Independent Work Seminar Offerings - Fall 2017
Title: COS IW 02 - Natural Language Processing
Instructor: Dr. Christiane Fellbaum
Meeting time: Friday 11:00 am - 12:20 pm
Abstract: Natural Language Processing, a sub-field of AI, tries to understand and model properties of human language and the ways it is learned, produced and interpreted by speakers. Participants in the seminar will choose from a wide range of topics including spelling correctors, sentiment and opinion analysis, argument detection, computational humor, question answering and automated reasoning, in English or another language of their choice. Using datasets constructed for specific projects from text corpora, news services, blogs, tweets, etc., you will apply (and possibly improve on) existing pre‐processing tools for word segmentation, part-of‐speech tagging and syntactic parsing. These “pipeline” steps rely on fundamental algorithms such as n-gram language modeling, naive Bayes classifiers and Hidden Markov Models. The focus will be on the analysis of explicit or implicit meaning in texts, on the word, sentence or document level. Symbolic and statistical approaches to semantic analysis, represented by the use of lexical resources such as Word Net and vector space models, respectively, will be explored. Projects may involve a supervised learning approach with data collected via Amazon Mechanical Turk.
Title: COS IW 03 - Computer Science Tools and Techniques for Digital Humanities
Instructor: Prof. Brian Kernighan
Meeting Time: Friday 11:00 am - 12:20 pm
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 is intrinsically 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 represent 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, encodings, APIs, data visualization, data cleaning, and user interface design for making the processes available to scholars just starting out in technology.
A typical project will begin with a humanities dataset (of which there are many) or a focus on a CS technique. In the former case, the goal will be to explore the data set to learn and present new and interesting things about the data. In the latter case, the goal will be to create or improve tools, languages, and interfaces to help scholars in the humanities.
Title: COS IW 04 - Help Future Computer Science Students Learn Computer Science!
Instructor: Dr. Robert Fish
Meeting Time: Tuesday 3:00 pm - 4:20 pm
Abstract: How would you like to have an IW project that could have lasting value for Princeton CS students? This seminar focuses on projects that try to enhance the computer science learning environment at Princeton. Recent years have seen a tremendous upsurge in both the interest and deployment of online learning platforms. Here at Princeton, some classes use a hybrid approach with online learning being supplemented and enhanced through classroom-based precepts and face-to-face one on one sessions. However, even with this method, some students struggle to keep up with the pace of these courses. To remedy this, there is some thought that people need training that combines a degree of self-pacing, as well as a variety of modes of learning.
In this seminar, students will choose some computer science concept from COS 126, 217, 226 or other Princeton Computer Science courses. You might pick some interesting concept which you think you can explain well to other students. Some examples might be 1) the dynamic operation of various gates and circuits in the TOY architecture or 2) visualizing function calls and the run-time stack frame for different functions (return types, parameters, optimizations on/off). For their projects, students will design and build an online learning experience that is targeted at this concept. It can include videos, graphic visualizations, quizzing mechanisms, or anything else that you can think of to help learn the concept. The project should also include a testing mechanism by which mastery of the concept may be assessed. A bonus would be utilizing the system to compare learning with it to a conventional approach.
Students may team up on these projects, creating a joint idea for a learning environment, with each student concentrating on some aspect of the software with a division of labor of frontend, backend, assessment, data analysis, etc. The learning and use of open source tools, including tools such as Open EdX, Django, and the D3 visualization library, etc. is encouraged in order that students may create the most effective online learning environments.
Some examples of past projects include an automated COS 226 quizzing system, visualizations of stack and heap data structures, and a user interface to improve student progress tracking.
Title: COS IW 05 - Invention and Innovation: Entrepreneurial Lessons for Computer Scientists
Instructor: Dr. Robert Fish
Meeting Time: Wednesday 3:00 pm - 4:20 pm
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 developing an independent project of your choice, introduces some of the elements of thinking and developing an idea into a going concern. Your project will include a software prototype, and a presentation, paper, and poster that captures 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, and the elements of an “pitch deck.” For the more adventurous, the possibility exists for you to share your idea in a real startup pitch event and report on the results.
Students may team 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 frontend, backend, mobile app, data analysis, 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. Also, if you’ve started a project with some entrepreneurial aspects in COS333, you might want to consider developing it further in this IW Seminar.
Title: COS IW 06 - Building Secure Decentralized Applications Using the Blockchain
Instructor: Prof. Michael Freedman
Meeting time: Monday 11:00 am - 12:20 pm
Abstract: The blockchain comprises a decentralized tamper-proof log of transactions. Today, it's primarily used for securing transactions of cryptocurrencies like Bitcoin at the scale of hundreds of thousands of daily transactions. Bitcoin can be used for online payments, real-world ATM withdrawals, even purchasing digital content from Microsoft or physical goods from Overstock.
But an emerging set of technologies like Blockstack are beginning to leverage the blockchain for other secure, decentralized applications: DNS without a centralized registrar, single-sign-on (SSO) without a trusted ID provider, social networks without a centralized service provider, and so forth. Fifteen years ago we had a flurry of peer-to-peer systems, but few survived or flourished. Today we have readily-available infrastructure and new decentralized security means via the blockchain: What's possible?
This seminar will introduce you to the technology behind Bitcoin, blockchains, and Blockstack, as well as various networking and systems protocols. Projects will involve building an application on top of the blockchain or using Blockstack.
Title: COS IW 07- Deep Learning
Instructor: Prof. Adam Finkelstein
Meeting time: Monday 9:30 am - 10:50 am
Abstract: Deep Learning is the fastest growing area of Machine Learning. This core technique has enabled the latest breakthroughs in computer vision, speech recognition, robotics, natural language processing, and artificial intelligence. It applies neural networks with many layers to large datasets in order to teach computers how to solve perceptual problems, such as detecting recognizable concepts in data, translating or understanding natural languages, interpreting information from input data, and more. Practical examples include vehicle, pedestrian and landmark identification for driver assistance; image recognition; speech recognition; natural language processing; neural machine translation and cancer detection. Major high tech companies such as Google, Facebook, Tesla, Microsoft, Intel, Yahoo, Baidu, Apple, Amazon, NVIDIA, Huawei, Qualcomm, NEC, and Toyota, invest significantly in the area. Students in the seminar will focus on either developing core components for deep learning algorithms, or applying deep learning algorithms to a target application.
Title: COS IW 08 - Random Apps of Kindness
Instructor: Dr. Alan Kaplan
Meeting time: Thursday 11:00 am - 12:20 pm
Abstract: Today there are more than 2.5 billion smartphone users globally, and by 2020, some estimates project over 6 billion smartphone subscriptions. This is an incredible number of mobile computers, each with mobile broadband connections, and a host of sensors, including cameras, GPS, accelerometers and barometers.
The overall goal of this IW seminar is to design, develop and experiment with mobile technology that can be used to help individuals or communities. The goal is not just to "write an app, " but rather to produce some innovative approach to a problem and demonstrate/evaluate its utility and benefits. Application areas include, but are not limited to: environment & climate, social activism, civic computing, healthcare, philanthropy and crowdsourcing. In general, IW projects must have an impact - locally, nationally or even globally. Some examples of past projects include: safe bike navigation, urban garden planning, drowsy driver detection and physical therapy exercise assessment.
All projects in this seminar will utilize Android as the core development platform. Students are highly encouraged to use and/or extend open source platforms. Projects may utilize any combination of Android devices, coupled with cloud-based backends (e.g., AWS), open APIs/data (many), hardware sensors (e.g., Raspberry Pi), augmented reality (e.g., Google Cardboard) and programmable UAVs.
Title: COS IW 09 - Computational Genomics
Instructor: Prof. Ben Raphael
Meeting Time: Friday 1:30 - 2:50 pm
Abstract: A genome contains the instructions for manufacturing many of the molecules within a cell. These instructions are spelled out using the 4-letter alphabet of ‘A’, ‘C’, ‘G’, and ‘T’ that comprise the nucleotides of DNA. In the past decade, our ability to measure, or sequence, a genome has increased dramatically with the cost of a sequencing a human genome approaching $1000. However, the interpretation of genome sequences is considerably more challenging, limiting our ability to derive new insights from the massive quantities of genomic data now being produced.
This seminar will explore the use of techniques from computer science to analyze, interpret, and compare genome sequences. Projects may be driven by a specific biological dataset (e.g. human genome variation, cancer genomes, etc.) or area of computer science (e.g. algorithms, machine learning, databases, visualization, etc.). Students may work individually or in small teams. Prior knowledge of basic biology is encouraged, but not required.
Title: COS IW 10 - Distributed Radio Sensing Across the Princeton Campus
Instructor: Asst. Prof. Kyle Jamieson
Meeting Time: Friday 1:30 pm - 2:50 pm
Abstract: In the past 15 years, software-defined radio (SDR) has arrived on the market, letting you build your own aircraft radar, conduct radio astronomy experiments on a shoestring, or even receive news and weather updates from geostationary satellites, from anywhere on the planet. But most of these radios are consigned to the laboratory, costing many thousands of dollars or more, and often impractical to transport. Recently, however, cheap and lightweight USB-based software-defined radios have become available for ca. $20 apiece, opening up the possibility of making the above sensing scenarios, and more, (a) crowd-sourceable and accessible to hackers and tinkerers, (b) distributed among many spatial vantage points, and (c) extremely portable and easy to deploy anywhere. This seminar is aimed at developing novel SDR sensing capabilities and/or extending existing sensing techniques to a distributed setting, where many SDRs cooperate to sense the same phenomenon, and aggregate their readings at a backend server, giving a more complete or higher-resolution picture of the world. You will use the RTL-SDR (http://rtl-sdr.com) platform---for which there is a rich open-source code ecosystem---and work in small groups to design and develop software for the above applications or a new application of their choosing. Deployment will be across the Princeton campus: in your dorm room, the Computer Science building, or elsewhere. Data cleaning, processing, and finally, visualization will then allow you to showcase the results of your sensing.
Title: COS IW 11 - Security and Privacy in the Internet of Things (IoT)
Instructor: Prof. Nick Feamster
Meeting Time: Monday 11:00 am -12:20 pm
Abstract: In the past several years, many of Internet-connected devices are not general-purpose computers, but rather a diversity of devices that have Internet connectivity. These devices, ranging from thermostats and camera to kitchen appliances to industrial control systems, are often referred to as the Internet of Things (IoT); it is very likely that the Internet will see many billions of these devices connected within just a few years. IoT devices promise significant innovation in smart homes and smart cities, but these new devices also carry significant privacy and security risks. For example, many of these devices ship with insecure software and fail to follow best practices concerning security and privacy. In many cases, the devices do not meet basic consumer expectations for privacy; these devices have also been used in large-scale denial of service attacks. In this independent work seminar, we will explore the state of security and privacy in IoT, from both technical and policy angles. Your project could involve installing a system or running an experiment in Princeton’s new Smart Home Lab on Prospect Street or developing a new piece of technology for improving privacy and security in smart homes. Expected audiences for your project may include both industry consortia working on IoT standards, government organizations such as law enforcement and consumer protection, and consumer advocacy groups.