New Program – Masters in Cybersecurity and Data Analytics

In April 2015 I was attending a job interview at UT Tyler. Tom Roberts, who was the incoming Computer Science Dept Chair, took me out to dinner and we laid out the roadmap for our vision for the department. It took us 7 years and several administrations, but we are please to announce a new degree program that blends together cybersecurity and data analytics. This program is 100% asynchronous online and designed for working professionals to complete in one year. Our first class starts January 9, 2023.

More information can be found here:

IIMA – An Analysis of COVID-19 Allergic Reactions

A new publication is available here.

From our study, all three covid-19 vaccines have a similar proportion of adverse reaction reports in which the patient had a history of allergies. However, the proportion of life-threatening outcomes were lower for those with the Janssen vaccine (0.62% hospitalization rate for Janssen versus 2.59% for Pfizer and 0.60% death for Janssen versus 5.15% for Moderna). In terms of specific allergies, patients with *cillin or sulfa allergies had the most adverse reactions to covid-19 vaccines, however, Janssen again had the lowest percentage of reported deaths (1.39% for *cillin-related allergy deaths for Janssen versus 6.10% for Pfizer). In terms of patient age and gender, females has 2.9x the number of adverse reactions than males and a lower average age for reactions for the Pfizer and Moderna vaccines. We feel this data could be used by individuals and medical professionals to assist in choosing a vaccine to maximize patient safety based on their allergy history, age and gender.

JITIM – A Data Driven Approach to Profile Potential SARS CoV-2 Drug Interactions using TylerADE

A new publication is available here.

We use a data driven approach on a cleaned adverse drug reaction database to determine the reaction severity of several covid-19 drug combinations currently under investigation. We further examine their safety for vulnerable populations such as individuals 65 years and older. Our key findings include 1. hydroxychloroquine/chloroquine are associated with increased adverse drug event severity versus other drug combinations already not recommended by NIH treatment guidelines, 2. hydroxychloroquine/azithromycin are associated with lower adverse drug event severity among older populations, 3. lopinavir/ritonavir had lower adverse reaction severity among toddlers and 4. the combination of azithromycin, hydroxychloroquine and tocilizumab is safer than its component drugs. While our approach does not consider drug efficacy, it can help prioritize clinical trials for drug combinations by focusing on those with the lowest reaction severity and thus increase potential treatment options for covid-19 patients.

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.”