Steffen Ventz

   

Steffen Ventz

 

Affiliation

Department of Data Sciences,
Dana-Farber Cancer Institute

Department of Biostatistics,
Harvard School of Public Health

Contact Information

3 Blackfan
Office: CLS-11032
Boston, MA 02215
Email: steffen [at] jimmy [dot] harvard [dot] edu

Full Curriculum Vitae

CV (last updated 06/2021)

Education

PostDoc Department of Biostatistics, Harvard University, Boston 2013-2015
Ph.D. in Mathematical Statistics, Bocconi University, Italy, 2013
M.Phil in Mathematical Statistics, Bocconi University, Italy, 2010
M.A. in Mathematical Demography, University of Rostock, Germany, 2007
B.S. in Mathematical Demography, University of Rostock, Germany, 2005

About me

I am a reserach scientist at the Department of Data Sciences at the Dana Farber Cancer Institute and the Department of Biostatistics at the Harvard T.H. School of Public Health. I am affiliated with the Cencer for Regulatory Sciences at the Dana-Farber Cancer Institute.

Before joining DFCI and Harvard University, I spent a couple of years as an Assistant Professor at the University of Rhode Island, where I was also affiliated with the Department of Computer Science and Statistics. Prior to URI, I was a PostDoctoral Fellow at at the Harvard T.H. School of Public Health. I completed my PhD in Statistics from Bocconi University in Milan, Italy, under the supervision of Pietro Muliere.

My research interests are mainly in response-adaptive clinical trials, statistical computation, Bayesian decision theory, Bayesian analyses and lately reinfored learning and causal inference. I’ve done work on information theory, Bayesian dose finding methods, platform and basket trials, statistical inference under adaptive sampling designs, causal inference and computational biology. My recent research interests focuse on multiple testing, deep learning and data fusion. Recent collaborative projects have involved applications in cancer and infectious disease. See my Papers page for more details.

Research Interests

Bayesian Statistics, Statistical Decision Theory,
Statistical Computing, Monte-Carlo Optimization,
Adaptive methods for Sequential Statistics Experiments,
Bayesian Adaptive Design of Clinical Experiments, Basket trials, Platform Trials
Inegrated Analysis of Multiple Datasets
Causal Inference
Reinfoced Learning, Deep-Learning

Academic Experience

Research Scientist, Department of Biostatistics, Harvard University, 2018-
Research Scientist, Program in Regulatory Science, Dana-Farber Cancer Institute, 2017-
Assistant Professor, Department of Computer Science and Statistics, University of Rhode Island, 2015 - 2018
Visiting Scientist, Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 2015 - 2018
Research Fellow, Department of Biostatistics, Harvard University, 2013-2015
Research Fellow, Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute 2013-2015

News

  • 2020/02: Steffen taught two short cources on Bayesian adaptive designs at the University of Sydney and monash University in Melbourne
  • 2020/02: Steffen joined the FDA-Project Data Sphere Talks Force on the development of novel hybrid trial designs for GBM
  • 2020/01: We just submitted our paper on hybrid trial designs for SCLC studies
  • 2019/12: Our JASA paper on BUD designs is out now
  • 2019/10: Our paper on Bayesian desins for Deintensification studies is now online at CCR
  • 2019/01: Our paper on the design and evaluation of synthetically controlled trial designs is now online at CCR
  • 2018/05: Steffen joined the FDA-Project Data Sphere Talks Force on ECTs for SCLC
  • 2018/07: Steffen organized a ISBA session on Bayesian adaptive designs for clinical studies Edinburgh, Scotland
  • 2017/05: Steffen gave a talk at on Bayesian uncertainty directed sampling at MBSW in Muncie, Indiana
  • 2017/05: Our paper on response adaptive designs for Platform studies has been accepted by Biostatistics
  • 2017/04: Our paper on Platform methods has been accepted by JCO
  • 2017/01: Our paper on Bayesian Basket designs has been accepted by Biometrics
  • 2016/06: Our paper on Adaptive designs for surrogate outcome models has been accepted by Clinical Trials
  • 2015/03: Our Biometrics paper on the control of Frequentist operating characteristics for Bayesian designs is out