Center for Data, Mathematical, and Computational Sciences

October 11, 2022Using Data and Analytics in Sports

Friday, October 21st at 12-1pm in ASB 225

Please join us for a DMC Lecture Series event on Using Data and Analytics in Sports, given by Dr. Scott Nestler, Principal Data Scientist & Optimization Lead, SumerSports LLC!

The use of data and analytics in sports has changed significantly in the nearly two decades since the release of the book “Moneyball” in 2003. Moving from descriptive to predictive and prescriptive (in terms of the types of analytics used), this evolution was enabled by changes in the type (box score, play-by-play, tracking) of data, as well as growth in quantity and improvements in quality. Analytic methods are being used to measure and predict individual and team performance, prevent injuries, and improve business outcomes. Besides providing a variety of examples from across different sports, I will provide suggestions on how those seeking to get into the growing field of sports analytics can ensure that they have the skills that are sought by teams and other organizations.

This talk was supported by a grant from the Ramapo College Foundation.

Scott is a “pracademic” who joined the Sumer Sport team in 2022, after a variety of experiences, including: Data Science Senior Manager / Director of Statistics & Modeling at Accenture Federal Services; Academic Director for the MS in Business Analytics program at Notre Dame, and a full career as an operations research analyst (and leader of analytic teams) in the U.S. Army. He teaches as an Adjunct Faculty Member for Notre Dame and SMU. Scott is very involved as a volunteer and leader with the Institute for Operations Research and the Management Sciences (INFORMS), where he served as the first Chair of the Analytics Certification Board, the governing body for the Certified Analytics Professional (CAP) program. He has a PhD in Management Science from the University of Maryland – College Park, is a CAP, and also an Accredited Professional Statistician (PStat). He is co-author of the book
“Mathletics: How Gamblers, Managers, and Fans Use Mathematics in Sports,” Princeton University Press, 2002.

His motto is, “Make yourself useful, doing something hard, with good people.” Scott enjoys traveling (he’s been to all 50 states and 25 countries), reading, cooking, and sitting around the firepit with family and friends.

Categories: Lecture Series

September 27, 2022Data Assimilation and Dynamical Systems Analysis of Circadian Rhythmicity and Entrainment

Wednesday, October 12th at 6-7pm in ASB 327

Please join us for a DMC Lecture Series event on Data Assimilation and Dynamical Systems Analysis of Circadian Rhythmicity and Entrainment, given by Dr. Casey Diekman of the New Jersey Institute of Technology!

Circadian rhythms are biological oscillations that align our physiology and behavior with the 24-hour environmental cycles conferred by the Earth’s rotation. In this talk, I will discuss two projects that focus on circadian clock cells in the brain and the entrainment of circadian rhythms to the light-dark cycle. Most of what we know about the electrical activity of circadian clock neurons comes from studies of nocturnal (night-active) rodents, hindering the translation of this knowledge to diurnal (day-active) humans. In the first part of the talk, we use data assimilation and patch-clamp recordings from the diurnal rodent Rhabdomys pumilio to build the first mathematical models of the electrophysiology of circadian neurons in a day-active species. We find that the electrical activity of circadian neurons is similar overall between nocturnal and diurnal rodents but that there are some interesting differences in their responses to inhibition. In the second part of the talk, we use tools from dynamical systems theory to study the reentrainment of a model of the human circadian pacemaker following perturbations that simulate jet lag. We show that the reentrainment dynamics are organized by invariant manifolds of fixed points of a 24-hour stroboscopic map and use these manifolds to explain a rapid reentrainment phenomenon that occurs under certain jet lag scenarios.

This talk was supported by a grant from the Ramapo College Foundation.

Casey Diekman is a mathematical biologist and Associate Professor in the Department of Mathematical Sciences at the New Jersey Institute of Technology. He obtained his PhD in Bioinformatics and Industrial & Operations Engineering from the University of Michigan in 2010. Diekman was then a Postdoctoral Fellow at the Mathematical Biosciences Institute at Ohio State University until joining the NJIT faculty in 2013. Recently, he spent a year in residence at the University of Exeter as a US-UK Fulbright Scholar. Diekman’s research interests include mathematical and computational modeling of circadian (~24-hour) rhythms such as the sleep-wake cycle, data assimilation, machine learning, and dynamical systems analysis. His research has been supported by the National Science Foundation and the US Army Research Office.

Categories: Lecture Series

February 15, 2022Multifractal Analysis of Daily US COVID-19 Cases

Wednesday, March 23rd at 6-7pm in ASB 323

In this talk we discuss how the multifractal detrended fluctuation analysis (MFDFA) technique can be used to explore the highly irregular behavior or volatility clustering of daily COVID-19 cases in the United States. By using the multifractal spectrum of the MFDFA we will characterize the path and predict the short or long memory behavior of the US COVID-19 Cases on different time scales.

Biography: Osei Tweneboah is Assistant Professor of Data Science at Ramapo College of New Jersey. His main research is Stochastic Analysis, Machine Learning and Scientific Computing with applications to Big Data and Complex Data sets arising in Finance, Public Health, Geophysics, and others. Dr. Tweneboah is co-author of the textbook Data Science in Theory and Practice: Techniques for Big Data Analytics and Complex Data Sets recently published by Wiley.

Categories: Data Science, Lecture Series, MSDS

February 7, 2022How to fail your tech interview successfully

Feb 22nd at 6-7pm in ASB 332

Computer Science is hard. Being a Software Engineer is hard. Translating your computer science skills into a successful Software Engineer gig after college shouldn’t be hard. After interviewing close to 100 candidates at all levels for Google, Facebook and Manticore, Dobri Yordanov has a few tips and tricks to share, as well as pitfalls to avoid. Join us if you’d like to hear about them, be it out of curiosity or practicality. Everyone is welcome!

Biography: Dobri is a Ramapo College ’15 graduate, originally from Bulgaria. Since graduating, he’s built a career as a Software Engineer and a self-described Prototype Wizard in large tech working for Google and Facebook, and most recently landing in the game industry as a principal engineer at Manticore Games. As of ’21, you can occasionally catch him in Ramapo teaching some of our Computer Science classes. He likes long walks on the beach in VR and philosophical ponderings about the nature of our existence and ethics in technology. He will also absolutely listen to you about your favorite algorithm or design paradigm – he is 100% that kind of dork.

Categories: Lecture Series, Uncategorized

November 1, 2021Lecture Series: Data is the New Oil- Why Now?

Wednesday, November 10, 2021 at 5:00 PM until 6:00 PM – Eastern Standard Time

Ramapo College is proud to host a Graduate Lecture Series about a variety of interesting topics throughout the year.

During the RCNJ Lecture Series: Data is the New Oil- Why Now, you’ll have the opportunity to hear from Arnab Mukhopadhyay, Head of Enterprise Architecture at Valley Bank more about exploring a systemic or architecture-based viewpoint on exploring various aspects of data – ranging from an overview on data technologies, data integration, data analytics, data governance, and industry usage of data.

For more information about this particular topic, or questions about the event, please email Professor Scott Frees at sfrees@ramapo.edu and we will be happy to assist you.

You won’t want to miss this exciting and informative Graduate Lecture Series Event.

Categories: Lecture Series, Uncategorized

August 27, 2021Using Machine Learning to Analyze and Predict the Movement of Horseshoe Crabs in Long Island Sound

Dr. Samah Senbel, Assistant Professor of Computer Science at Sacred Heart University will be describing her work on developing machine learning models to predict animal movement patterns. Please join us (virtually) on Monday, September 27th at 1pm to learn more about this important area of study in ecology, conservation and wildlife management.

Connection details will be provided after registration.

Abstract: Developing models to predict animal movement patterns is an important area of study in ecology, conservation and wildlife management. Models can be used to decipher patterns in mark-recapture data and machine learning can help to make predictions about future animal movement patterns. Project Limulus (PL), a community research program, has been tracking the movement of tagged individuals in the population of American horseshoe crabs (Limulus polyphemus) in Long Island Sound since 1997. During the spring spawning season, horseshoe crabs are captured by hand in spawning areas along the Connecticut (CT) shoreline, tagged and then released. Recaptured horseshoe crabs give valuable information about their behavior, if they exhibit site fidelity and movement patterns around the Sound. In this paper, we tested various models to find the best predictor for the movement of spawning horseshoe crabs to shorelines in the Sound based on the observed movement activity in previous years. The dataset consists of all the previous horseshoe crab movements: initial longitude and latitude, sex, initial date, and recapture longitude and latitude and recapture date. This dataset has 19,219 recapture records covering twenty years of activity. We experimented with three different models: Linear Regression, Decision Tree, and Random Forest Regression models. We used the data for 2018 as our test set and the data of all previous years as our training set. The Random Forest Regression model proved to be the best predictive model for animal movement and resulted in the smallest RMSE and MAE, as well as the smallest maximum error in prediction. The predicted horseshoe crab locations can be targeted in the next season for recapturing previously tagged horseshoe crabs, which provides valuable information about their movement patterns. It also concentrates the scientists’ effort and time to find the maximum number of horseshoe crabs.

This talk is supported by a grant from the Ramapo College Foundation.

Categories: Data Science, Lecture Series, MSDS

January 21, 2021From Data Ethics to Data Justice: The Challenge of Building Better Worlds through Data Science

Dr. Andrea Pitts, Assistant Professor of Philosophy at the University of North Carolina, Charlotte will be describing this new new branch of study within applied ethics, a subfield in professional ethics that includes areas of research and practice such as computing ethics, media ethics, and biomedical ethics. This new branch of applied ethics responds, specifically, to novel applications and technologies for data storage, maintenance, and processing that add new layers to the study of morally relevant considerations within information ethics, business ethics, and AI ethics, for example.

Categories: Lecture Series, Uncategorized

November 20, 2019Data Science at ESPN: NBA player performance

Data Science at Ramapo

Join us on December 5th to hear Brian Macdonald showcase how Data Science identifies the value of box score statistics in estimating NBA players’ contribution to on-court performance. Dr. Macdonald is the Director of Sports Analytics at ESPN, and has a doctorate in Mathematics from Johns Hopkins University.

Please join us in the York Room (Mansion) on December 5th at 4pm to hear about how these approaches can be applied to a variety of sports such as hockey, soccer, football, and eSports.

You’ll also have the opportunity to learn more about Ramapo’s new Data Science programs, launching this coming fall.

Categories: Data Science, Lecture Series