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Princeton Research Day: 2021

Date and Time
Thursday, May 6, 2021 - 4:00pm to 5:30pm
Location
Online (off campus)
Type
Event

Graphic for Princeton Research Day with the event website at the bottem

Princeton Research Day is an exciting opportunity for Princeton researchers and scholars — from postdocs and non-tenured scholars to graduate students and undergraduates — to showcase their research and creative work for a broad audience. 

This year, PRD will be held entirely online. Presenters will create a 3-minute video and submit it March 31 - April 28. All videos will be displayed online and the top videos will appear at PRD Mainstage, an online celebration May 6 from 4 pm to 5:30 pm.

Visit researchday.princeton.edu to sign up to present your research or creative work, volunteer to be a judge, or attend PRD Mainstage on May 6. 

Forward Fest: Thinking Forward Bioengineering

Date and Time
Thursday, March 18, 2021 - 3:30pm to 4:45pm
Location
Webinar (off campus)
Type
Event

Forward Fest is a monthly online series that continues throughout A Year of Forward Thinking. The event features Princeton faculty and alumni exploring a range of forward-thinking topics. Sparking dialogue among the entire Princeton community — students, faculty, staff, alumni and other interested thinkers — Forward Fest explores, engages and develops bold thinking for the future.


Thinking Forward Bioengineering

At the intersection of engineering and the life sciences, bioengineers are on the forefront of many of the advances in research, education and innovation that will have a positive impact on health, medicine and quality of life. Faculty members involved in Princeton’s Bioengineering Initiative will discuss their groundbreaking interdisciplinary work and the open questions that they continue to think forward for the betterment of society. RSVP now to receive updates.

Forward Fest event graphic with an image from a microscope behind text that lists the date, time, and website.

Forward Fest - Data Science and Artificial Intelligence

Date and Time
Friday, November 20, 2020 - 8:00pm to 9:15pm
Location
Webinar (off campus)
Type
Event

As the pace of data creation and collection continues to accelerate, professors in a variety of disciplines talk about both the power and potential perils of artificial intelligence and what limitations and safeguards we need to take into account moving forward.

Join Matthew Salganik, Elad Hazan *06, and Mona Singh as they participate in the Forward Fest series discussion examining Data Science and Artificial Intelligence.  Brad Smith '81, President of Microsoft, will serve as moderator.

Forward Fest is a monthly online series that will continue throughout A Year of Forward Thinking. The events, featuring Princeton faculty and alumni exploring a range of forward-thinking topics, will be free and open to the public. Sparking dialogue among the entire Princeton community — students, faculty, staff, alumni and other interested thinkers — Forward Fest will explore, engage and develop bold thinking for the future.

Forward Fest is free and open to the public. RSVP now to receive updates and a resource guide, which includes must-know information about the featured speakers with links to their books, articles, podcasts and more!

Matthew Salganik


Matthew Salganik is a professor of sociology who has pioneered uses of data and digital technologies in social research. He was appointed interim director of Princeton University’s Center for Information Technology Policy on July 1, 2019, and then director of CITP for a two-year term beginning July 1, 2020.

Matt is affiliated with several other Princeton’s interdisciplinary research centers, including: the Office for Population Research, the Center for Health and Wellbeing, and the Center for Statistics and Machine Learning. His research interests include social networks and computational social science. He is the author of Bit by Bit: Social Research in the Digital Age.

Matt’s research has been published in journals such as Science, PNAS, Sociological Methodology, and Journal of the American Statistical Association. His papers have won the Outstanding Article Award from the Mathematical Sociology Section of the American Sociological Association and the Outstanding Statistical Application Award from the American Statistical Association. Popular accounts of his work have appeared in the New York Times, Wall Street Journal, Economist, and New Yorker. Salganik is currently on the Board of Directors of Mathematica Policy Research. His research has been funded by the National Science Foundation, National Institutes of Health, Joint United Nations Program for HIV/AIDS (UNAIDS), Russell Sage Foundation, Alfred P. Sloan Foundation, Facebook, and Google. During sabbaticals from Princeton, he has been a Visiting Professor at Cornell Tech and a Senior Researcher at Microsoft Research. During the 2018-19 academic year, he was a professor in residence at the New York Times.


Mona Singh
Mona Singh is a professor of computer science and the Lewis Sigler Institute for Integrative Genomics. She has been on the faculty at Princeton University since 1999.   She received her A.B. and S.M degrees from Harvard University, and her Ph.D.  from MIT, all three in computer science.  She works broadly in computational molecular biology, as well as its interface with machine learning and algorithms.  Much of her work is on developing algorithms to decode genomes at the level of proteins and she is especially interested in developing data-driven methods for predicting and characterizing protein sequences, functions, interactions and networks, both in healthy and disease contexts.  Among her awards are the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2001, and the Rheinstein Junior Faculty Award from Princeton’s School of Engineering and Applied Science in 2003. She was named a Fellow of the ACM in 2019, and of the ISCB in 2018.

Working at the intersection of data science and molecular biology, Singh develops algorithms to decode genomes at the level of proteins. She has pioneered interdisciplinary courses in the field of bioinformatics, the method by which computers are used to synthesize vast quantities of raw biological data. Her recent work has identified genes and mutations that play a role in cancer development, an important first step to guiding new treatments.


Elad Hazan
Elad Hazan is a professor of computer science at Princeton university. His research focuses on the design and analysis of algorithms for basic problems in machine learning and optimization. Amongst his contributions are the co-development of the AdaGrad algorithm for training learning machines, and the first sublinear-time algorithms for convex optimization. He is the recipient of the Bell Labs prize, (twice) the IBM Goldberg best paper award in 2012 and 2008, a European Research Council grant, a Marie Curie fellowship and Google Research Award (twice). He served on the steering committee of the Association for Computational Learning and has been program chair for COLT 2015. In 2017 he co-founded In8 inc. focusing on efficient optimization and control, acquired by Google in 2018. He is the co-founder and director of Google AI Princeton.

Hazan and his team of computer scientists at Google AI Princeton research the automation of the learning mechanism and its efficient algorithmic implementation. In other words, they are developing advanced artificial intelligence where machines can learn quicker — and even teach themselves. Such AI will determine the future of technology, including self-driving automobiles, delivery drones and speech recognition software.


More info on this event can be found here.

Class Day 2019

Date and Time
Monday, June 3, 2019 - 1:30pm to 3:00pm
Location
Friend Center Courtyard
Type
Event

The Chair and the Faculty of the Department of Computer Science
invite all graduating seniors to attend... 

Class Day 2019
Departmental Award Ceremony

Monday, June 3, 2019

Join us as we gather at 1:30 pm, Ceremony will begin at 2:00 pm 
under the tent in the Friend Center Courtyard.
Immediately following, there will be SEAS Reception in the Friend Lobby at 3:00 pm
Presentation of SEAS Awards
Friend Courtyard 3:15 pm.

Unsolved Data Problems

Date and Time
Wednesday, March 13, 2019 - 4:30pm to 5:30pm
Location
Computer Science Small Auditorium (Room 105)
Type
Event
Host
Center for Digital Humanities, Department of Computer Science, and the Center for Statistics and Machine Learning

Robot arms playing a keyboard.
Unsolved Data Problems will introduce faculty and students in the computer and data sciences to the untapped research possibilities inherent in humanities data. A panel of Princeton faculty - Meredith Martin (English), Marina Rustow (History and Near Eastern Studies) and Dan Trueman (Music) - will discuss some of Princeton’s landmark digital humanities projects, and the challenges they’ve faced when transforming historical, multilingual and experimental source material into data and code.

Projects discussed include the Princeton Prosody Archive, the Princeton Geniza Lab, and bitKlavier. Jennifer Rexford and Brian Kernighan (Computer Science) will moderate the panel.

Help discover innovative algorithmic solutions to these unsolved computational problems. This panel will be of particular interest to researchers working in the fields of: computer vision, natural language processing, machine learning, and audio/music engineering.

This event is collaboratively organized by the Center for Digital Humanities,  the Department of Computer Science and the Center for Statistics and Machine Learning

Hack Princeton Fall 2018

Date and Time
Friday, November 9, 2018 - 5:00pm to Sunday, November 11, 2018 - 3:00pm
Location
Computer Science Small Auditorium (Room 105)
Type
Event

Twice a year, HackPrinceton welcomes 600 developers and designers from across the country to create incredible software and hardware projects. For 36 hours this fall, from November 9th to 11th, we will provide a warm and collaborative environment for you to build out brilliant, innovative, and impactful ideas.

At HackPrinceton, you'll meet fellow hackers, learn new technologies, and work alongside seasoned mentors. We'll have free food, swag, workshops, lecture series, mentorship, prizes, game, free food, and more. Don't have a team, or even an idea? Don't worry! We'll give you the tools to build something incredible.

Whether you’re new to coding/design/hardware or a seasoned hacker, you have a place at HackPrinceton. All we expect is a passion for learning, a willingness to collaborate with people of different backgrounds, and a desire to benefit the world with technology. We'd love to see you here!

Register here!

Data Science: A View to the Future

Date and Time
Saturday, October 6, 2018 - 9:00am to 10:15am
Location
Friend Center 101
Type
Event

Data Science: A View to the Future

Moderator:
Jennifer Rexford ’91, Gordon Y.S. Wu Professor of Engineering, Professor of Computer Science and Computer Science Department Chair

Panelists:
Jennifer Chayes *83, Technical Fellow and Managing Director of Microsoft Research-New England,  Microsoft Research-NYC, and Microsoft Research-Montreal
Patricia Falcone ’74, Deputy Director, Science and Technology at Lawrence Livermore National Laboratory
Courtney Monk ’01, Manager, Data Science, Chegg, Inc

Program Opening By:
Cathy Chute ’81, Executive Director, Institute for Applied Computational Science; Assistant Dean for Professional Programs, Harvard Paulson School of Engineering and Applied Sciences

This panel is part of She Roars: Celebrating Women at Princeton

Celebrate Princeton Innovation

Date and Time
Thursday, November 8, 2018 - 5:00pm to 8:00pm
Location
Frick Chemistry Building 124
Type
Event

Each year, our research community comes together with friends in the innovation and entrepreneurship ecosystem to celebrate the impacts of University technologies on everyday lives.

Our annual reception honors faculty researchers, postdoctoral researchers, graduate students and undergraduates who are making a difference through their discoveries and entrepreneurial spirit. 

Register here.

Can machine learning trump theory in communication system design?

Date and Time
Friday, August 17, 2018 - 11:30am to 1:30pm
Location
Engineering Quadrangle B205
Type
Event
Host
Prof. H. Vincent Poor & Prof. Yuxin Chen, Electrical Engineering

Abstract:
Design and analysis of communication systems have traditionally relied on mathematical and statistical channel models that describe how a signal is corrupted during transmission. In particular, communication techniques such as modulation, coding and detection that mitigate performance degradation due to channel impairments are based on such channel models and, in some cases, instantaneous channel state information about the model. However, there are propagation environments where this approach does not work well because the underlying physical channel is too complicated, poorly understood, or rapidly time-varying. In these scenarios we propose a completely new approach to communication system design based on machine learning (ML). In this approach, the design of a particular component of the communication system (e.g. the coding strategy or the detection algorithm) utilizes tools from ML to learn and refine the design directly from training data. The training data that is used in this ML approach can be generated through models, simulations, or field measurements. We present results for three communication design problems where the ML approach results in better performance than current state-of-the-art techniques: signal detection without accurate channel state information, signal detection without a mathematical channel model, and joint source-channel coding of text. Broader application of ML to communication system design in general and to millimeter wave and molecular communication systems in particular is also discussed.

Bio:
Andrea Goldsmith is the Stephen Harris professor in the School of Engineering and a professor of Electrical Engineering at Stanford University. She also serves on Stanford’s Presidential Advisory Board, University Budget Group, and Faculty Senate. She previously served as Chair of Stanford’s Faculty Senate and as a member of Stanford’s Commission on Graduate Education, Commission on Undergraduate Education, Committee on Research, Planning and Policy Board, and Task Force on Women and Leadership. She co-founded and served as Chief Technical Officer of Plume WiFi (formerly Accelera, Inc.) and of Quantenna (QTNA), Inc. She has also held industry positions at Maxim Technologies, Memorylink Corporation, and AT&T Bell Laboratories, and she currently chairs the Technical Advisory Boards of Interdigital Corp., Quantenna Communications, Cohere Communications, and Sequans. In the IEEE Dr. Goldsmith served on the Board of Governors for both the Information Theory and Communications societies. She has also been a Distinguished Lecturer for both societies, served as President of the IEEE Information Theory Society in 2009, founded and chaired the student committee of the IEEE Information Theory society, and chaired the Emerging Technology Committee of the IEEE Communications Society. She currently chairs the IEEE TAB committee on diversity and inclusion, and the Women in Technology Leadership Roundtable working group on metrics.

Dr. Goldsmith is a member of the National Academy of Engineering and the American Academy of Arts and Sciences, a Fellow of the IEEE and of Stanford, and has received several awards for her work, including the IEEE ComSoc Edwin H. Armstrong Achievement Award as well as Technical Achievement Awards in Communications Theory and in Wireless Communications, the National Academy of Engineering Gilbreth Lecture Award, the IEEE ComSoc and Information Theory Society Joint Paper Award, the IEEE ComSoc Best Tutorial Paper Award, the Alfred P. Sloan Fellowship, the WICE Technical Achievement Award, and the Silicon Valley/San Jose Business Journal’s Women of Influence Award. She is author of the book ``Wireless Communications'' and co-author of the books ``MIMO Wireless Communications'' and “Principles of Cognitive Radio,” all published by Cambridge University Press, as well as an inventor on 28 patents. Her research interests are in information theory and communication theory, and their application to wireless communications and related fields. She received the B.S., M.S. and Ph.D. degrees in Electrical Engineering from U.C. Berkeley.

Data: The New Killer Application and How Data Is Driving Exciting New Applications Across IoT and Beyond

Date and Time
Saturday, June 2, 2018 - 8:45am to 10:00am
Location
McCormick Hall 101
Type
Event

Alumni-Faculty Forum
Data: The New Killer Application and How Data Is Driving Exciting New Applications Across IoT and Beyond

Moderator: 
-Jennifer Rexford '91, Gordon Y.S. Wu Professor in Engineering, Professor of Computer Science and Chair, Department of Computer Science
Panelists:
-James Shepard ’78, Founder and Managing Partner, GenNx360 Capital Partners
-Angela T. Tucci ’88, CEO, Apto, Inc.
-Jean Hsu ’08, Co-Founder, Co Leadership
-Michael S. Wang ’08, Co-Founder & CEO, SIRL

This event is part of Princeton University's Reunion 2018 celebration

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