to infer the heart rates of people in the videos? This can be done by extracting the subtle, humanly imperceptible head motion caused by the influx of blood at each heart beat. What other sensitive information can be inferred based on publicly available data using clever algorithms?
 
2. How does machine learning absorb human biases and what can we do about it?
 
Machine learning captures patterns from training data, and that includes societal prejudices such as racial and gender stereotypes. Unsurprisingly, machine learning methods used for automated screening of resumes or automated risk scoring of criminal defendants turn out to be biased against some groups. How can we mitigate such biases?
 
3. Blockchain analysis with BlockSci
 
The Bitcoin blockchain is an unprecedented public log of financial transactions — 150 gigabytes and growing quickly. It holds many secrets. Can we do a forensic analysis of well-known thefts of bitcoins to discover where the money went? How anonymous are Bitcoin users? What does the wealth distribution look like? My research group has built a research tool called BlockSci to help answer these types of questions.

Dr. Iasonas Petras, Corwin Hall, Room 033

  • Research Areas: Information Based Complexity, Numerical Analysis, Quantum Computation.
  • Prerequisites: Reasonable mathematical maturity. In case of a project related to Quantum Computation a certain familiarity with quantum mechanics is required (related courses: ELE 396/PHY 208).
  • Possible research topics include:

1.   Quantum algorithms and circuits:

  • i. Design or simulation quantum circuits implementing quantum algorithms.
  • ii. Design of quantum algorithms solving continuous problems (such as Eigenvalue problems for Partial Differential Equations).

2.   Information Based Complexity:

  • i. Necessary and sufficient conditions for tractability of Linear and Linear Tensor Product Problems in various settings (for example worst case or average case). 
  • ii. Necessary and sufficient conditions for tractability of Linear and Linear Tensor Product Problems under new tractability and error criteria.

3. Topics in Scientific Computation:

  • i. Randomness, Pseudorandomness, MC and QMC methods and their applications (Finance, etc)

Prof. Benjamin Raphael, Room 309  

Research interests: Computational biology and bioinformatics; Cancer genomics; Algorithms and machine learning approaches for analysis of large-scale datasets

Fall 2017 IW Seminar - Computational Genomics
Research projects:

  • Implementation and application of algorithms to infer evolutionary processes in cancer
  •  Identifying correlations between combinations of genomic mutations in human and cancer genomes
  •  Design and implementation of algorithms for genome sequencing from new DNA sequencing technologies
  • Graph clustering and network anomaly detection, particularly using diffusion processes and methods from spectral graph theory

Prof. Jennifer RexfordRoom 222

  • Research areas: networking, software-defined networks, network management
  • Independent Research Topics:
    • Enterprise and data-center networking solutions built on Software Defined Networking (SDN).  For example, middleboxes like firewalls, NATs, intrusion detection systems, and load balancers, adaptive measurement of network traffic, networking in challenged environments (e.g., developing regions, emergency situations, etc.).
    • Research on better programming abstractions for SDN.  Projects could combine computer networking with other areas like programming languages, network optimization, algorithms, and distributed systems.
    • Any interesting project in computer networking.

Prof. Szymon Rusinkiewicz, Room 406

  • Research Areas: computer graphics; acquisition of 3D shape, reflectance, and appearance of real-world objects; novel methods for physical fabrication of objects with particular shape/appearance.
  • Independent Research Topics (updated fall, 2011):
    • Construct an efficient and easy-to-use 3-D scanning system for large collections of fragments of archaeological artifacts.
    • Investigate algorithms for computing and visualizing differences between ancient coins struck from similar, but slightly different, dies.
    • Develop a system combining body-mounted cameras and/or Kinect with tactile or auditory feedback to help blind people avoid obstacles.
    • Use computer-controlled milling machines to fabricate bas-reliefs, using substrates of heterogeneous materials.
    • Adapt a MakerBot or other hobbyist-grade manufacturing device to use multiple materials.
    • Implement (and perform the appropriate theoretical sampling/aliasing analysis for) a rendering system that explicitly accounts for the red/green/blue sub-pixels of LCD displays.
    • Other projects in computer graphics and vision, or technologies for documenting and studying cultural heritage objects.

Prof. Olga Russakovsky, Room 408

  • Research Areas: computer vision, machine learning, deep learning, crowdsourcing, fairness&bias in AI
  • Independent Research Topics (from AY 2017-2018):
    • Design a semantic segmentation deep learning model that can operate in a zero-shot setting (i.e., recognize and segment objects not seen during training)
    • Develop a deep learning classifier that is impervious to protected attributes (such as gender or race) that may be erroneously correlated with target classes
    • Build a computer vision system for the novel task of inferring what object (or part of an object) a human is referring to when pointing to a single pixel in the image. This includes both collecting an appropriate dataset using crowdsourcing on Amazon Mechanical Turk, creating a new deep learning formulation for this task, and running extensive analysis of both the data and the model

Prof. Robert Sedgewick, Room 319

  • Research Areas: Scientific analysis of algorithms, Analytic combinatorics
  • Independent Research Topics:
    • Professor Sedgewick is willing to advise any student who comes up with an idea for independent work from his books, papers, courses, or in his current areas of active research.  Send mail or stop by to discuss possible topics if you are interested.

Prof. Sebastian Seung, Princeton Neuroscience Institute - Room 153

  • Research Areas: computational neuroscience, connectomics, "deep learning" neural networks, social computing, crowdsourcing, citizen science
  • Independent Research Topics:
    • Gamification of neuroscience, e.g. EyeWire 
    • Hierarchical segmentation and object detection in biological images 
    • Crowdsourcing of computer science problems
    • Neural network theories of visual computation in the retina

Prof. Jaswinder Pal Singh, Room 324

  • Research Areas: Boundary of technology and business/applications; building and scaling technology companies with special focus at that boundary; parallel computing systems and applications: parallel and distributed applications and their implications for software and architectural design; system software and programming environments for multiprocessors.
  • Independent Research Topics:
    • Develop a startup company idea, and build a plan/prototype for it.
    • Explore tradeoffs at the boundary of technology/product and business/applications in a chosen area.
    • Study and develop methods to infer insights from data in different application areas, from science to search to finance to others. 
    • Design and implement a parallel application. Possible areas include graphics, compression, biology, among many others. Analyze performance bottlenecks using existing tools, and compare programming models/languages.
    • Design and implement a scalable distributed algorithm.

Prof. Mona Singh, Room 420

  • Research Areas: computational molecular biology, as well as its interface with machine learning and algorithms.
  • Independent Research Topics:
    • Whole and cross-genome methods for predicting protein function and protein-protein interactions.
    • Analysis and prediction of biological networks.
    • Computational methods for inferring specific aspects of protein structure from protein sequence data.
    • Any other interesting project in computational molecular biology.

Prof. Robert Tarjan, 194 Nassau St. Room 308

  • Research Areas: Data structures; graph algorithms; combinatorial optimization; computational complexity; computational geometry; parallel algorithms.
  • Independent Research Topics:
    • Implement one or more data structures or combinatorial algorithms to provide insight into their empirical behavior.
    • Design and/or analyze various data structures and combinatorial algorithms.

Prof. Olga Troyanskaya, Room 320

  • Research Areas: Bioinformatics; analysis of large-scale biological data sets (genomics, gene expression, proteomics, biological networks); algorithms for integration of data from multiple data sources; visualization of biological data; machine learning methods in bioinformatics.
  • Independent Research Topics:
    • Implement and evaluate one or more gene expression analysis algorithm.
    • Develop algorithms for assessment of performance of genomic analysis methods.
    • Develop, implement, and evaluate visualization tools for heterogeneous biological data.

Prof. David Walker, Room 211  On sabbatical during the 2019-2020 AY. 

  • Research Areas: Programming languages, type systems, compilers, domain-specific languages, software-defined networking and security
  • Independent Research Topics:  Any other interesting project that involves humanitarian hacking, functional programming, domain-specific programming languages, type systems, compilers, software-defined networking, fault tolerance, language-based security, theorem proving, logic or logical frameworks.

Dr. Kevin Wayne, Corwin Hall, Room 040

  • Research Areas: design, analysis, and implementation of algorithms; data structures; combinatorial optimization; graphs and networks.
  • Independent Research Topics:
    • Design and implement computer visualizations of algorithms or data structures.
    • Develop pedagogical tools or programming assignments for the computer science curriculum at Princeton and beyond.
    • Develop assessment infrastructure and assessments for MOOCs.

Asst. Prof. Matt Weinberg,  194 Nassau St. Room 222 

  • Research Areas: algorithms, algorithmic game theory, mechanism design, game theoretical problems in {Bitcoin, networking, healthcare}.
  • Independent Research Topics:
    • Theoretical questions related to COS 445 topics such as matching theory, voting theory, auction design, etc. 
    • Theoretical questions related to incentives in applications like Bitcoin, the Internet, health care, etc. In a little bit more detail: protocols for these systems are often designed assuming that users will follow them. But often, users will actually be strictly happier to deviate from the intended protocol. How should we reason about user behavior in these protocols? How should we design protocols in these settings?

Asst. Prof. Mark Zhandry, 194 Nassau St. Room 242

  • Research Areas: Cryptography, Privacy, Quantum Information and Computation
  • Independent Research Topics: Various topics in cryptography, privacy, and quantum computing
I am also looking for a student or students to help create a “Cryptography Zoo”, an analog of the “Complexity Zoo” (https://complexityzoo.uwaterloo.ca/Complexity_Zoo) for cryptographic concepts.  This would be a great resource for future researchers, documenting the various foundational results in cryptography.  
 
In more detail, the various concepts in cryptography (encryption, signatures, hash functions, etc) are nodes in a directed graph.  The edges in this graph are the various feasibility results (such as block ciphers can be used to build secret key encryption).  Various graph theory concepts, when applied to this graph, yield interesting insights for researchers.  For example, a path in the graph represents a chain of feasibility results.  So the path 
 
pseudorandom generator —> pseudorandom function—> block cipher 
 
demonstrates that pseudorandom generators can be used to build block ciphers.  Similarly, two concepts are in the same strongly connected component if and only if they are equivalent concepts.  
I am interested in documenting this graph, providing a central bibliography for the various cryptographic concepts.  In addition, I would like to provide users the ability to run simple graph algorithms on the graph.  For example, if the user wants to know if pseudorandom generators can be used to build block ciphers, they will simply enter the two concepts into the interface.  They will get the response “yes”, along with the path above.
 

Opportunities outside the department

We encourage students to look in to doing interdisciplinary computer science research and to work with professors in departments other than computer science.  However, every CS independent work project must have a strong computer science element (even if it has other scientific or artistic elements as well.)  To do a project with an advisor outside of computer science you must have permission of the department.  This can be accomplished by having a second co-advisor within the computer science department or by contacting the independent work supervisor about the project and having he or she sign the independent work proposal form.

Here is a list of professors outside the computer science department who are eager to work with computer science undergraduates.

 

Prof. Branko Glisic Room E330 - Engineering Quad

  • Research Areas: 
    • Documentation of historic structures
    • Cyber physical systems for structural health monitoring
  • Ideas for Independent Research Topics:
    • Developing virtual and augmented reality applications for documenting structures
    • Applying machine learning techniques to generate 3D models from 2D plans of buildings
  •  Contact: Rebecca Napolitano,

Prof. Sharad Malik, Engineering Quad, Room B224

  • Research Areas: 
    • Design of reliable hardware systems
    • Verifying complex software and hardware systems

Prof. Prateek Mittal, Engineering Quadrangle, Room B236

  • Research Areas: 
    • Internet security and privacy 
    • Social Networks
    • Privacy technologies, anonymous communication
    • Network Science
  • Ideas for Independent Research Topics:
    • Internet security and privacy: The insecurity of Internet protocols and services threatens the safety of our critical network infrastructure and billions of end users. How can we defend end users as well as our critical network infrastructure from attacks?
    • Trustworthy social systems: Online social networks (OSNs) such as Facebook, Google+, and Twitter have revolutionized the way our society communicates. How can we leverage social connections between users to design the next generation of communication systems?
    • Privacy Technologies: Privacy on the Internet is eroding rapidly, with businesses and governments mining sensitive user information. How can we protect the privacy of our online communications? The Tor project (https://www.torproject.org/) is a potential application of interest.

Prof. Ken Norman,  Psychology Dept, PNI 137

Potential research topics

  • Methods for decoding cognitive state information from neuroimaging data (fMRI and EEG) 
  • Neural network simulations of learning and memory

Caroline Savage, Office of Sustainability, Phone: (609) 258-7513, 

The Campus as Lab program supports students using the Princeton campus as a living laboratory to solve sustainability challenges. The Office of Sustainability has created a list of campus as lab research questions, filterable by discipline and topic, on its website.

An example from Computer Science could include using TigerEnergy, a platform which provides real-time data on campus energy generation and consumption, to study one of the many energy systems or buildings on campus. Three CS students used TigerEnergy to create a live energy heatmap of campus.

Other potential projects include:

  • Apply game theory to sustainability challenges
  • Develop a tool to help visualize interactions between complex campus systems, e.g. energy and water use, transportation and storm water runoff, purchasing and waste, etc.
  • How can we learn (in aggregate) about individuals’ waste, energy, transportation, and other behaviors without impinging on privacy?

Asst. Prof. Janet Vertesi, Sociology Dept, Wallace Hall 122 

  • Research areas: Sociology of technology; Human-computer interaction; Ubiquitous computing.
  • Possible projects: At the intersection of computer science and social science, my students have built mixed reality games, produced artistic and interactive installations, and studied mixed human-robot teams, among other projects.

Prof. David Wentzlaff, Engineering Quadrangle, Room 228

Computing, Operating Systems, Sustainable Computing.

  • Independent Research Topics:
  • Instrument Princeton's Green (HPCRC) data center
  • Investigate power utilization on an processor core implemented in an FPGA
  • Dismantle and document all of the components in modern electronics. Invent new ways to build computers that can be recycled easier.
  • Other topics in parallel computer architecture or operating systems
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