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
Ăcole polytechnique fĂ©dĂ©rale 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
Publications
Computational Biology
- Species-aware DNA language models capture regulatory elements and their evolution Genome Biology 2023; 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 â 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.
Scholarships and Awards
- 2015-2021: Scholarship at Konrad-Adenauer-Foundation
- 2019: Swiss ERASMUS+ Scholarship for exchange at EPFL
- 2019: Audi Talents Program
- 2015: German Physics Society, award for excellent high school achievements