Roberto Cavazos, Ph.D.
Executive In Residence
Department of Information Systems and Decision Science
Office: Business Center 477
- Ph.D., University of Texas
- Continuing Education: Coursera Python, Data Scientists Tool Box. Project Management, �R�. ,
- M.P.A, The University of Texas
- B.A., The University of Texas at Austin
Economist with over 25 years experience in economic analysis, statistical & data analysis, project and program management. Experience with foreign & U.S. Governments, businesses, financial institutions and non-governmental organizations. International work experience in Australia, Mexico, Honduras, Spain.
Applications of analytics, measurement, analytics and litigation, analytics and performance.
Statistics, Business Analytics, Economics/Econometrics
Cavazos, R. (2019). Big Data Analytics in U.S. Courts: Uses, Challenges and Implications, 2019. Palgrave Advances in the Economics of Innovation and Technology, Springer Nature, Switzerland AG..
Refereed Journal Articles
Cavazos, R. (2019). An inquiry into social impact measurement for programs designed to end poverty, in developed nations, through entrepreneurship training to sub-theme 71: Social Impact Evaluation: The Technical and Sociopolitical Challenges of Accountability. Eurpoean Group for Organizational Studies.
Cavazos, R. (2020). The Economic Costs of Keyword Blacklists for Online Publishers.
Cavazos, R. (2020). The Economic Cost of OTT Fraud.
Cavazos, R. (2019). Bot Attacks 2019.
Cavazos, R. (2019). Fake News 2019.
Cavazos, R. (2019). Fake Influence Marking 2019.
Cavazos, R. 13th Annual Pharma Resource Planning & Portfolio Management Conference, Pharma, Philadelphia. (2020).
Cavazos, R. Fraudnomics Summit, "Keynote for Summit," Various, New York. (2019).
Cavazos, R. Analytics and Complex litigation, "Analytics and Complex Lititation," UB Merrick and Law School, UB. (2019).
Cheddar: 11/18/2019 "Exclusive: Fake News Is Costing the World $78 Billion a Year" Cheddar, Inc. Michelle Castillo https://cheddar.com/media/exclusive-fake-news-is-costing-the-world-billion-a-year (2019).
Institutional Investor: "Fake News Creates Real Losses" Institutional Investor Alicia McElhany https://www.institutionalinvestor.com/article/b1j2ttw22xf7n6/Fake-News-Creates-Real-Losses (2019).
Wall Street Journal: "Online Influencers Tell You What to Buy, Advertisers Wonder" Wall Street Journal Suzanne Kapner, Sharon Terlep https://www.wsj.com/articles/online-influencers-tell-you-what-to-buy-advertisers-wonder-whos-listening-11571594003 (2019).
Elle Magazine: "INVESTIGATING INSTAGRAM FRAUD The Social Media Scams Costing Businesses �1Billion Per Year" Elle Magazine Daisy Murray https://www.elle.com/uk/life-and-culture/a28842871/instagram-fraud/ (2019).
Times of London: "Influencer fraud costs sponsors �1bn a year" Times of London Mark Bridge https://www.thetimes.co.uk/article/influencer-fraud-costs-sponsors-1bn-a-year-25zwltrj3 (2019).
American Marketing Association: 7/26/2019 "Fraudulent Influencer Marketing is Costing Brands" American Marketing Association Katie Powers https://www.ama.org/marketing-news/fraudulent-influencer-marketing-is-costing-brands/ (2019).
CBS News: "Influencer marketing fraud will cost brands $1.3 billion in 2019" CBS News Megan Cerullo https://www.cbsnews.com/news/influencer-marketing-fraud-costs-companies-1-3-billion/?ftag=CNM-00-10aab4i (2019).
CNBC: "Fake followers in influencer marketing will cost brands $1.3 billion this year, report says" CNBC Megan Graham (2019).
Mobile Marketing Association: "Online Ad Fraud To Cost $23 Billion Globally in 2019" Mobile Marketing Association Unknown https://www.mmaglobal.com/research/online-ad-fraud-cost-23-billion-globally-2019 (2019).
Ad Age: "REPORT: AD FRAUD TO HIT $23 BILLION, ISN'T GOING DOWN" Ad Age George Slefo https://adage.com/article/digital/report-ad-fraud-hit-23-billion-isnt-going-down/2174721 (2019).
Research in Progress
"Ad Fraud and Marketing ROI a Conundrum" (Writing Results)
"Big Data and Impications for Litigation" (Writing Results)
Article on changing bench guide given the preponderance of big data.