Using knowledge for causal feature selection
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Scott Alexander Malec is currently a postdoctoral associate at the University of Pittsburgh, and is currently seeking tenure-track assistant professor opportunities in all relevant areas including public health, epidemiology, and biomedical informatics and bioengineering. Dr. Malec's research focuses on using formal knowledge representations to improve causal inference in real-world patient health data, such as EHRs, by addressing confounding and selection biases.
As a pre-doctoral fellow, he developed drug safety applications combining NLP and graphical modeling methods for addressing confounding bias. He has had three poster abstracts on methods addressing confounding and selection bias accepted at the American Medical Informatics Association (AMIA) Symposia, AMIA Summits, and the National Library of Medicine trainee conference. He has also received an NLM-funded K99/R00 “kangaroo” career development award and is currently working on using the literature to build causal models of retrospective observational data.
Additionally, he has ongoing projects investigating modifiable risk factors for Alzheimer's disease and related dementias and the effects of intervening in those risk factors. He has four forthcoming manuscripts and has been invited to present his work at various conferences.
Dr. Malec has worked as a software engineer at Carnegie Mellon University, a teaching assistant at the University of Texas Health Science Center, and a scientific programmer at the University of Texas Health Science Center. Malec's work focuses on developing methods for addressing confounding and selection biases when assessing causal effects from observational data.
He has worked on several projects, including developing drug safety applications that combine NLP and graphical modeling methods to address confounding bias. Currently, he is working on using the literature to build causal models of retrospective observational data, focusing on applying methods for complex longitudinal exposures that must be measured repeatedly and in settings with time-varying confounding and confounders affected by prior treatment. Additionally, he has ongoing projects investigating modifiable risk factors for Alzheimer's disease and related dementias and the effects of intervening in those risk factors.
Malec has authored several manuscripts and has presented his work at various conferences.
Scott Alexander Malec is a highly accomplished postdoctoral associate seeking tenure-track assistant professor positions at R1 universities. He obtained a B.A. in Languages & Humanities from Edinboro University of PA, an M.L.I.S. in Library & Info Science from the University of Pittsburgh, an M.S.I.T. in Info Sys Management from Carnegie Mellon University, and a Ph.D. in Biomedical Informatics from the University of Texas SBMI. His research focuses on developing methods for addressing confounding and selection biases when assessing causal effects from observational data.
