Wang Evaluation Consultants
TTU Process Evaluation
Child and Adolescent Needs and Strengths (CANS)
Child Protective Services (CPS)
how to create effective visualizations, how to present findings to stakeholders, how to collaborate on a data science team, and much much more.
Dr. Wang is an excellent data scientist. Over our time together, he and the team he led built dozens of machine learning models to solve problems related to education and health. He was passionate about always learning new data science techniques to improve the work. Because of his passion for learning and improving, he has a deep knowledge of data science and ML/AI techniques.
Dr. Wang is a one-of-a-kind leader. He works towards creating an environment where everyone can flourish. He truly cares about those he leads. To this day, he still regularly checks in on me to see how I’m doing. Now that I’m manage my own data science team, I look to him as an example of the type of leader I want to be.
I don’t think it’s an overstatement to say I owe my career to Dr. Wang. I’m very lucky to have had him in my life.
Being part of the team that he put together to analyze complex issues developed skills that are beyond what formal education can attain.
Not only is Dr. Wang highly skilled in data science, he has a perspective that can make the complex appear simple. I have been fortunate to work with him on Machine Learning (ML) analysis of substance use and criminal justice. His understanding and application of ML concepts is remarkable. I have not met anyone with as deep of an understanding of the multiple statistical methods and models. His passion for staying on the cutting edge of analysis is evident in not only his abilities, but also in his ease of explaining new technologies.
Being a part of Dr. Wang’s team explains 100% of the variance in my statistical capabilities. I have also been able to glean a perspective to look at issues more critically, and determine the best avenue for analysis. Working with Child Protective Services provided difficulties due to the patchwork of data and issues. However, through analysis, Dr. Wang was able to lead the team to develop relevant understanding and provide solutions for outcomes.
I recommend Dr. Eugene Wang for all statistical analysis, specifically ML. I cannot think of anyone who has more abilities or experience in analyzing social sciences. His understanding of governmental programs, substance misuse, criminal justice and child welfare are beyond compare. His integrity only adds to the mixture of abilities. Any job that Dr. Wang is involved in will be done transparently and honestly. Skill, integrity, and leadership are the best adjectives I can think of in describing Dr. Wang.
Dr. Wang has helped me foster and focus my passion for data analytics by helping me focus, teaching me programming skills, how to build machine learning models, and how to translate the results to individuals outside of academic institutions.
Dr. Wang is a superb data scientist and mentor. In the short time I have known him, he has dedicated himself to building various machine learning models to solve problems related to substance use, risk of recidivism, risk of sexual violence, and many other social problems. His understanding and application of machine learning concepts, and his ability to foster these skills in his students and employees is extraordinary. Dr. Wang’s abilities have had, and will continue to have, tremendous payoffs in the realm of various social problems.
Dr. Wang embodies everything I hope to be as a researcher, a professional, an employee, and a mentor. He has supported me, encouraged me, and inspired me in ways I am unable to sufficiently articulate. His mentees and employees love him and appreciate his humorous, helpful, patient, and encouraging manner. I am honored to learn from and work for him and I look forward to many more years of collaboration with him.
What we do
Dr. Wang's current
and former ph.d. students
Brooke Bell, Ph.D.
Senior Research Associate
Community, Family, and Addiction Sciences
Dr. Bell has seven years of experience evaluating social service programs through externally sponsored projects for the Texas Department of Criminal Justice (TDCJ) and the Texas Department of Family and Protective Services (DFPS). Her doctoral dissertation examined responsivity in rehabilitation programming for offenders within the Windham School District (WSD) to differentiate who has a greater likelihood of success in the Cognitive Intervention Program (CIP2).
Dissertation: Responsivity in rehabilitation programming for offenders
Kelly Chroback, M.S.W., LMSW
Kelly is currently a doctoral candidate in the Addictive Disorders and Recovery Studies (ADRS) program at Texas Tech University. She received her Master’s degree in Social Work from the University of Pennsylvania. Her research interests include the effects of substance use and mental health conditions on individual risk of perpetrating violence. Her doctoral dissertation examines the effects of substance use on violence among offenders released from the Texas Department of Criminal Justice (TDCJ) and is set to be defended in August of 2022.
Dasha Cochran, Ph.D.
Dasha is a program evaluator with more than ten years of evaluation experience. She holds a PhD in Educational Psychology, a master’s degree in Counseling, and a Bachelor of Science in Economics. Her passion is bringing the world of program evaluation and economics together by supplying the necessary data to make informed decisions toward greater program effectiveness. Dasha strives to inform her clients about the relative value of their interventions and find ways to improve program effectiveness while minimizing costs.
Dissertation: Cost–Benefit Analysis of the Windham School District’s Correctional CTE Program
Jacob Curtis, Ph.D.
Jacob joined Dr. Wang’s lab as a research assistant in 2014. While in Dr. Wang’s lab, he completed projects for the United Way of Amarillo and Canyon, Goodwill Excel Center, and Texas Department of Criminal Justice. His dissertation was titled, “On Using Machine Learning to Predict Recidivism.” After graduating with his PhD in 2018 he joined H-E-B as a data scientist. At H-E-B he oversees projects related to using machine learning to predict out of stock products and using time series analysis to identify trending items.
Dissertation: On using machine learning to predict recidivism
William "Buddy" Gerber, MPA, Ph.D.
Buddy has worked in the addiction treatment industry for more than five years in an administrative and clinical support role. While earning his Master of Public Administration, he acted as a graduate assistant at the Center for Collegiate Recovery Communities at Texas Tech University.
Dissertation: The Effects of Substance Type and Use on Public Safety: A Machine Learning Analysis
Shelby Hatch, M.S.
Samuel Meeks, Ph.D.
Samuel discovered an interest in quantitative research while interning at the Institute for Measurement, Methodology Analysis and Policy during his undergraduate career at Texas Tech. Current research interests include machine learning, low base-rate outcomes with asymmetric cost, and using data to drive policy.
Dissertation: Evaluating class imbalance and asymmetric costs using machine learning
Zachary Nichols, M.B.A., LCDCI
Zachary is currently a doctoral student in addictive disorders and recovery studies (ADRS) at Texas Tech University. He is a licensed chemical dependency counselor and holds an M.B.A. Prior to Texas Tech, Zachary worked at the Menninger Clinic in Houston, Texas. His research interests include the workplace and substance use, interpersonal violence (IPV), decision trees, and choice psychology.