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Projects in 2015–2016


Environmental Data Resources: Algorithms for Property Search and Identification

Advisor
Darryl Yong

EDR provides a range of products to allow property stakeholders to manage their assets and liabilities. Many of EDR’s products involve determining if two textual records refer to the same location. EDR would like to improve on the speed and accuracy of these comparisons through automated matching algorithms. Our team has developed a systematic approach to build and test matching algorithms grounded in probability and statistical learning theory.

Team

  • Michael Libucha. Ben Lowenstein
  • Sean O'Keeffe (Project Manager)
  • Bo Zhang

HRL Laboratories: Analysis of Quantum Communication Network Protocols

Advisor
Weiqing Gu

This project is looking at ways to generate random numbers via shared entanglement on a quantum network. The eventual goal is a distributed randomness beacon using our quantum protocol. We started by looking at networks of 4 and 8 node planar graphs. We analyzed possible malicious actions to investigate the effects an adversarial node can have on the network. We also consider other network topologies as possible candidates for this distributed randomness beacon.

Team

  • Yossathorn Tawabutr (fall) (Project Manager)
  • Wenhao Lu (spring) (Project Manager)
  • Kilian Fa
  • Reyna Hulett
  • Ben Johnson

Microsoft Corporation: Anomaly Detection for Live Site Incident Detection

Advisor
Rachel Levy

Bing is a Microsoft search engine that currently holds approximately 30% of the search engine market. It is critical for Bing to ensure that service remains fast and reliable. This year the Microsoft Math Clinic Team implemented efficient and accurate algorithms to detect anomalies in Bing live site data. The team also created a tool to determine optimal parameters for different algorithms.

Team

  • Angela Chin (Project Manager)
  • Lucy Gao
  • Sam Jun
  • Alison Kingman

NOAA Alaska Fisheries: Parameter Estimation on Marine Biological Models

Advisor
Alfonso Castro

Understanding how fish populations change over time helps the National Oceanic and Atmospheric Administration (NOAA) to prevent overfishing and protect fisheries. The Ecosim model describes the change in biomass per species over time for an entire marine ecosystem. The model itself leaves many parameters unspecified which must be inferred from the data. Our goal has been to algorithmically determine sets of parameters which allow the Ecosim model to best predict our data.

Team

  • Nathan Geldner (Project Manager)
  • Tasman Loustalet
  • Rowan Zellers

Pharmavite, LLC: Finite Scheduling

Advisor

The Pharmavite clinic team worked on creating and implementing a finite scheduling tool to generate an optimized work order schedule for the manufacturing processes of Pharmavite's San Fernando facility. The tool will reduce current costs and non-value added time by minimizing bottlenecks, creating visibility to capacity constraints, and optimizing other factors.

Team

  • Jessica de la Fuente (fall)
  • Kanak Singh (fall)
  • Aleina Wachtel (fall) (Project Manager)
  • Allison Barry (spring) (Project Manager)
  • Rachel O'Neill (spring)
  • Stephen Schein