2018 Symposium

Sponsors

  1. Amazon Robotics
  2. Bulger Partners

Judges

  1. Rob Gurwitz, Former CTO and SVP of Technology & Architecture, Bulger Partners
  2. Robert W. Martin, Web Development Manager & Accessibility Lead, State of Rhode Island Department of Administration
  3. Ugur Cetintemel, Professor and Department Chair, Brown University Computer Science
  4. James Tompkin, Assistant Professor, Brown University Computer Science

Entrants

  1. ReNeg for Behaviorally Cloning Autonomous Vehicles – by Jacob Beck
    We propose a method allows for better and faster autonomous vehicle learning: regression with the full range of positive AND negative behavior.

  2. Increasing Retention Rates of Undergraduates in STEM – by Victoria Chávez
    This research investigates and addresses the disproportionate underrepresentation of minorities in STEM concentrations and suggests different actionable steps that can be taken at various levels of the university.

  3. STOP (Stackelberg Trained Optimal Policies) Car Bullying – by Matt Cooper
    We employ an adaptive policy computed from the Stackelberg Equilibrium of a two-player game that enables autonomous cars to safely assert themselves in scenarios requiring social negotiation with a human driver.

  4.  Improving Shape Deformation in Unsupervised Image-to-Image Translation – by Aaron Gokaslan
    We develop a network that morphs objects in the image to the required domain with minimal background and scene feature distortion.

  5. Criteria Sliders Web – by Mae Heitmann
    Criteria Sliders organizes images based on arbitrary ranking criteria from the user in a useful way.

  6.  ShareAid: The Personalized Photo Sharing Assistant – by Philip Hinch
    ShareAid investigates if a machine can automatically learn and imitate the photo-sharing process by learning on a user’s previous social media behavior.

  7. Inferring the Intentions of Learning Agents – by Vince Kubala
    This work addresses the problem of inferring the goals of an intelligent agent who is learning in a known way. It generalizes the standard inverse reinforcement learning problem by assuming instead that the agent may learn in a known way and makes decisions in a known, albeit not necessarily optimal, way.

  8.  Dash – by Luke Murray
    Dash’s vision is to be a context-aware, note taking application for individuals and small workgroups that facilitates summarizing and digesting information through a streamlined yet highly customizable UI.

  9.  MS Lesion Segmentation with Cascaded 3D Convolutional Neural Network – by Charles Njoroge
    I present a reimplementation of automated multiple sclerosis lesion segmentation with a cascaded 3d convolutional neural network which utilizes a cascaded 3d convolutional neural network to effectively segment the MICCAI2008 public dataset.

  10.  Deep Abstract Q-Networks – by Melrose Roderick
    We examine the problem of learning/planning on high-dimensional reinforcement learning domains with long horizons & sparse rewards.

  11.  Virtual Reality Teleoperation Task Feasibility – by Eric Rosen
    This work poses the question of what robot tasks are feasible under a commercially VR teleoperation system like ROS Reality.

  12.  Driving as Fast as Possible: End to End Learning Obstacle Detection and Avoidance – by Josh Roy
    In this project, we hope to evaluate the performance of an end-to-end neural network to perform this avoidance and navigation using a small, two-wheeled, robot which the neural network will learn to control.

  13.  Applying Rademacher-Like Bounds to Combinatorial Samples and Function Selection – by Clayton Sanford
    We applied our framework (a variant of the Rademacher Complexity) and Rademacher complexity to incorporate bounds into learning algorithms in the audio domain.

  14.  ProSecCo: Progressive Sequence Mining with Convergence Guarantees – by Sacha Servan-Schreiber
    This work extends existing data mining techniques into a progressive algorithm that keeps interactivity by outputting incremental results very frequently.

  15.  Rewind: Automatically Generated Location-based Videos for Revisiting Personal Memories  – by Neilly Tan
    Rewind is a system that automatically recreates a digital memory of a past trip by taking historical geolocation data and generating a stitched-together cinematic-style video made of streetside images from where a user has been.

  16.  An Optical MIDI Interpreter for Acoustic Guitar – by Sam Title
    The optical pickup explored in this paper was a viable design that can serve as an alternative to hexaphonic guitar pickups for detecting note events.

  17.  DBPal: An End-to-end Neural Natural Language Interface for Databases – by Nathaniel Weir
    DBPal is an intelligent system that makes databases more accessible and expressive requiring extensive background knowledge.

  18. SleepCoacher 2.0: A Personalized Automated Self-Experimentation System for Sleep Recommendations – by Jina Yoon
    SleepCoacher is an Android app that helps people figure out how to achieve sleep perfection by coaching them through sleep "experiments" and analyzing their data.