Projects Day May 2, 2017
Biology / Computer Science / Mathematics Clinic
Dart NeuroScience, LLC
Creation and Analysis of Experiment Driven Biological Networks for Understanding Memory Processes
Liaisons: Philip Cheung ’96, Amir Fayyazuddin, Qingying Meng, Douglas Fenger
Advisors: Lisette de Pillis, Eliot Bush
Students: Loring Thomas (PM-S), Lisa Goeller, Ellen Seidel, Rohan Shankar (PM-F)
Dart Neuroscience (DNS) is a pharmaceutical company that focuses on developing treatments for memory disorders. The goal of the clinic project was to build biological networks based on DNS experimental data and to create accompanying network analysis tools. The networks and tools will help DNS better understand memory processes and find drug targets, with the goal of improving long term memory.
Computer Science Clinic
Hotel Recommendation System
Liaisons: Dawn Thomas, Di Xu
Advisor: Zachary Dodds
Students: Christine Chen (PM), Yacht Kitimoon, Alyssa Kubota, Jon Ueki
American Express and its partners seek to make travel planning easier, quicker, and more personalized. To that end, the objective of our clinic team was to explore and extend American Express’s current machine-learning based hotel recommendation algorithms with the goal of improving their performance.
Big Fish Games
Measuring User Engagement in Fairway Solitaire
Liaisons: Brad Bulkley, Chris Chatburn, Sam Prud’homme, Michael Tapley
Advisor: Colleen Lewis
Students: Justis Allen, Michael Diamond (PM), Adam Dunlap, Aaron Stringer-Usdan
Big Fish Games, Inc. develops the game Fairway Solitaire and cares deeply about the player experience. The goal of our project was to use machine learning on existing user data to better understand how player interaction with the game’s features affects player engagement. Better understanding what makes users engage with the game would allow Big Fish Games, Inc. to make more in-formed design decisions.
Using Latent Topics Models to Detect Rare Behaviors
Liaisons: Scott Zoldi, Joe Murray
Advisor: Robert Keller
Students: Savannah Baron, Sneha Deo (PM-S), Emily First (PM-F), Hope Yu
Our project’s goal was to investigate the detection of rare customer behaviors in transactional data using latent topic models, a form of unsupervised machine learning typically used to detect topics in examples of natural language. Our team has developed techniques to apply these models to time series data and has assessed their viability in the detection of anomalous behaviors.
Dynamic Website Updates
Liaisons: Heidi Gibson, Jacob Page, Dan Gwozdz
Advisor: Ben Wiedermann
Students: Keighley Overbay (PM-S), Maureen Naval (PM-F), Terrence Diaz, Linnea Nelson, Connie
GoDaddy provides small business owners with the tools they need to easily host and create their own personalized websites. The goal of our project is to extend GoDaddy’s website builder to allow small business owners to automatically display announcements on their websites at a predetermined time, as well as directly post these announcements to their social media accounts.
Serializing Chromium Tab State
Liaisons: Aaron Gable ’12, Chris Palmer
Advisor: Beth Trushkowsky
Students: Julien Chien (PM), Zoab Kapoor, Thomas Le, Yi Yang
Google’s Chrome browser, based on the open source project Chromium, is the most widely used browser in the world. The goal of our project was to research and implement strategies for serializing the full state of a tab in Chromium so that it can be suspended and restored with minimal user-visible disruption. Our team researched and implemented strategies for serializing and restoring tabs so that Chrome users would not lose information during memory-constrained situations.
International Business Machines Corporation (IBM)
Cognitive Note Taking
Liaisons: Maria Ebling ’88, John Vergo, Michael Tanenblatt
Advisor: Lisa Kaczmarczyk
Students: Scott Chow, Harry Cooke (PM), Wyatt Cooper, Julia Cosma, Emilia Reed
This project aims to develop a note-taking mobile application and service that acts as a personal cognitive assistant to help IBM employees extract company-specific information from their notes. The application accepts collections of documents (such as PDF files or images) and direct input to the application (such as text or handwriting). It utilizes IBM Watson cognitive services to analyze the documents and extract specific information about companies, which is then verified by the user.
Fast Detection of Problems in Scanned Documents
Liaisons: Tessa Adair ’14, Karl Chan ’89 P19, Carl Sykes
Advisors: Yekaterina Kharitonova, Melissa O’Neill
Students: Tiffany Sun (PM), Kharisma Calderon, Carmen Mejia, Andrew Scott
Laserfiche builds software that helps organizations digitize content and automate processes. To ensure that data from scanned paper documents can be accurately extracted, Laserfiche has tools to fix image quality problems such as skew and speckles. The goal of our project was to automatically and quickly detect problems in scanned documents. By detecting these problems, the software can reduce the time and processing required for image correction. Our team extracted features from a collection of scanned images and used machine learning classifiers to predict if a newly scanned document has problems.
Lawrence Livermore National Laboratory
High Performance Portability
Liaisons: Holger Jones, David Beckingsale, David Poliakoff
Advisor: Chris Stone
Students: Nick Gonzalez (PM-F), Aaron Lobb (PM-S), Dan Obermiller
Lawrence Livermore National Lab (LLNL) uses supercomputers to perform complex physics simulations. Maintaining parallel code is difficult when faster computers with different architectures are installed every few years. Portability layers can simplify this code by hiding details of computer architecture and parallelism. The goal of the clinic team was to improve RAJA, a portability layer created and used by LLNL. The team also com-pared RAJA to other portability layers with respect to usability and performance.
The MITRE Corporation
Liaisons: Sarah Doyle, Nick Orlans, Jay Doyle
Advisor: Lisa Kaczmarczyk
Students: Madi Pignetti (PM), Nava Dallal, Michael Sheely, Veronica Rivera
The MITRE Corporation is a not-for-profit re-search company that applies new technologies to problems in an array of areas. The goal of the MITRE clinic team’s project is to produce an algorithm that transforms an image to preserve apparent similarity to a human, but leads to a de-creased accuracy for a number of specified recognition algorithms. This algorithm makes it significantly more difficult for certain facial recognition algorithms to detect individuals, leading to in-creased security and privacy.
New Relic, Inc.
New Relic Churn Prediction & Prevention — Micro-Segmentation and Predictive Analytics
Liaisons: Kira Chuchom, Tarun Arora
Advisor: Ran Libeskind-Hadas
Students: Felis Perez, Rose Choi, William Chen (PM-S), Yiqing Cai (PM-F)
The goal of the New Relic Clinic project is to develop a data-driven approach to predicting potential churn. New Relic has collected substantial data. The types of data that has been collected have varied over time, leading to a heterogeneous dataset that is difficult to analyze. To address this issue, the New Relic Clinic project aims to first restructure the data to be consistent and then apply machine learning techniques to identify features capable of predicting churn.
Predicting Malicious URLs
Liaisons: Thomas Lynam, Mike Morris ’97
Advisor: Elizabeth Sweedyk
Students: Vidushi Ojha (PM), Aidan Cheng, Kevin Herrera, Carli Lessard
As part of their security solutions, Proofpoint provides a service to scan URLs embedded in clients’ emails, and determine whether they lead to sites containing malware. Suspicious URLs are redirected to a virtual environment, or sandbox, where they are tested for maliciousness. The goal of our project is to create a machine learning classifier which can better detect malicious URLs, so that fewer URLs need to be sandboxed. We investigated various models and features to create a number of options for such a classifier.
Detecting Evil Through Machine Learning
Advisor: Yi-Chieh Wu
Students: Jonathan Chang (PM-S), Rachel Lee, Anna Ma, Kent Shikama (PM-F), Lisa Yin
Reddit is an online discussion platform where users can form communities centered around a variety of topics. Like any discussion website, Reddit has experienced instances of spam, trolling, cyberbullying, and general aggressive behaviors from users, which can alienate other users or dis-courage people from joining Reddit. To help Reddit combat such behavior, we created an extensible machine learning pipeline for predicting whether a comment will be perceived as aggressive.
Real-Time Visualization and Machine Learning On Network Streams
Liaisons: Hal Lonas, Trung Tran
Advisor: Geoff Kuenning
Students: Nick Bailey (PM), Rohin Lohe, Jeff Milling, Norwood Square
Webroot specializes in cloud-based Internet security for consumers and businesses. The goal of our project was to perform real-time machine learning on local network streams and provide insight about anomalous and malicious behavior. Our team developed an infrastructure that uses ma-chine learning to capture and analyze network traffic and display information about it, offering clients a better understanding of malicious activity on their networks and a new way to protect against malware.
Computer Science/Engineering Clinic
ZAM Helmets, Inc.
Hockey Helmet Impact-Monitoring System
Liaison: Whitman Kwok ’97
Advisor: David Money Harris
Students: Lydia Scharff (TL-S), David Tenorio (TL-F), Erin McCarthy, Matthew Williams, Zunyan Wang
(S), Kim Joly (F)
ZAM Helmets Inc. is a startup creating better hockey helmets to reduce concussions among youth players. The ZAM clinic team is building an Internet of Things impact-monitoring system for use in these helmets. The system consists of an in-helmet impact sensor array, an iPhone app for displaying data about potential concussion risk, and cloud data storage for future analysis to aid concussion research.
The Aerospace Corporation
One TFLOP/s GPU on an Aerocube Picosatellite
Liaisons: Tim Smith ’05, Alex Utter ’05, Darren Rowen, Dr. Joseph Betser
Advisor: Brian Bryce
Students: Aaron Wang (TL-F), Men Cheol Jeong (TL-S), Lauren Hu (S), Alex Echeverria (S), Teresa
Despres (F), Nancy Wei (F), Nicholas Sakowski (F)
The Picosat program at The Aerospace Corporation designs, constructs, launches and operates small cube-like satellites for various mission concepts. The Aerospace Corporation clinic project is to build and demonstrate a picosatellite payload using the NVIDIA Jetson TX1 supercomputer-on-module. This payload will measure the functional ability of the Jetson TX1 in a low earth orbit radiation environment. Successful demonstration of the Jetson will raise the space readiness level of this cutting-edge technology and will enable exciting future mission capabilities.
Configurable Microphone Harness Array
Liaison: Ken Hild
Advisor: TJ Tsai
Students: Paul Slaats (TL-S), Samantha Hoang (TL-F), Rosh Lam, Eyassu Shimelis (S), Gabe Rubin
(F), Jonathan Kupfer (F)
Amazon Lab126 is a subsidiary of Amazon.com focused on development of consumer electronic products. The Amazon Lab126 Clinic team will design a configurable microphone-speaker system. It must fit into arbitrary product enclosures while supporting 16 location-adjustable microphones and computer interfacing for automated testing. The system will support stereo, mono, and 5.1-surround sound speaker outputs. This project will expedite the testing process for future prototypes in the Amazon Echo family of products with varying microphone and speaker configurations.
Create a Visual Production Scheduling System
Liaisons: Christopher Dinsley, Paul Rogers
Advisors: Patrick Little, Werner Zorman
Students: Shaan Gareeb (TL-S), Katherine Yoo, Jeong Shim (TL-F), Camille Croll (S), Anjaneya
Malpani (S), Lam Huynh (F), Marissa Lee (F), Angelica Virrueta (F)
Arconic’s Rancho Cucamonga facility produces aerospace parts in (Nickel, Titanium, Aluminum) and makes monthly shipments to companies across the globe. Arconic Rancho’s revenue growth is being constrained by forge capacity, which prompted Rancho to engage the Harvey Mudd clinic team to develop a production scheduling system that will assist the scheduler to optimize the forge units to increase efficiency and through-put, enabling future revenue growth.
RF Drones for Automated Signal Analysis
Liaisons: Terence Wu, Chuck Palaganas
Advisors: Albert Dato (S), Ruye Wang (F)
Students: Patrick McKeen (TL -S), Siyi Hu (TL-F), Jesse Joseph, Ramy Elminyawi (F), Austin Shin (S),
Charles Van Eijk (F)
The AT&T Clinic project is to develop a drone-based system to collect data on over-the-air digital television signals, particularly signal strength, clarity, and orientation across location and altitude. The system will include an operating procedure, easy-to-use operation and visualization software, drone selection, and onboard hardware, as well as the reasoning behind design choices and recommendations for future improvements.
Improving Ease and Efficiency of Blood Sample Manipulation for Flow Cytometry Verification
Liaisons: Christine Paulson ’02, Josh Zollett
Advisor: Gordon Krauss
Students: Lani Chapko (TL-F), Andrew Marino, Kelly McConnell, Ruth Sung (TL-S), Ramita Kondepudi
(S), Thomas Morgan-Witts (F)
BD Biosciences’ flow cytometers are crucial re-search and clinical instruments used in studying, diagnosing, and finding cures for today’s diseases such as HIV and leukemia. Harvey Mudd College has been enlisted to help BD Biosciences’ systems development team in making verification testing of their products more efficient. Our Clinic Team is focused on reducing the skill and tedious nature of whole blood specimen manipulation techniques, by providing tools to make these procedures easier, faster, and less error-prone.
City of Hope
Redesigning the Lighting and Optics for Laparoscopic Surgery
Liaisons: Dr. Kurt Melstrom, Dr. Yanghee Woo, Dr. Yuman Fong, Dr. Mustafa Raoof
Advisor: Qimin Yang
Students: Kathryn Jones (TL-S), Erica Martelly (TL-F), Leonardo Huerta, Richard Liu (F), Sean Nguyen
(F), Arthur Reyes (S), Robin Bendiak (S)
Minimally-invasive (laparoscopic) surgeries currently utilize a tethered, expensive system that relies on a single hot, limited-range incandescent light attached to a lone camera. This year the team focused on designing a set of cost-effective, self-sufficient systems using modern lighting and cam-era systems that will provide improved visibility for surgeons.
City of Hope
A Raman Spectrometer for in vivo Cancer Assessment
Liaisons: Dr. Veronica Jones, Dr. Yuman Fong, Dr. Dan Schmolze, Dr. Lily Lai, Dr. Bertrum Yuh
Advisor: Philip Cha
Students: Sarah Anderson (TL-S), Connor Stashko, (TL-F), Nathan Miller, Alex Echevarria, Willie
The City of Hope-Spectrometer clinic team is laying the groundwork for a Raman system to assess cancer margins in vivo and in real time. The final device will be placed into the breast, liver, or prostate and, upon recognition of cancer, ablate the malignant tissue. The team’s focus has been to collect and analyze spectra of human tissue to extract features that indicate if the tissue is malignant.
Dolby Laboratories, Inc
FPGA Implementation of HEVC Decoder
Liaison: Olivier Lambert
Advisor: David Money Harris
Students: Michael Reeve (TL-S), Achintaya Bansal, Bonny Chen, Joanna Ho (TL-F), Charlotte
The purpose of this project is to develop a proto-type implementation of an HEVC decoder in FPGA based on a Dolby’s internal “IMPACT” HEVC decoder implementation written in C-code for multi-core CPUs. The project will involve performance evaluation of the existing C-code to identify the most compute-intensive modules, and an RTL implementation of these modules.
Clear Fluid Detection on Media
Liaisons: Alyssa Siegman ’13, Aaron Rosen ’16, Stephen Bauer, Mark Choy
Advisor: Nancy Lape
Students: Lucia Kaye (TL-S), Tae Ha “Jeff” Park (TL-F), Michelle Niu, Ramonda Giddings, Jose
Orozco, Kana Hatori, (KU-S), Florence Walsh (F)
HP Inc is the worldwide leader of home, office, commercial, and industrial printing. The goal of the HP Clinic project is to detect clear fluids, which are crucial in providing durability and improving quality of printed products. By detecting the location and quantity of clear fluids in real time and in situ, the team will help reduce waste and provide more consistent printing quality.
Intuitive Surgical, Inc.
Providing Aerial Views During Minimally Invasive Surgery
Liaisons: Dr. Diana Friedman ’04, Dr. Andy Hazelton, Kayla Keifer Anderson
Advisor: Angie Lee ’05
Students: Faith Lemire-Baeten (TL-S), Sarah Nichols (TL-F), Daniel Rodriguez, Tyler Smallwood, Lupe
Carlos (S), Michelle Lanterma (S), Zachary Shattler (F)
The Intuitive Surgical, Inc. Team will design, build, and test a device that works with the da Vinci Surgical System to provide a wide angle view of the patient’s entire body cavity for surgeons and operating room staff during minimally invasive surgery to augment the close-up view provided by the existing endoscope. This project has three main parts: the camera, the lighting, and the casing containing both of the previous components. The main areas of work are in minimizing the device size and providing as much lighting as possible.
RF Propagation in Buildings
Liaison: Dave Neff ’79
Advisor: Nassibeh Hosseini
Students: Cherie Ho (TL-S), Marisa Kager (TL-W), Olivia Schneble (TL-F), Duncan Crowley (S),
Ragini Kothari (F), Patrick Scalise (F)
Microsoft Corporation builds many wireless devices, including the Surface tablet. These devices connect to a variety of wireless networks and often operate in an interior environment where building structures (e.g. walls, floors) interfere with signal propagation. The Microsoft Surface Clinic team is characterizing the impact of interior environments (e.g. hallways, walls, floors) on RF propagation at commonly used WiFi and cellular data bands. From their experiments, the team developed a revised model for predicting path loss in a variety of indoor environments.
Mission Rubber Company
Energy Monitoring System for Industrial Rubber Molding
Liaisons: Richard Getze, Luciana Ramirez, Jay Clark, Don Wrixon
Advisor: Matthew Spencer
Students: Mark Lozano (TL-S), Hannah Zosman (TL-F), Huting Lin, Fernando Salud, Viviana Bermudez
The Mission Rubber Company (MRC) clinic team designed an energy diagnostic and monitoring (EDM) system that measures, records, and graphically displays power used by industrial rubber presses. A prototype version of the EDM system was installed at the MRC manufacturing facility in Corona, whose annual energy use (10 GWh) could power nearly 1,000 homes. The EDM will be used to compare the operating power of different ma-chines, recognize power inefficiencies and quantify the effects of energy reduction programs.
MIT Lincoln Laboratory
Adaptive Wireless Sensing
Liaisons: Masato Kocberber ’10, Eric Storm ’15
Advisor: Philip Cha
Students: Sam Dietrich (TL-S), Orpheas Petroulas (TL-F), Jacob Nguyen, Enoch Yeo (S), Manu
Kondapi (S), James Palmer (F), David Kwan (F)
MIT Lincoln Laboratory is a federally funded research and development center and leader in wireless technology research. The MIT Lincoln Laboratory Clinic project is to design and proto-type a reconfigurable signal classification system with applications including intelligent Wi-Fi channel allocation. The team will research, develop, and characterize algorithms to discriminate be-tween several simultaneous RF emitters and deter-mine signal properties including carrier frequency and modulation type. Algorithms will be tested in simulation and on software-defined radios.
Motiv Power Systems
Heat Pump for Heavy Electric Vehicles
Liaisons: Jim Castelaz ’06, Edmond Kwok, Megan Peekema
Advisor: Anthony Bright
Students: Emily Beese (TL-S), Joshua Sealand (TL-F), Jacob Knego (S), Kamau Waller (S), Sean
Mahre (S), Kyla Scott (F), Bryce Murley (F), Jacey Coniff (F)
Motiv Power Systems is a provider of all-electric drivetrains for medium and heavy-duty vehicles. The goal of the Motiv clinic project is to design and test a new, more efficient thermal management system for Motiv’s electric powertrains that incorporates battery heating and cooling into the current cabin AC system. This would facilitate the use of cheaper, higher performance lithium ion batteries in their electric vehicles.
Niagara Bottling, LLC
Rotation Speed of Blow Molding Equipment
Liaisons: Alexander Mouschovias, Alberto Giron
Advisor: Hesam Moghaddam
Students: Ian Song (TL-S), Michael Chaffee (TL-F), Phuong Nguyen, Ryan Gibbs (S), Kristin Lie (S),
Jose Godinez (F), Kim Tran (F)
Niagara Bottling, LLC is the largest private bottled water manufacturer in the U.S. that is currently undergoing double digit annual growth. The HMC Niagara Blowmolding clinic project is to develop tools and processes to evaluate the electrical, mechanical, and thermal limitations of the blowmolding machines.
Secure State Estimation
Liaisons: Stephanie Tsuei, Ron P. Smith ’83, Ken Dreshfield ’80, Ian Jimenez ’11
Advisor: Christopher Clark
Students: Aishvarya Korde (TL-S), Paige Rinnert (TL-F), Robert Cyprus, Zayra Lobo (F), Austin Chun
(S), Jesus Villegas (S)
Autonomous vehicle control requires estimating vehicle states from on-board sensor readings. In the case that some of the sensors are compromised, the state of the vehicle may not be accurately estimated. The goal of this Clinic project is to implement a secure state estimator (SSE) in simulation and then validate it in hardware on a low-cost quadrotor. The team will demonstrate that the addition of the SSE to the control loop reduces the real-time tracking error of a quadrotor when using measurements from compromised onboard sensors.
New Form Factor and User Interface
Liaisons: Martin Kirk, Joseph Bright
Advisor: Elizabeth Orwin
Students: Benjamin Kunst (TL), Coco Coyle (TL), Owen Morrison (S), Justin Lauw (S), Wenkai Qin (S),
William Balliet (F), Christine Goins (F), Josephine Wong (F)
The 2016-17 Regenesis Biomedical Clinic project is to design, build, and test circuitry to generate radio frequency signals in four applicator pads for the next generation Provant Therapy System. The team will design a user interface to support this function and maintain EMC compliance.
Project Beluga: Trajectory-Tracking Controller for Autonomous Underwater Vehicles
Liaisons: Jerry Hsiung ’16, Ben Chasnov ’16, Cyrus Huang ’16, Yu Yang
Advisor: Anthony Bright
Students: Vaibhav Viswanathan (TL-S), Jessica de la Fuente (TL-W), Cherlyn Chan (TL-F), Kyle Lund,
Elijah Carbanaro (F), Jessica Lupanow (S), Chris Kotcherha (S)
The HMC Techmation Clinic team will modify and build a new version of the current Beluga AUV, develop an underwater trajectory-tracking controller and demonstrate the working controller on the Beluga 2.0 in field trials.
Energy Usage and Efficiency in a Fuel Cell Electric Semi-Trailer Truck
Liaison: Mr. Takehito Yokoo
Advisor: Okitsugu Furuya
Students: Elyse Pennington (TL–S), Cassie Burgess (TL–F), Daniel Nguyen, Aurora Leeson (S), Luis
Viornery (S), Lillian Liang (F), Sarah Silcox (F)
Toyota has long maintained that hydrogen fuel cell technology could be a zero emission solution across a broad spectrum of vehicle types. The scalability of this technology is enabling the automaker to explore a semi-trailer truck application for a California-based feasibility study. The Toyo-ta clinic project models energy usage and efficiency in the vehicle’s four main subsystems, with the goal of specifying vehicle component capacities.
Triple Ring Technologies
IoT Mobile Health Monitoring
Liaisons: Jen Keating, Dickshitha Thyagharajon
Advisor: Brian Bryce
Students: Deval Gupta (TL-S), Erin Paeng (TL-F), Senghor Joseph, Zane Bodenbender, Sarah Wang
Triple Ring Technologies (TRT) is an engineering consulting firm dedicated to bringing deep scientific knowledge to design of innovative medical technologies. The TRT Clinic project aims to develop a mobile health monitoring platform that can readily accommodate emerging medical sensor technologies. The platform includes data acquisition on a wearable device, data visualization and storage on an Android application, and a cloud interface. As a proof-of-concept, the platform is configured to measure heart rate via photoplethysmography.
United Launch Alliance
Improved Cryogenic Insulation System
Liaison: Tucker Gritton
Advisor: Gordon Krauss
Students: Rachel O’Neill (TL-S), Elizabeth Lee (TL-F), Michael Muzio, Bailey Meyer (S), Jasmine Yang
(S), Isabel King (F), Richard Ni (F)
United Launch Alliance is America’s ride to space and is interested in developing new technologies for space travel. The ULA clinic team seeks to identify and test potential materials for a cryogenic insulation system. The team will also create a model to predict heat transfer properties and thermal degradation of such a system.
Optimized Emergency Power Management Planning
Liaisons: Jerry Meek, Chris Wimmer
Advisors: Tanja Srebotnjak, Ruye Wang (F)
Students: Joseph Sinopoli (TL), Eric Mueller, Dan McCabe, Ahhyun Ahn, Andrea Vasquez (F)
Genentech is a biotechnology company researching and producing medicines for serious illnesses. Genentech is headquartered in South San Francis-co, CA and is vulnerable to power outages during earthquakes. The Genentech clinic team is tasked with developing a emergency power management plan. Using operations research techniques, generator refueling and shutdown schedules for each building are generated. Displayed within Genentech systems, the plan helps facilities protect price-less research, upkeep production, and prevent inventory spoilage.
Niagara Bottling, LLC
Capping Accuracy of Highspeed Lightweight Bottling Lines
Liaisons: Clemente Sanchez, Tony Peterson, Miles Moyers, Jim Brady, Damon Choate, Danny
Weckstein, Jim Utley, Alan Bunteman
Advisors: Kash Gokli, Talithia Williams
Students: Jonathan Lum (TL -S), Alexa Le (TL -F), Lakshay Akula, Zachary Friedlander, Michaela
Niagara Bottling, LLC is the largest family owned bottled water company in the United States, and is the largest producer of bottled water by volume. The Niagara Bottling – Capping clinic project is to understand the causes of bottle cap misapplication and reduce the misapplication frequency through conducting a Design of Experiments.
Sandia National Laboratories
Measuring the Permittivity of Ferroelectric Nanoparticles in an Epoxy Composite
Liaison: Todd Monson
Advisors: Richard Haskell, Albert Dato
Students: Marisol Beck (TL-S), Carmel Zhao (TL-F), Jonas Kaufman, Cesar Orellana, Robin Bendiak
(F), Isabel Martos-Repath (S)
Barium titanate (BTO) is a ferroelectric material commonly used in capacitors because of its high bulk dielectric constant, which may be even higher in nanoparticle form. The Sandia team is determining the dielectric constant of BTO nanoparticles as a function of particle size by measuring composites of BTO nanoparticles in epoxy. We are improving our composite fabrication procedure to reduce the agglomeration of BTO nanoparticles and using finite element analysis to extract the dielectric constant of the nanoparticles.
High Throughput Laser Diode Burn-in Systems
Liaisons: Dr. Bardia Pezeshki ’87, Christopher Stonier, Jacinto Dominguez, Dr. Dinh Ton, Dr. Mike
Jubber, Jay Kubicky, Derek Keir
Advisor: Matthew Spencer
Students: Jeewan Naik (TL-S), Emily Schooley (TL-F), Tommy Berrueta, Evan Kahn, Yashas Hegde
(S), Hamza Khan (F)
Kaiam Corp. is an industry leader in the field of optical communications for data centers, and rising demand has stretched its manufacturing capability. One manufacturing bottleneck is the diode burn-in process, which tests the micron scale laser diodes at high power and temperature. The Kaiam clinic project is to design a new burn-in system using micromechanical chips to make contact with the diodes and test them more quickly.
Document Mining and Analysis on Environmental Reports
Liaisons: Paul R. Schiffer, Richard White, Zach Fisk
Advisor: Weiqing Gu
Students: Vinh The Hoang (PM), Abram Sanderson, Annaliese Johnson, Matthew Bae, Johan Hoeger
The EDR clinic team was asked to work on a solution for EDR which would enable them to tag key pieces of information that appear in State and Federal Government environmental documents. As a major holder and distributor of environmental data, EDR desires to have a more effective method for finding desired information in these documents than their current methods allow. Since an environmental professional might be interested in multiple aspects of any given the document, the EDR team has explored classification and search techniques for both images and text in order to analyze and tag documents. The team’s work will be formatted as per EDR’s request, for adoption by EDR, and merging into their current systems.
Reverse-Engineering Power Flows on the Eastern Interconnect from Real-Time Price Data
Liaisons: Dr. Brian Maurizi, CMC ’03, Ross Sclafani, HMC ’08
Advisor: Weiqing Gu
Students: Rohan Nagpal, Ricky Pan, Michael Rees (PM), Jincheng Wang
Independent organizations called Independent System Operators are constantly calculating how to most efficiently meet the country’s demand for power. They communicate this information by publishing prices. Our team developed methods for using these prices to estimate power flows through large subsets of the U.S. power grid to better inform Saracen of the state of various lines. Knowledge of these flows will ultimately help Saracen, which trades in a market of buying and selling power, make better trading decisions.
Evaluation and Optimization of SoCalGas Routing Planning and Algorithms
Liaisons: Virginia Balbo, Ludivina Michel
Advisor: Susan Martonosi
Students: Stetson Bost (PM-S), Max Howard, Yichen Lu (PM-F), Noah Marcus
SoCalGas provides natural gas services to over 20 million residents of the Southern California region. Each day, SoCalGas must generate routes to service up to 14,000 individual customer orders. The SoCalGas Clinic team worked to improve the vehicle routing process and route quality through district design and parameter optimization.
HRL Laboratories, LLC
Automated Tuning of Electrostatically Defined Quantum Dots: Navigating Through High-Dimensional Potential Energy Landscapes
Liaisons: Matt Reed ’07, Mark Gyure, Emily Pritchett, Richard Ross
Advisor: Gregory Lyzenga
Students: Kathleen Kohl (TL-S), Amy Brown (TL-F), Brynn Arborico, Max Byers
HRL Laboratories is a cutting-edge physical science and engineering research laboratory. The HRL clinic project aims to create a computational model which navigates through the high-dimensional potential energy landscape of a triple quantum dot system in order to automate the process of placing one electron into each quantum dot. HRL is developing these quantum dot-based devices for eventual use in quantum information processing technologies.