Curriculum Vitae

What I have been up to the last couple of years!

Work experience

2024 - now: Databricks, Inc. | Senior Solutions Engineer

Zurich, Switzerland

Working as a Pre-Sales Senior Solutions Engineer to help customers navigate through the complex data and AI space, architecturing solutions and being a technical advisor.

Programming languages/concepts/tools: Python | SQL | Software Architecture | Data Lakehouse | Big Data and AI.

2023 - 2024: Transcality | Head of Data Science

Zurich, Switzerland

Building up a data science team and working on full-stack data science projects. Helping to build/mainting/improve Transcality's software engineering workflows. Transcality is an ETH-spinoff, details here

Programming languages/concepts/tools: Python | Deep Learning | Object-oriented Programming (OOP).

2023 - 2023: ETH Zurich | Postdoctoral researcher

Zurich, Switzerland

Research focusing on machine and deep learning in transportation. Teaching and proposal duties at the IVT, ETH.

Programming languages/concepts/tools: Python | Deep Learning | Object-oriented Programming (OOP).

2018 - 2022: ETH Zurich | Research assistant

Zurich, Switzerland

Research focusing on traffic prediction and optimization problems with data sets and utilizing traffic models. Also involved in research projects on intelligent mobility infrastructure funded by Swiss transport authorities and municipalities. Teaching assistant in BSc. and MSc. courses.

Programming languages/concepts/tools: Python | Machine Learning | Object-oriented Programming (OOP) | MATLAB | R.

2015 - 2018: Austrian Institute of Technology (AIT) | Student researcher

Vienna, Austria

Simulation framework development in MATLAB to investigate automated driving systems and the interplay with transportation infrastructure, precisely collision avoidance and ride comfort. Involvement in national/international research projects with GPS data: Data cleaning, analysis, and visualization tasks.

Programming languages/concepts/tools: Python | MATLAB.

Education

2018 - 2022: ETH Zurich | Dr. sc.

Major: Civiling Engineering with focus on Machine Learning and Data Science in Traffic Engineering

Zurich, Switzerland

2016 - 2018: University of Natural Resources and Life Sciences Vienna (BOKU) | MSc.

Major: Civil engineering and water management

Vienna, Austria

2012 - 2016: University of Natural Resources and Life Sciences Vienna (BOKU) | BSc.

Major: Environmental and bio-resource engineering

Vienna, Austria

2012 - 2019: 80 ECTS completed computer science courses at TU Graz, Chalmers, ETH.

Vienna, Austria, Gothenburg, Sweden, Zurich, Switzerland

Publication list

Also check out my Google Scholar or ResearchGate

Journal publications

Genser, A., Makridis, M., Yang, K., Ambühl, L., Menendez, M., and Kouvelas, A. (2023). A traffic signal and loop detector dataset of an urban intersection regulated by a fully actuated signal control system. Data in Brief, 48, 109117.

Genser, A., & Kouvelas, A. (2022). Dynamic optimal congestion pricing in multi-region urban networks by application of a multi-layer-neural network. Transportation Research Part C: Emerging Technologies, 134, 103485.

Genser, A., Spielhofer, R., Nitsche, P., & Kouvelas, A. (2022). Ride comfort assessment for automated vehicles utilizing a road surface model and monte carlo simulations. Computer-Aided Civil and Infrastructure Engineering, 37(10), 1316.

Genser, A., Makridis, M., Yang, K., Ambühl, L., Menendez, M., and Kouvelas, A. (2022). Time-to-Green predictions for fully-actuated signal control systems with supervised learning, IEEE Transactions on Intelligent Transportation Systems.

Genser, A., Hautle, N., Makridis, M., & Kouvelas, A. (2021). An experimental urban case study with various data sources and a model for traffic estimation. Sensors, 22(1), 144.

Chavoshi, K., Genser, A., & Kouvelas, A. (2021). A pairing algorithm for conflict-free crossings of automated vehicles at lightless intersections. Electronics, 10(14), 1702.

Conference publications

Genser, A., Makridis, M., & Kouvelas, A. (2022). Exploiting deep learning and traffic models for freeway traffic estimation. 4th Symposium on Management of Future Motorway and Urban Traffic Systems (MFTS 2022). Dresden, Germany.

Genser, A., Hautle, N., Makridis, M., & Kouvelas, A. (2022). An experimental urban case study with various data sources and a model for traffic estimation. In: 101th Annual Meeting of the Transportation Research Board (TRB 2022). The National Academies of Sciences, Engineering, and Medicine.

Genser, A., Makridis, M., & Kouvelas, A. (2022). Real-time traffic state estimation with the application of deep learning techniques. In: 22nd Swiss Transport Research Conference (STRC 2022). STRC.

Genser, A., & Kouvelas, A. (2020). Optimum route guidance in multi-region networks: A linear approach. In: 99th Annual Meeting of the Transportation Research Board: New Mobility and Transportation Technology Takeaways (TRB 2020). The National Academies of Sciences, Engineering, and Medicine.

Genser, A., Ambühl, L., Yang, K., Menendez, M., & Kouvelas, A. (2020). Time-to-green predictions: A framework to enhance spat messages using machine learning. In: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC). IEEE.

Genser, A., Ambühl, L., Yang, K., Menendez, M., & Kouvelas, A. (2020). Enhancement of spat-messages with machine learning based time-to-green predictions. In: 9th Symposium of the European Association for Research in Transportation (hEART 2020). European Association for Research in Transportation.

Genser, A., & Kouvelas, A. (2020). Route-choice management with optimal dynamic pricing in urban large-scale networks. In: 20th Swiss Transport Research Conference (STRC 2020)(virtual). STRC.

Genser, A., Nitsche, P., & Kouvelas, A. (2019). Identification of critical ride comfort sections by use of a validated vehicle model and monte carlo simulations. In: 2019 IEEE intelligent transportation systems conference (ITSC). IEEE. 2019, 1644.

Genser, A., & Kouvelas, A. (2019). Dynamic congestion pricing for multi-region networks: A traffic equilibria approach. In: 19th Swiss Transport Research Conference (STRC 2019). STRC.

Nitsche, P., Welsh, R. H., Genser, A., & Thomas, P. D. (2018). A novel, modular validation framework for collision avoidance of automated vehicles at road junctions. In: 2018 21st international conference on intelligent transportation systems (ITSC). IEEE. 2018, 90.

Other contributions:

Genser, A. (2022). Predicting time-to-green of fully-actuated signal control systems with deep learning models.

Genser, A., Makridis, M., & Kouvelas, A. (2022). Optflow: Schätzung der reisezeit mit flir kamerasensoren. ETH Zurich.

Genser, A., Neuenschwander, M., & Kouvelas, A. (2020). Wirkungsanalyse selbst-steuerung. ETH Zurich.

Genser, A., Makridis, M., Yang, K., Ambühl, L., Menendez, M., & Kouvelas, A. (2022). A traffic signal and loop detector dataset of an urban intersection regulated by a fully actuated signal control system.

Karrer, T., Bartsch, M., Genser, A., Lämmer, S., & Heimgartner, C. (2021). Praxistest in Luzern zeigt: Selbststeuerung verbessert die Verkehrsqualität deutlich. Schweizerischer Verband der Strassen-und Verkehrsfachleute (VSS).

Featured projects

Dynamic congestion pricing framework based on traffic equilibria

A dynamic pricing method for an urban large-scale network based on traffic equilibria and deep learning.

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Traffic state estimation with a physics-informed deep learning model

Using traditional traffic models and deep learning to enhance traffic state estimation on freeways.

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