Sotabase

Career

· Software Engineer, Celonis2023–
· Software Engineer Intern, Google2018–2018
· Doctor of Philosophy (Ph.D.), Computer Science, Columbia University in the City of New York2016–2022
· Research Intern, NCSR "DEMOKRITOS"2015–2015
· SAP HANA Engineer Internship, SAP2015–2016
· Master’s Degree, Electrical Engineering and Computer Engineering, 9.78, National Technical University of Athens2010–2015

Publications (21)

No-regret learning and mixed Nash equilibria: They do not mix
Neural Information Processing Systems · 2020
93
cited
Principled Weight Initialization for Hypernetworks
International Conference on Learning Representations · 2020
84
cited
Complaint-driven Training Data Debugging for Query 2.0
SIGMOD Conference · 2020
48
cited
Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games
Neural Information Processing Systems · 2019
44
cited
Efficiently avoiding saddle points with zero order methods: No gradients required
Neural Information Processing Systems · 2019
35
cited
Assessing SATNet's Ability to Solve the Symbol Grounding Problem
Neural Information Processing Systems · 2023
24
cited
Enabling SQL-based Training Data Debugging for Federated Learning
Proceedings of the VLDB Endowment · 2021
16
cited
Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent
Neural Information Processing Systems · 2021
15
cited
ConnectorX: Accelerating Data Loading From Databases to Dataframes
Proceedings of the VLDB Endowment · 2022
12
cited
Complaint-Driven Training Data Debugging at Interactive Speeds
SIGMOD Conference · 2022
11
cited
Hunter NMT System for WMT18 Biomedical Translation Task: Transfer Learning in Neural Machine Translation
Conference on Machine Translation · 2018
11
cited
Online Wideband Spectrum Sensing Using Sparsity
IEEE Journal on Selected Topics in Signal Processing · 2017
8
cited
FaDE: More Than a Million What-ifs Per Second
Proceedings of the VLDB Endowment · 2024
4
cited
Accelerating Deletion Interventions on OLAP Workload
IEEE International Conference on Data Engineering · 2024
1
cited
Chaos persists in large-scale multi-agent learning despite adaptive learning rates
arXiv.org · 2023
1
cited
How I stopped worrying about training data bugs and started complaining
DEEM@SIGMOD · 2022
1
cited
Complaint Driven Training Data Debugging for Machine Learning Workflows
2023
Fast Hypothetical Updates Evaluation
Proceedings of the ProvenanceWeek 2025 · 2025
Hard Threshold Least Mean Squares Algorithm
arXiv.org · 2016
Prompt Editor: A Taxonomy-driven System for Guided LLM Prompt Development in Enterprise Settings
SIGMOD Conference Companion · 2025
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