Project Title: Mitigating Inefficient Resource Deployment in the Houston Fire Department
Team Members: Lu Huang, Phillip Jaffe, Nicole Jaiyesimi, Keming Li
This project is working to assist the Houston Fire Department in effectively and efficiently serving the millions of Houstonians under their jurisdiction. To achieve this, the group has worked to identify and quantify dispatch protocols that are suboptimal and provide recommendations for improvement.
Sponsors/Mentors: HFD: Leonard Chan, Assistant Chief Ruy Lozano, Assistant Chief Justin Wells, Assistant Chief Rodney West, Geiby George, Station 28 and Rice: Daniel LeJeune, Cara Tan, Dr. Tasos Kyrillidis
Project Title: Cross-Community Comparison of Fire and Emergency Medical Services
Team Members: Ajith Kumar, Armin Khamoshi, Celeste Biltz, Viginesh Muraliraman
Clustering analysis of fire departments in order to determine appropriate cohort groups for performance comparison.
Sponsors/Mentors: Intterra: Brian Collins, Rice: Daniel Bourgeois, Santiago Segarra, Jack Wang
Project Title: A data-driven approach to well failure identification
Team Members: Camille Little, Ed Hong, Jiachen Ni, Qian Chen, Zhihan Lu
How can Natural Language Processing be used to prevent drilling catastrophes? We are trying to identify well failure events in drilling reports that may cause the next great oil spill with the power of data science.
Sponsors/Mentors: Shell: Silvio Baldino, Rice: Jack Wang, Daniel LeJeune
Project Title: A Data-Driven Framework for Pediatric Cardiac Arrhythmia Detection
Team Members: Hossein Babaei, Yanwan Dai, Ahmed Humayun, Mario Paciuc, & McKell Stauffer
Our team works to detect specific arrythmias in pedriatric patients using various waveforms.
Sponsors/Mentors: Texas Children's Hospital: Parag Jain, Raajen Patel, Craig Rusin; Rice: Meng Li, Souptik Barua and Xincheng Tan
Project Title: A Novel Method for Discovering Relationships Between Futures
Team Members: Hasnain Ali, Jake Flores, Stefano Romano, Jessica Wang
We explore relationships between futures and market structure dynamics using an innovative statistical approach for financial data.
Sponsors/Mentors: Belvedere Trading: Andrew Wendorff; Rice: Daniel Kowal (Professor of Statistics), Daniel Bourgeois (D2K Fellow), Souptik Barua (D2K Fellow)
Project Title: Optimizing the Spatial Placement of Emergency Vehicles for the Houston Fire Department
Team Members: Shannon Chen, Erin Kreus, Jesse Pan, Ashwin Varma, and Lynn Zhu
The project aims to determine optimal placement and allocation of HFD vehicles to stations in order to minimize response times and maximize appropriate response proportions.
Sponsors/Mentors: Leonard Chan (HFD), Assistant Chief Ruy Lozano (HFD), and Dr. Tasos Kyrillidis (Rice)
Project Title: Beating Expectations: Predicting Market Movements Using Historical Data
Team Members: Tara Bian, Santi Tellez, Arjoon Srikanth
To predict where Belvedere's expectations will be with respect to actual market movements and to discover the factors which cause markets to move differently than Belvedere's calculations.
Sponsors/Mentors: Dr. Andrew Wendorff (Belvedere Trading); Dr. Dan Kowal (Rice)
Project Title: Data Driven Drilling Dysfunction Detection
Team Members: Alex Jiang, Wei Wu, Joyce Jiang, Ying Xiong, Erin Song
Our project is focused on providing a visualization tool to analyze correlations in historical data and using this to further detect trending deviation.
Sponsors/Mentors: Dr. Yu Liu (Shell), Dr. Yingyan Lin (Rice)
Project Title: A Data Science Approach to Detect Fraudulent Online Payments
Team Members: Cara Tan, Han Shi, Whitney Li, Yifei Hu, Zach Neuberg
Our project uses statistical and machine learning models to detect and determine what signifies fraudulent B2B (business to business) transactions.
Sponsors/Mentors: Bryan Wang, Sangam Singh, Vinay Pai, Rob Lam, Kartik Khanna (Bill.com), Dr. Anshumali Shrivastava (Rice)
Project Title: Spatial Mapping of Fly Brain Gene Expression
Team Members: Stephanie Yang, Makoto Jankovsky, Vicram Rajagopalan, Qituo Ding, Alivia Wu
We combine gene expression data and gene spatial imaging data in order to identify the spatial location of different cell types. By mapping genes or cell types to a known brain location, we are able to link them to neurological functions in that area, aiding in the study of neurological disorders and behavior.
Sponsors/Mentors: Dr. Zhandong Liu, Chaohao Gu (Baylor College of Medicine), Dr. Genevera Allen (Rice)
Project Title: Gone with the Wind? - Impact of Meteorology on Air Pollution in Houston
Team Members: Manuel Croitoru, Jenny Kwon, Yan Li, Hongyu Mao
Our project strives to better understand the spatial and temporal patterns of ground-level ozone and PM concentrations in the greater Houston area with its meteorology.
Sponsors/Mentors: Dr. Daniel Cohan, Dr. Pedram Hassanzadeh, Daniel Bourgeois (Rice)
Project Title: Unraveling an Engine: Quantifying the effects of fuel additives in Diesel engines
Team Members: Donaldo Almazan, Eduardo Berg, Samantha Gilmore, Sunny Yu, Swapnav Deka
Fuel additives are essential to enhancing the quality and efficiency of fuels used in motor vehicles. In this project, we seek to develop an effective predictive model to utilize during engine testing research. Specifically, we are highlighting the effects of Shell fuel additive NEMO2015 on engine power output.
Sponsors/Mentors: Dr. Detlef Hohl, Dr. Jennifer Kensler, Alastair Smith (Shell Oil Company), Dr. Santiago Segarra (Rice)
Project Title: Preventing Foodborne Illness at Houston Area Restaurants
Team Members: Wendy Feng, Carolina Hatanpää, Charlsea Lamb, Alvin Sheng, and Ouyang Zhu
Our project uses food establishment inspection report data from the City of Houston to help Houston Health Department (HHD) officials determine where to target restaurant inspections and food safety training. This will better allow HHD to prevent foodborne illness outbreaks.
Sponsors/Mentors: Dr. Loren Raun. Naomi Macias, and Conrad Janus (City of Houston Health Department), Dr. Kathy Ensor (Rice)
Project Title: Houston 311 Quality Improvement: An Analysis of Citizen Satisfaction and Engagement
Team Members: Akin Bruce, Ben Herndon-Miller, Soo Bin Park, Ben Rieden, Emily Rychener
The goal of this project is to analyze 311 customer survey responses and gain insights into what drives positive and negative responses from the community. We use a combination of traditional statistical methods and machine-learning techniques to help the city of Houston optimize their operational models.
Sponsor / Mentors: Steven David (City of Houston), Dr. Meng Li (Rice)
Project Title: Predicting Realized Variance in the S&P500
Team Members: Santiago Tellez, Oliver Jin, Jessica Yuan, Wei Wu, Ruimeng Xu
By using minute-level data of the S&P500 over a three and a half year time frame, we will predict the variance in the market to better price options.
Sponsors/Mentors: Dr. Andrew Wendorff (Belvedere Trading); Dr. Dan Kowal (Rice)
Project Title: Primary Visual Tuning for Movements in Mice
Team Members: Kevin Li, Tengjiao Liu, Xincheng Tan, Yuchong Zhang, Yuyan Liu
Neuron Tuners team has been exploring how the movements of a mouse correlate with its brain activities in the visual area. We are interested in how much of the movement-related information is encoded in the primary visual cortex.
Sponsor / Mentors: Dr. Jacob Reimer (Baylor College of Medicine), Dr. Genevera Allen, Tianyi Yao, Andersen Chang (Rice)
Project Title: Searching for Auditory Responses in the Visual Cortex
Team Members: Aziza Salako, Rui Qin, Sadie Richardson, Elliott Smith, Kenneth Li
As a Data Science Projects team, our overarching goal for the semester is to process the ambient noise recordings, detect acoustic features like mouse calls, human voices, and other noises, and identify neurons in the visual cortex that respond to these auditory cues.
Sponsor / Mentors: Dr. Jacob Reimer (Baylor College of Medicine), Dr. Genevera Allen (Rice)
Project Title: Validation of Urban Parks in Houston as a Flood Mitigation Tool
Team Members: Adam Strathman and JeongSu Park
An interdisciplinary team of statisticians, civil engineers, and architects have been assigned the task of promoting and implementing urban parks as a way to mitigate the damages of future flood events. As data scientists, we will work with parcel-level appraisal data gathered by Harris County Appraisal District and a dataset of elevation certificates of residential parcels within Brays Bayou to map and quantify the benefits of urban parks based on their ability to reduce flood risk in and around the City of Houston.
Sponsor / Mentors: Dr. Reggie DesRoches and Dr. Antonia Sebastian (Rice), Dr. Katherine Ensor (Rice)
Project Title: Genomic Basis of Alzheimer's Disease
Team Members: EunYeop Kim, Dessy Akinfenwa, Ami Sheth, Jason Yin and Miten Shah
The goal is to utilize a combination of unsupervised and supervised learning approaches to derive a set of mouse models on which experiments can be performed to find treatments for Alzheimer's Disease.
Sponsor / Mentors: Dr. Ying-Wooi Wan (Baylor College of Medicine), Dr. Genevera Allen (Rice)
Project Title: Predicting Illegal Dumping in Houston Using 311 Service Helpline Requests
Team Members: Sarah Asson, David Brodkey, Richard He, Nick McMillan, Emma Min
Our team uses reports of illegal dumping collected via Houston's 311 Service Helpline platform to develop a model that can predict month-ahead spatial patterns of illegal dumping. We use these spatial predictions to identify hotspots of illegal dumping where we recommend the City of Houston place cameras to catch perpetrators of this crime.
Sponsor / Mentors: Steven David (City of Houston), Dr. Dan Kowal (Rice)