TOPAS Industriemathematik

Software Engineer

Universität Bremen

Project DiSCO2: 
Urban traffic flow prediction based on deep learning methods.

Project hyBit:
Timeseries (consumption and demand) forecasting for electricity grids using deep learning.

PhD research: 
Evolutionary Neural Architecture Search for traffic flow/speed forecasting.

Scientific Researcher

Data analytics and deep learning for industrial projects (e.g. medical applications -> cancer detection)

Student Research Assistant

I helped SMEs with various projects in AI and data analytics. I worked on tools for image optimization and modification, multi agent frameworks and userfriendly GUI for non-experts. I also helped a small fashion label in data analytics for their campaigns.

AI Consultant

Steinbeis GmbH & Co. KG für Technologietransfer

Digital assistance system for route and energy consumption planning of battery electric vehicles.

Scientific Researcher at Steinbeis Research Center Optimierung, Steuerung und Regelung 

Volkswagen AG

Non-segmantic localisation of autonomous vehicles via artificial intelligence

Research Internship

AI researcher @ University of Bremen, Center for Industrial Mathematics, WG Optimization and Optimal Control | Founder & CEO @ Aiplex

I'm Daniel from Bremen, Germany. I studied industrial mathematics in my bachelor's and master's with a focus on deep learning. I've led the development of a skin cancer detection system as a student researcher throughout my master's. I did my PhD on neural network architecture search.

Next to work I'm a passionate and ambitious triathlete, participating in world championships and becoming world champion in long distance aquabike (which is triathlon without running) in 2022. 

I also love to play chess!

Daniel Klosa

University of Bremen

Project: Hydrogen for Bremen's industrial transformation (hyBit).

Research Lead

Project: Data-based and intelligent simulation of traffic for CO2 reduction in Bremen (DiSCO2-Bremen)

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Daniel Klosa

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