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Address

Kaiserstraße 170-174
66386 St. Ingbert (Germany)

Awards

IBM Great Minds Award in 2014

Short Bio

Lucjan Hanzlik is a member of the faculty at CISPA Helmholtz Center for Information Security. Previously, he was a visiting assistant professor at Stanford University and a research group leader at CISPA Helmholtz Center for Information Security. He obtained his Ph.D. degree at the Institute for Computer Science Polish Academy of Sciences in Warsaw in January 2016 under the supervision of Prof. Mirosław Kutyłowski. His research focuses mainly on applied cryptography and cryptography for embedded devices. He has published papers at top venues in computer science, including Eurocrypt, Asiacrypt, USENIX Security, and CCS. Lucjan Hanzlik is also a recipient of the IBM Great Minds Award.

CV: Last four stations

Since 2020
Faculty at CISPA Helmholtz Center for Information Security
2018 - 2020
Visiting Assistant Professor at Stanford University
2017 - 2020
Research Group Leader at CISPA Helmholtz Center for Information Security
2016 - 2017
Research Assistant, Wrocław University of Science and Technology

Publications by Lucjan Hanzlik

Year 2023

Year 2022

Conference / Medium

CCS
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security29th ACM Conference on Computer and Communications Security (CCS)

Conference / Medium

ESORICS
Computer Security – ESORICS 2022ESORICS 2022

Conference / Medium

PETS
Proceedings on Privacy Enhancing Technologies22nd Privacy Enhancing Technologies Symposium (PETS 2022)

Conference / Medium

PETS
Proceedings on Privacy Enhancing Technologies22nd Privacy Enhancing Technologies Symposium (PETS 2022)

Conference / Medium

FC
Financial Cryptography and Data SecurityFC 2022

Year 2021

Conference / Medium

CCS
Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications SecurityACM CCS 2021

Conference / Medium

ECCV
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops2021 IEEE CVPR Workshop on Fair, Data Efficient and Trusted Computer Vision

Year 2020