Self & Career Development (AS2)

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Registration is optional. However, only registered participants will receive a certificate of participation.

Online Link

Speakers:
Yannis Chronis, Assistant Professor, Department of Computer Science, ETH Zurich 
Dr. Nikos Myrtakis, Applied Scientist, Synaptically

Title: Self & Career Development
Date: 2026-02-19
Time: 11:00 – 13:00 (Athens), 10:00 – 12:00 (Paris)
Location: Online Link
Meeting ID: 829 7868 9843
Password: 039956
Host: Themis Palpanas, UPC

Abstract: Feeling uncertain about the next stage of your career is common, whether you are just embarking on doctoral research, preparing for your thesis defence, or eyeing a move into industry or vice-versa.
This seminar is honoured to welcome Mr Yannis Chronis and Mr Nikos Myrtakis, working as Assistant Professor and Applied Scientist respectively, to identify your personal strengths, develop effective networking and personal branding strategies, and provide an in-depth analysis of how to plan your career. It goes beyond theorectical frameworks through case studies, bridging academic research with industry expertise. After their presentations, a moderated discussion along with an interactive Q&A session will assit you in transforming your research compentencies into a strategic career vision.

Short bio:
Yannis Chronis
Yannis Chronis an Assistant Professor in the Department of Computer Science at ETH Zurich and a Visiting Professor at Google. He is a member of the ETH Systems Group. His work focuses on making access to data efficient, and the systems that provide it robust and easy to use. Yannis' research interests span database systems, computer architecture, machine learning and their intersections. Before joining ETH, he spent 3 years at the Systems Research Group at Google. He received Ph.D. in Computer Science from the University of Wisconsin-Madison, advised by Prof. Jignesh Patel. He holds a Bachelor's and a Master's Degree on Computer Science from the University of Athens, Greece.

Nikos Myrtakis
Nikos Myrtakis holds a joint Ph.D. in Computer Science from CY Paris University and the University of Crete, with a focus on data quality monitoring for deep learning models. He is currently an Applied Scientist at Synaptically, and previously worked at Honda Research Institute Europe and SAP Paris, where he contributed to anomaly detection and distribution shift detection methods across vision, tabular, and time-series modalities. His research has been published at established machine learning and data management venues, including SIGKDD, VLDB Journal, ICML, and ICDE, and has been recognized with a Best Paper Award by the French National Conference on Data Management. His research interests include data quality monitoring for deep learning, explainable AI, and anomaly detection.