Dennis Gankin

Ph.D. student at ETH Zurich | ETH AI Center Associated Researcher
M.Sc. in Computer Science

Researching Machine Learning for Biology and Genetics
Deep Learning, Bioinformatics, Data Science, Industrial Automation, IT Security

Education

ETH Zurich

Since 2023: Doctoral Student at Beltrao Lab
Interpretable Deep Learning for Genotype-to-Phenotype modeling

Technical University Munich

2019-2023: M.Sc. Informatics
Final grade: 1.3
Specialization areas: Artificial Intelligence, Bioinformatics, IT Security, Computer Networks

2015-2019: B.Sc. Informatics
Final grade: 2.0
Minor in Mechanical Engineering Thesis topic: Intelligent Multi-Agent-System for Modular Production Control

École polytechnique fédérale de Lausanne

2017-2018: ERASMUS+ year abroad
Average Grade: 5.2

Massachusetts Institute of Technology

2019-2020: Research project at Abugoot lab
Computational discovery of novel CRISPR-Cas systems

Work Experience

Audi AG - Internship

April - September 2019: digital strategy and algorithms for modular manufacturing

Konrad-Adenauer-Foundation - Working Student

2016-2019: API development and testing; web design; server administration

Sports Clubs and University Sports

2014-2018: Tennis and Badminton coach

Publications

Computational Biology

Leveraging multiplicity in biologically informed neural networks to uncover disease heterogeneity bioRxiv 2026; Gankin & Beltrao.
Unifying the genetic landscape of common and rare diseases via latent neighborhoods bioRxiv 2026; Laman Trip et al.
The AlphaGenome deep learning model predicts effects of non-coding variants Nature Structural Molecular Biology 2026; Gankin & Beltrao
Species-aware DNA language models capture regulatory elements and their evolution Genome Biology 2024; Gankin, Karollus, Hingerl et al.
A global metagenomic map of urban microbiomes and antimicrobial resistance Cell 2021; Danko et al.

Modular Production Control

Modular Production Control with Multi-Agent Deep Learning IEEE ETFA 2021; Gankin et al.
Adaptive Production Control with Negotiating Agents in Modular Assembly Systems IEEE SMC 2019; Gankin, Mayer et al.
Adaptive Production Control in a Modular Assembly System – Towards an Agent-based Approach IEEE INDIN 2019; Mayer et al.
Standardized Framework for Evaluating Centralized and Decentralized Control Systems in Modular Assembly Systems IEEE SMC 2019; Mayer et al.

Talks & Outreach

Invited talk, "Interpretive multiplicity reveals disease heterogeneity in biologically informed neural networks", Department of Biomedicine, University of Basel, 06/2026
Interview on the role of AI in science, Konrad-Adenauer-Stiftung, 11/2025

Scholarships and Awards

2026 Anthropic AI for Science credit grant recipient
2023-present: ETH AI Center Associated Researcher
2017-2018: Swiss ERASMUS+ Scholarship for exchange at EPFL

2019-2023: Audi Talents Program
2015-2023: Scholarship at Konrad-Adenauer-Foundation
2015: German Physics Society, award for excellent high school achievements