IEEE Access paper – Developing Big Data Projects in Open University Engineering Courses: Lessons Learned

A new publication is available here.

Big Data courses in which students are asked to carry out Big Data projects are becoming more frequent as a part of University Engineering curriculum. In these courses, instructors and students must face a series of special characteristics, difficulties and challenges that it is important to know about beforehand, so the lecturer can better plan the subject and manage the teaching methods in order to prevent students’ academic dropout and low performance.

CFP – Machine Learning Designs, Implementations and Techniques

IEEE Access special issue on Machine and Deep Learning.

The topics of interest include, but are not limited to:

  • Real time implementation of machine and deep learning,
  • System level implementation, considering full pipeline from raw data until the decision layer
  • Novel and innovative applications with strong emphasis on design and implementation
  • Novel approaches for Temporal / Spatial/Spatio-Temporal Association analysis
  • Pattern discovery from Time stamped Temporal and Interval databases
  • High performance data mining in cloud
  • Novel approaches for handling Uncertain and Imbalanced data
  • Supervised/Unsupervised techniques for mining healthcare data
  • Deep learning for translational bio-informatics
  • Periodic/Sequential pattern mining
  • Evolutionary algorithms
  • Privacy-Preserving Data mining
  • Time series similarity and Irregular temporal data analysis
  • Mining Text Web and Social network data
  • Imputation techniques for Temporal data
  • Causality and Event Processing
  • Applications of Data Mining in Anomaly and Intrusion detection
  • Applications to medical informatics

Sports Data Mining book still going strong

Springer announced that my Sports Data Mining book of 2010 is still in the Top 25% of eBook sales for 2018.

DHPS paper – Opioids and Frequency Counts in the US Food and Drug Administration Adverse Event Reporting System (FAERS) Database

A new publication is available here.

The U.S. Food and Drug Administration Adverse Event Reporting System (FAERS), contains information on adverse drug events and medication error reports submitted to the FDA through the MedWatch program. A significant number of adverse events reported in the FAERS database have been for opioid use. The objective of this study was to determine the frequency counts and associated deaths of opioid drug names in the FAERS database.

Keynote – National Institute of Applied Science and Technology

Dr. Schumaker was keynote at NIT Day for the National Institute of Applied Science and Technology (INSAT) on April 7, 2019 on “Becoming a Data Scientist.” This lecture is part of the ACM’s Distinguished Speakers Program.

Invited Talk – ESPIRIT (Tunis, Tunisia)

Dr. Schumaker provided a motivational talk on getting into the field of Data Science to students at Ecole Supérieure Privée d’Ingénierie et de Technologies (ESPIRIT) on April 6,2019. This lecture is part of the ACM’s Distinguished Speakers Program.

Invited Talk – Western Washington University

Dr. Schumaker was invited to present to Western Washington University in Bellingham, WA on May 16, 2019 on “Becoming a Data Scientist” and “Prediction from Regional Angst – A Study of NFL Sentiment in Twitter Using Technical Stock Market Charting.”

Invited Talk – Seattle Pacific University

Dr. Schumaker was invited to present to Seattle Pacific University in Seattle, WA on May 15, 2019 on “Becoming a Data Scientist” and “Lessons from the Future: Predictions in Finance, Sports and Medicine.”

UT Tyler Professor Explains How Sports Analytics Could Predict Super Bowl 53 Winner

Dr. Schumaker was featured in a segment by Jeff Wright on “UT Tyler Professor Explains How Sports Analytics Could Predict Super Bowl 53 Winner” for KLTV.com.

The article can be accessed here.

Interview – KYTX The Noon Show

Dr. Schumaker was interviewed live by Jen Moynihan on “The Science of Sports Analytics” for The Noon Show.