Best Paper Runner-Up at High Performance Computing for Imaging (HPCI), Electronic Imaging Symposium (Jan. 2023); Best Paper Award at Supercomputing, 2020 (out of 378 submisions); (Two times) Impact Argonne Award for notable achievement in Innovation, DSL/ANL (June 2022, May 2020); SIGHPC Certificate of Appreciation, ACM Student Cluster Competition at Supercomputing, 2020; Top Recognition for an Exemplary blend of Network, Computing, and Storage, SCinet Technology Challenge at Supercomputing, 2019; Pacesetter Award for excellence in achievement and performance, DSL/ANL (Jan. 2019); Best Paper Nomination at CCGrid, 2014 (283 submitted, 3 selected); Travel Grants: CCGrid’14, IPDPS’13, IPDPS’10; Senior Member of IEEE and ACM.
Research Experience
Computer Scientist at Data Science and Learning Division, Argonne National Laboratory (2018-Present); Computer Scientist at X-ray Science Division, Argonne National Laboratory (2018-Present); Senior Scientist at Consortium for Advanced Science and Engineering, University of Chicago (Aug. 2020-Present); Assistant Computer Scientist at Mathematics and Computer Science Division, Argonne National Laboratory (Sept. 2016-2018); Postdoctoral Researcher at Mathematics and Computer Science Division, Argonne National Laboratory (June 2014-Sept. 2016); PhD Intern in Data Intensive Scientific Computing Group, Pacific Northwest National Laboratory (Fall 2012, Summer 2011); Research Intern in Distributed Streaming Systems Group, IBM T.J. Watson Research Center (Summer 2012); Graduate Research or Teaching Associate in CSE Department, Ohio State University (2010-2014).
Education
Ph.D., Computer Science & Engineering, Ohio State University, 2010-2014; M.S., Computer Science & Engineering, Ohio State University, 2008-2010; B.Eng., Computer Engineering, Izmir Institute of Technology, 2001-2006.
Background
Computer scientist at the Data Science and Learning (DSL) division at Argonne National Laboratory. Also holds joint appointments in X-ray Science Division (XSD) at Advanced Photon Source (APS) and Consortium for Advanced Science and Engineering (CASE) at the University of Chicago. Currently interested in developing high-performance computing and AI/ML techniques to solve large-scale synchrotron radiation X-ray image analysis problems.
Miscellany
Links to personal pages on GitHub, Google Scholar, ORCID, ResearchGate, etc.