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Students share their work at the 2018 Princeton Research Day

Several students from Princeton’s Computer Science Department will participate in the annual Princeton Research Day, a celebration of the research and creative endeavors by our undergraduates, graduate students, postdoctoral researchers and other nonfaculty researchers. The event, which is free and open to the public, will be held from 10:30am to 5:00pm in Frist Campus Center on Thursday, May 10. No registration is required.

The campuswide event serves as an opportunity for researchers and artists to share their work with the community and includes research from the natural sciences, social sciences, engineering, the arts and humanities. The program features talks, posters, performances, art exhibitions, demonstrations, digital presentations and an awards ceremony for outstanding contributions. 

Those presenting posters include:

Cathy Chen '18
Context Learning in Artificial Neural Networks
Cathy's poster is about using artificial neural networks to learn the schematic structure of a world. "We investigate when and how networks succeed and fail on contextual learning tasks in a (simple) world defined through stochastically generated stories, and I received advice from Professor Ken Norman, Qihong Lu, Andre Beukers, and Chris Baldassano."  Room: Frist Main Atrium at 11:30am-1:00pm

Zachary Liu '18
Reconstruction of cancer evolution using time-series DNA sequencing data
Zachary will present a poster on his work developing an augmented reality app for recording and viewing annotations of structures using a mobile device, in collaboration with Princeton's Structural Health Monitoring Lab.  Room: Frist Main Atrium at 12:30am-2:00pm

Barak Nehoran '18
Separation of Quantum and Classical Communication Complexity  Room: Frist Main Atrium at 12:30am-2:00pm

Matthew Myers, Ph.D. candidate 
Mobile AR Software for Infrastructure Health & Performance Assessment  Room: Frist Main Atrium at 12:30am-2:00pm

Those giving 10-minute talks include:

Donghun Lee, Ph.D. candidate 
Learning to Learn: How to Get Learning Algorithms Work Better
Donghun will talk about active meta-learning for adaptive algorithms in Markov decision process setting. "Major application is intelligent bidding in sponsored search auctions such as Google Ad-click."  Room: Frist 208

Rebecca Elyanow, Ph.D. candidate 
Analyzing single-cell RNA-sequencing data in the presence of dropout events  Room: Frist 208
Rebecca will be giving a 10 minute talk about clustering single-cell RNA-sequencing data. 

Trisha Datta '19
Privacy-Preserving Traffic Obfuscation for Smart Home IoT Devices
Trisha will talk about her research on privacy and security in the Internet of Things. "In my work, I developed mechanisms that shape IoT device traffic to prevent user activity inference, and I made these mechanisms available to IoT device developers through a Python library."  Room: Frist 212

Michael Li '20
Applying the Knowledge Gradient Policy with Locally Quadratic Belief Model to Optimizing Energy Pricing Strategies
Michael will give a talk about applying a novel Bayesian optimization algorithm to optimizing pricing strategies of energy storage providers. "I'll also discuss my analysis of the performance and behavior of this algorithm across a variety of problem settings."  Room: Frist 309

Nora Williett, Ph.D. candidate 
Triggering Artwork Swaps for Live Animation
Nora will talk about triggering artwork changes during a live performance of a 2D animated character.  Room: Frist 329

Those giving 90-second "pitches" in include:

Grace Turner '18 
Applications for Natural Language Processing in Data Processing and Analytics  Room: Frist 309

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