The Analytics Lab @ OU team is a diverse group of brilliant students, both PhD and MS, from Industrial and Systems Engineering (ISE) and Data Science and Analytics (DSA), led by Dr. Nicholson to work on a variety of projects relating to the research foci of the lab: optimization, predictive and classification modeling, and metaheuristics. The majority of the students contribute to projects with application in the burgeoning area of community resilience. However, the research team is large and diverse and over the years a variety of application areas have been included, e.g. bioinformatics, interactive machine learning, novel approaches for statistical methods in observational studies, and real-time streaming predictive modeling. The group also reflects a diversity of cultures, languages, and backgrounds — the past and present students come from (in alphabetical order): Bangladesh, Brazil, China, Columbia, France, India, Iran, Nigeria, Peru, and the United States.
Director: Charles Nicholson, Ph.D.
Dr. Nicholson is an Associate Professor at the University of Oklahoma in the School of Industrial and Systems Engineering and the Analytics Lab director. He holds bachelor degrees in Physics and Mathematics, a Master’s degree in Business, and a PhD in Operations Research from Southern Methodist University in Dallas, TX. Prior to obtaining an academic position he worked in industry and developed proprietary data analytics solutions for eight corporations across the nation and internationally over 12 years. Projects included a wide variety of predictive and prescriptive analytics for diverse companies representing multi-billion dollar retail, finance, and restaurant industries. An excerpt of successful data-intensive solutions included customer-level behavior prediction, fraudulent activity detection, geographic information systems (GIS) strategic and competitive targeting, and product allocation optimization.
He is currently collaborating on research projects with several groups across the United States including Colorado State University, University of Illinois Urbana-Champaign, Texas A&M, University of Oregon, Southern Methodist University, University of North Texas, University of Virginia, Virginia Tech, University of Wisconsin, Stevens Institute of Technology, and Penn State.
Dr. Nicholson serves on the Editorial board of the new Taylor and Francis journal Sustainable and Resilient Infrastructure.
Current Ph.D. students
Vera Wendler Bosco started her PhD at OU in Fall 2014. She completed her B. Sc. in Industrial Engineering at the Federal University of Paraná, in Brazil. She worked at ExxonMobil in Brazil for two years before leaving for an exchange program in Mannheim, Germany. Her current research interest is in the application of stochastic methods on ship routing under uncertain weather conditions.
In her spare time, Vera enjoys swimming and reading fictional books – she is always reading something. She speaks Portuguese, English and German, and wants to learn a fourth language.
- PhD topic: Tropical storms and intermodal resilience
Sai Krishna Theja Bhavaraju completed his master’s in Industrial and Systems Engineering at OU. Sai also holds a bachelor’s degree in Mechanical Engineering from JNTUH, India. Currently, he is working as a Graduate Research Assistant for Prof. Nicholson. During his Master’s, Sai worked as a web editor for the ISE website. Sai is very passionate about cricket and likes road trips. In his free time, Sai enjoys watching movies and listening to music.
- PhD topic: Open-world supervised learning framework
Yunjie “Nicole” Wen, Ph.D. student, ISE
Yunjie Wen completed her Masters in Data Science and Analytics at OU in December 2017. She is currently in the PhD program in the School of Industrial Systems and Engineering at OU. She completed her Bachelor in Electrical Engineering at HUST, China. Before she moved to US, she worked for different companies in industry for over decade. Her Master’s research relates to game theory to evaluate resilience in road-bridge network problems. Currently she is using machine learning methods to further study complex transportation problems.
Yunjie is a very outdoorsy person. She enjoys rock climbing, intense hiking and trail running. Besides outdoor activities, she loves Second World War movies and books. She also plays soccer and is defender for Total Chaos.
Nicole is currently examining resilience intervention strategies and decision-making with respect to critical physical infrastructure systems with respect to the impact on the economy.
- PhD topic: Mitigation for Physical, Social, and Economic Community Resilience
Jay started his PhD at University of Oklahoma officially in the fall of 2018. Prior to that he completed his Master in Data Science and Analytics at OU in May 2017 and his B.A. in Economics at OU in 2016. Before coming to OU he spent 13 years in the US Army. Jay also works as a Data Scientist for the Office of Business Analytics at the University of Oklahoma. His primary research interest include data analytics applied to improve student and university outcomes. Jay also has a B.S. in Psychology.
In his spare time Jay likes to hang out with his wife and two young boys and watch movies and TV shows. Every other year or so he goes with his wife and kids to visit his in-laws in Germany and enjoys some delicious Schnitzel.
- PhD topic: Economic gravity models
Jorge started his PhD. in Industrial and Systems Engineering in the Fall of 2019, after completing his MSc. in Data Science and Analytics at The University of Oklahoma (OU) in the Summer of 2019. He also holds a BSc. in Systems Engineering from Universidad El Bosque in Bogotá, Colombia where he is from originally. His MSc. Thesis was entitled Probabilistic characterization of floods from catchment-scale precipitation moments, in which machine learning models were used in conjunction with data pertaining the spatial variability of rainfall, in order to characterize flood conditions and characteristics over gauged locations across the Contiguous United States (CONUS).
Since Spring of 2017, Jorge has worked with NOAA’s National Severe Storms Laboratory (NSSL) through OU’s Cooperative Institute for Mesoscale Meteorological Studies (CIMMS). As part of NSSL’s Warning Research and Development Division (WRDD), he’s been actively involved with projects such as ANCHOR (Automated Non-Contact Hydrologic Observation in Rivers) [https://blog.nssl.noaa.gov/anchor/] and FLASH (Flooded Locations and Simulated Hydrographs) [https://blog.nssl.noaa.gov/flash/]. Revolving around topics related to hydrometeorology and hydroinfomatics: hydrologic modeling of flash floods, remote sensing and post-wildfire debris flows, his contributions have involved designing and implementing machine learning and statistical computing approaches for predictive modeling, data processing and analysis.
Jorge’s primary research interests include predictive modeling, applied machine learning and hydroinformatics.
In his spare time Jorge enjoys composing, playing and producing music, and as an Amateur Radio Operator (licensed as W3JDG and HK3JDG) he also enjoys exploring the radio spectrum, and contacting DX (long distance) stations.
Current Masters students
William Keely is a Norman native and MSc student in the Data Science and Analytics program at the University of Oklahoma. Prior to starting his Masters, he completed his BA in Mathematics at OU in August 2019.
William is interested in applying Topological Data Analysis, persistent homology, and machine learning to Meteorology and topics in community resilience.
In his spare time William can be found racing or working on bicycles, playing tennis or soccer, or enjoying the weather on a patio with friends. Currently, William is doing an internship with Iridium Satellite Communications.
Former PhD Students
Weili Zhang, PhD ISE, MS DSA
Completion: December 2017
Weili Zhang completed his Master’s degree in Data Science and Analytics at OU and subsequently completed his Ph.D. in Industrial and Systems Engineering at OU. Afterwards, he took a position as a post-doc researcher at OU for ISE and Civil Engineering. He conducts research in the areas of mathematical programming, heuristics, network analysis and machine learning. Previously, Weili worked full-time at Schneider Electric for 2 years and has 4 publications and multiple projects related to simulation modeling and healthcare as undergraduate research assistant at System Engineering Lab of Southeast University. His personal website is https://sites.google.com/site/weiliwebpage/home.
His research interest is in machine learning for resilience analysis of complex networks.
- Masters thesis: Optimal Flow Analysis, Prediction and Application
- PhD topic: Interdependent network restoration optimization
Former MS Students
Rafael A. Pires de Lima, MS DSA
Dr. Rafael A. Pires de Lima completed his MS in DSA and his PhD in Geophysics from OU in December of 2019. His research utilizes deep learning for petrographic analysis. Petrographic analysis is based on the microscopic description and classification of rocks and is a crucial technique for sedimentary and diagenetic studies. When compared to hand specimens, thin sections of rocks provide better and more accurate means for analysis of mineral proportion, distribution, texture, pore space analysis, and cement composition. Most petrographic analysis relies on visual inspection of rock thin sections under a microscope, a task that is laborious even for experienced geologists. Large projects with a tight time frame requiring the analysis of a large amount of thin sections may require multiple petrographers, thereby risking the introduction of inconsistency in the analysis. To address this challenge, he explores the use of deep convolutional neural networks (CNN) as a tool for acceleration and automatization of microfacies classification.
Completion: December 2019
MS thesis: Petrographic analyses with convolutional neural networks
Completion: Summer 2019
Paúl started his Master’s in Data Science and Analytics in Summer 2017 and completed in Summer 2019. He completed his B. Sc. in Mechanical Engineering at Universidad Nacional de Ingeniería, Peru. In his senior year, he was awarded with a scholarship to spend two semesters as an exchange student at OU. His research interest is in mathematical optimization models and data analytics. He finished his MS DSA thesis working on a multi-objective, non-linear, integer programming problem for resilience mitigation modeling and solving the problem using NSGA-II, a genetic algorithm based solution technique.
Paúl has now joined the School of Computer Science at the University of Oklahoma to continue his academic career as he pursues a Ph.D. in CS.
Completion: December 2018
MS Thesis: Lower-energy conformers search of TPP-1 polypeptide via hybrid particle swarm optimization and genetic algorithm
Genwei Zhang, Ph.D. decided to complete his MS in Data Science and Analytics at the University of Oklahoma. Dr. Nicholson was very happy to advise such a bright individual along with Dr. Yihan Shao from the Department of Chemistry and Biochemistry at OU. Genwei completed his Master’s in DSA and accepted a post-doctoral position in the Pentelute Lab at MIT.
Completion: December 2018
Alex holds a BS in Mathematics, as well as an MS in Mathematics from OU. He is a Business Intelligence Analyst for the Oklahoma City Thunder. His research focus, both at work and for the DSA program, is predictive modeling for multiple areas of the business. Prior to his opportunity to work for the Thunder, he worked for Devon Energy and was a teacher and basketball coach.
Alex enjoys spending time with friends and family, working out, reading, and worshiping with Memorial Road Church of Christ.
Alexander Rodríguez, MS DSA
Completion: May 2018
MS thesis: “Data-based stochastic network mitigation”
Alexander started his Master’s in Data Science and Analytics in the Summer of 2016 as a part of the interdisciplinary Community Resilience CORE Research Lab at OU which is a part of the broader NIST-funded Center of Excellence on Community Resilience. He worked on building both mathematical optimization models and predictive models to develop resilience intervention strategies.
Prior to joining the team, he completed his B.Sc. in Mechatronics Engineering at Universidad Nacional de Ingenieria, Peru. During his undergrad, he worked on several predictive analytics projects. In his senior year, he was awarded with a scholarship to spend one year as an exchange student at OU, in which he joined a project at the Systems Realization Laboratory. After graduating, he spent one year in the Maintenance Department of a LNG plant, in which he experimented on the application of prognostics and system health management for some automated devices. Then he got a position on Business Intelligence for a short period before coming to OU.
Alexander likes to engage in a variety of projects to effect social change. In his spare time, he enjoys reading about several kinds of scientific knowledge and also watching soccer on TV.
Alex is currently pursuing his PhD in Computer Science at Virginia Tech.
Yanbin Chang, MS ISE
Completion: May 2018
MS thesis: “Heuristic approach to network recovery”
Yanbin begin work with Professor Nicholson in May of 2016. His MS thesis relates to optimizing the scheduling of the post-disaster recovery actions for a transportation network. The performance measurement for the network is based on the average all-pairs max flow of traffic using a Gomory-Hu tree. Once the network system is damaged, the time and trajectory of the system recovery is highly sensitive to the sequence in which network components are restored. The research question addressed in his thesis relates to the objective function to be minimized for the recovery problem. The most direct choice is to minimize the total recovery time (TRT), that is, the time until system performance obtains the pre-disaster state. However, this approach may be inadequate. A recent metric introduced in the resilience literature referred to as the “skew” of the recovery time (SRT) captures more information than TRT alone. Optimizing under SRT will provide different results than TRT. However, this has not been analyzed in detail. The first research objective addressed by Yanbin is to conduct experiments to provide an empirical analysis to compare and contrast the schedules resulting from the different objectives. The second research objective is to consider alternatives to SRT. Yanbin proposed, implemented, and evaluated an entirely new metric based affectionally referred to as the CRT. The novel measure incorporates even more information about the recovery profile of a particular restoration sequence than the SRT. Additionally, besides the resulting high quality solution results, the genetic algorithm using CRT as the fitness function outperform TRT and SRT in computation time. The derived solutions have substantially different (and arguably must better) schedules.
Yanbin is currently pursuing his PhD in Industrial and Systems Engineering at Clemson.
Completion: December 2017
Gowtham is currently a dual Masters student in Data Science and Analytics and Petroleum Engineering. He has a Bachelors degree in Petroleum Engineering from Indian Institute of Technology, Dhanbad, India. He worked at ONGC, National oil company of India before starting Masters. His current research interest is in Uplift modeling for effective marketing campaigns. Besides this, he has interest in Artificial Neural Networks and Deep Learning.
Gowtham likes to travel in his free time. In last two years, he visited Alaska, Arizona, California, Colorado, Nevada and a few other states. He also visited Denali, Grand Canyon, Sequoia, Death Valley, Sand Dunes National parks.
Pauline Ribeyre, MS ISE
Completion: December 2017
Pauline started her Master’s thesis at OU in the Fall of 2016. She is an ISE student who earned a degree in Computer Science, Modeling and their Applications at ISIMA in Clermont-Ferrand, France. Her research focuses on the application of data analytics to anticancer drug discovery. She is actively collaborating with with SMU’s Center for Drug Discovery, Design, and Delivery to analyze in-silico data at the molecular level to investigate the multidrug resistant P-glycoprotein pump which is problematic in cancer chemotherapy. Essentially, most cancer chemotherapy drugs are “pumped” out of the cancer cells before they can be effective. Professor John Wise at SMU has put together a 3D simulation video of the process and provided some excellent background information here.
When Pauline is not trying to help cure cancer, she likes to spend her free time traveling with friends, hiking and watching TV shows.
Completion: May 2017
MS thesis: A new approach to adapting neural network classifiers to sudden changes in non-stationary environments
Alexandra Amidon started her Master’s in Data Science and Analytics in the Fall of 2015. She completed her B.S. in Economics at George Washington University in Washington, D.C. and spent the following two years working in the economic consulting and data collection/risk solutions industries. Her current research, in collaboration with a video game company, focuses on classifying and predicting user behavior in order to aid game development.
Alexandra competes in local 5k’s and half marathons and plays the clarinet in the Oklahoma City Symphonic Band. In her spare time, Alexandra enjoys traveling, meeting new people, and watching Spanish telenovelas.
Alexandra has recently accepted a position with MSCI, a leading provider of investment decision support tools worldwide, as a Reference Data Production Analyst. She will be using her skills in machine learning to continue developing new tools for anomaly detection.
Completion: May 2017
MS thesis: Model for mitigating economic and social disaster damage through structural reinforcement
Megan Snelling started her Master’s in Industrial and Systems Engineering in the Fall of 2015. In the Spring of 2016, she completed her B.S in Industrial and Systems Engineering at the University of Oklahoma. Megan previously completed research with the Department of Homeland Security in the area of structuring large-scale problems for simulations used for resource planning.
Her current research focuses on optimization models for community resilience. In particular, she is considering a multiple objective, non-linear and integer programming problem meant to inform decision makers on actions to take to minimize damage (in terms of direct economic loss) and minimize expected population dislocation. The problem is further constrained by the need to control factors which (without restriction) tend to exacerbate existing inequities in the community associated with socioeconomic levels. The resilience intervention strategies under study relate to investments in reinforcing and/or retrofitting existing residential, commercial, and government structures within the community.
Megan is getting married this Summer (2017) and plans to spend her Summer hiking through Europe!
Completion: May 2017
MS thesis: The effect of gathering on sandbox player engagement as defined using analytic methods
Emily Grimes graduated from OU with a degree in English Literature and Culture Studies in 2011. After graduation she did freelance work that motivated her to acquire more technical skills. She came back to OU to prepare for a more technical degree. In the meantime she became a project manager at the Digitization Lab at OU’s own Bizzell Libarary. She joined the Data Science and Analytics program for a Master’s degree in the Spring of 2015. Her background in liberal arts informs her passion for user experience. Her current research is in the emerging field of interactive machine learning which incorporates both user experience and machine learning.
Emily is an active volunteer and advocate for women and minorities in tech. She was recently a reviewer for the IEEE VIS Arts Program, a program that highlights the intersection of data visualization and art, and she facilitates a local Girls Who Code club.
She enjoys a good debate, binging on quality television shows, and cooking.
The Summer after graduation she has a road trip planned to the Grand Canyon, Sequoia National Park, and the Big Sur in California. She is also in discussions with KGOU and NPR about starting a new radio program.
Param Tripathi, MS ISE
Completion: December 2016
MS thesis: Analysis of resilience in US stock markets during natural disasters
Param Tripathi started his Master’s in Industrial & Systems Engineering, in Fall 2014. He earned his Bachelor’s in Mechanical Engineering from Jaypee University of Engineering & Technology, India. During his Bachelor’s he did research to predict the crop yield of Soybean in Central India by using mathematical modeling. He also developed a novice automatic chain sprocket transmission mechanism as a part of his capstone project. His current research interest is data analysis for community resilience in order to improve disaster preparedness.
Param loves meeting new people, volunteering and enjoys playing guitar. He is the reigning Mr. International OU and also serves as General Secretary at the International Advisory Council here at OU. Param also likes working on 3D printers and cars in his free time.
Olivia Perret, MS ISE
Completion: May 2015
MS thesis: A novel post-hoc matching procedure using statistical learning methods
Olivia Perret started her master’s thesis at OU in the fall of 2014. She came to Oklahoma to earn a M.S. in Industrial and Systems Engineering, while working in parallel on a degree in Mathematics and Modeling in her Engineering School Polytech in Clermont-Ferrand, France. She earned her two-years university diploma in Mathematics and Computer Science. Her research work focuses on developing novel approaches to matched sampling, propensity scores for longitudinal data. Her other academic interest include programming, modeling and statistics.
Olivia already came to the U.S. six years ago as an exchange student, and it made her want to finish her studies in the U.S. She is planning to stay in the U.S. to start working after obtained her two diplomas from OU and Polytech.
She was involved in the Student Association of her department in her Engineering School in 2013 and was in charge of the event’s organization. Olivia enjoys traveling to discover new countries and new cultures. She likes to spend her spare time with family and her friends, going to fitness classes, and watching TV shows.
Olivia has accepted an offer as an analyst for Standard and Poor’s — immediately after completion she flew the coop to New York.
Cyril Beyney, MS ISE
Completion: December 2015
MS thesis: Quantitative analysis of social media sensitivity to natural disasters
Cyril Beyney is an ISE M.S. student who began his studies in Fall 2014. He is working in parallel on a degree in Computer Science, Modeling, and Applications at ISIMA in Clermont-Ferrand, France. He earned his two-year university diploma in Technology from the Institute of Technology of Limoges in France. His research work is currently focused on analyzing social media data in relationship to disruptive events such as natural disasters (hurricanes, earthquakes, etc.) in order to help inform decision makers regarding community resilience. His other research interests include data analytics and web technologies.
He likes American Football that he discovered at OU with the Sooners. He also likes travelling around the world to discover new countries and cultures, and hanging out with his friends. Cyril is also an avid “couchsurfer” (https://www.couchsurfing.com)!
Cyril has taken the Lead Data Scientist position at Nerd Kingdom — a game development company!
Leslie Goodwin, MS ISE
Completion: May 2015
Leslie completed the accelerated Master’s program in ISE. Her research revolves around employing data-analytics to study biological systems. There is a push to create insightful gene regulatory networks from expression data. People are able to better predict how the system will be affected when one gene is targeted by a drug or treatment by utilizing these networks. Therefore, it is important to explore and apply the various methods for optimizing networks on this type of data. In addition to school, Leslie has been active around campus while at OU having served as Vice President of the Dean’s Leadership Council and Historian for the Institute of Industrial Engineers.
Leslie has completed her studies and has found an amazing job at Deloitte US as a consultant — a job with lots of travel!
Completion: May 2015
MS thesis: Towards resilience analysis: An efficient way to evaluate network performance
Xiaodan, or in English, Diana completed her Master’s in ISE in 2015 on research relating to modeling network performance using data analytics with an overall goal of enhancing resilience analysis capabilities.
Diana is pursuing her PhD in Business Administration at the University of Oklahoma.
Oluwafemi Oseni, MS ISE
Completion: May 2015
Oluwafemi Oseni, or just “Femi”, as he his known to his friends (and everyone is his friend), successfully completed his Masters degree in ISE in 2015. His project focus was was in multicommodity network flows and his area of interest is in data analytics for the energy sector. Femi is currently pursuing opportunities in industry.