About me
I am an Assistant Professor of Analytics at Miami University. Prior to this appointment, I was a postdoctoral research fellow at the Northwestern Argonne Institute of Science and Engineering. My postdoctoral research focused on applying and developing novel techniques based on Bayesian uncertainty quantification and computational statistics. I completed my Ph.D. in December 2020 in the Industrial Engineering and Management Sciences Department at Northwestern University. The objective of my research is to develop new statistical methods in the presence of data.
Education:
- PhD in Industrial Engineering and Management Sciences
- Northwestern University, 2020
- MS in Industrial Engineering
- Bogazici University, 2014
- BS in Industrial Engineering
- Istanbul Technical University, 2011
Interests:
- Uncertainty quantification
- Statistical computing
- Statistical learning for large data sets
News:
October 21, 2024
Moses Chan and I co-organized a two-part session at the INFORMS Annual Meeting, Seattle, 2024. The sessions titled “Computational/Statistical Methods for Uncertainty Quantification” covered a range of emulation and calibration strategies in tackling searches in high-dimensional parameter space, stochastic simulation data, computationally effective design constructions, multi-fidelity experiments, and more. Some of the presented works can be found via this post.
July 26, 2024
Our NSF grant “Advancing Theory for Nuclear Double-Beta Decay (@NDB)” has been awarded! You can read the details about this exciting project here.
March 18, 2024
I gave an invited talk on the BAND Framework as part of the STAR collaboration’s “Spring Juniors Day”.
July 8, 2023
I accepted the invite to join the ISNET (Information and Statistics in Nuclear Experiment and Theory) Board.
October 3, 2022
I received NSF award to conduct my own research program within BAND collaboration.