Scholar
Athanasios (Thanos) Vlontzos
Google Scholar ID: XTkiyj4AAAAJ
Research Scientist - Advanced Causal Inference Lab - Spotify
Citations & Impact
Citations
836
H-index
13
i10-index
14
Publications
20
Co-authors
19
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Featured Publication: 'Estimating categorical counterfactuals via deep twin networks', published in February 2020.
Research Experience
- Research Scientist at Spotify, Aug 2022 - Present, London, UK, Part of the Advanced Causal Inference Lab (ACI-Lab), conducting research in causal inference and machine learning, providing causal inference tools to stakeholders supporting major negotiations and decision making; Machine Learning Research Scientist Intern at Apple, Aug 2020 - Dec 2020, Cambridge, UK, worked on word sense disambiguation with the Interactive Intelligence Team; AI Research Consultant at Zeit Medical, Oct 2019 - Aug 2022, Palo Alto, CA, USA (Remote), Advisor to the CEO, led team on machine learning research for identifying stroke events; AI Research Scientist - Contractor at NASA Frontier Development Lab, Jun 2019 - Aug 2019, Mountain View, CA, USA, developed solutions for enhancing predictability of GNSS disturbances; Teaching Scholar at Imperial College London, Oct 2018 - Jun 2022, London, UK, responsible for course material creation, guest lecturing, lab demonstrations, courses included Deep Learning, Computer Vision, NLP, and others; Computer Vision Researcher Intern at General Electric Healthcare, Mar 2017 - Oct 2017, Buc, FR, worked on Interventional Radiology Applications, localization and classification of medical devices in X-Ray Fluoroscopy; Undergraduate Research Assistant at Imperial College London, Jun 2016 - Oct 2016, London, UK, Machine Learning Undergraduate Researcher with Prof. Erol Gelenbe, led to 1 publication.
Education
- PhD in Machine Learning from Imperial College London, BioMedIA group, Oct 2018 - Sep 2022, Advisors: Prof. Daniel Rueckert and Dr. Bernhard Kainz; MEng in Engineering (including B.Eng in Electrical and Electronic Engineering) from Imperial College London, Oct 2014 - Sep 2018, Degree Result: 1st Class; FHEA (Fellowship of the Higher Education Academy) from Imperial College London, Oct 2020 - Sep 2021, as part of the Postgraduate Certificate in University Learning and Teaching.
Background
- Research interests: Causal Inference, Machine Learning, Macroeconomics, Computer Vision, and their real-world applications. Currently a Research Scientist at Spotify, focusing on the intersection of causal inference and machine learning.
