DIDA DATENSCHMIEDE - Key Persons
After graduating in psycholinguistics, Arne gained experience in various management and leadership positions. He can look back on many years of work experience in various industries (IT, automotive, insurance, banking) with small and medium-sized companies as well as corporations. With his passion for successful communication, Arne always looks for the best solution to current challenges depending on the situation and context. He loves working with people, both on the customer side in his role as Key Account Manager, as well as dida internally in the further development of our teams and the organization as a whole.
Augusto studied computer engineering in Brazil and holds a PhD in mathematics (University of Notre Dame, USA). Before joining dida, he was a postdoc in Bonn and Greifswald, doing research in the field of algebraic topology and its application as a foundation of quantum field theory.
Axel is a skilled product professional who excels in developing and launching innovative software solutions to solve complex business problems. With extensive experience in both product management and business development, he has a proven track record of leading cross-functional teams and driving growth for B2B SaaS companies. He holds a Master's degree in Digital Media Technology from TU Ilmenau, providing him with a well-rounded understanding of both the technical and business aspects of product development.
Organizational and behavioral psychology have been Bela's main interests since he started studying psychology. His working method is driven by the idea of combining scientific standards and advances with their applicability in the real world. As a working student at dida, he realizes this approach and supports in all areas of personal and organizational development.
Job Titles:
- Expert / Adobe Creative Suite
With an original focus on stochastics and numerics (FU Berlin), the mathematician has been dealing with deep learning algorithms for some time now. Besides his interest in the theory, he has practically solved multiple data science problems in the last 10 years. Lorenz leads the machine learning team.
After completing her PhD in algebraic topology at Université Paris 13, Eva was a postdoc at the Max Planck Institute in Bonn and in the Netherlands.
Looking for interesting applications in the real world, Eva got into machine learning. At dida, she now works as a Machine Learning Scientist.
As a graduate in business administration, Iris has many years of professional and management experience in the field of human resources. She has worked in large and medium-sized companies and is responsible for recruiting and organizational development at dida. In addition, she has been working as a business coach for more than ten years and supports dida in individual topics.
During his studies in mathematics (TU Berlin) Jan focussed on applied topics in optimization, functional analysis, and image processing. His doctoral studies (TU Berlin) explored the interplay between theoretical and empirical research on neural networks. This resulted in his PhD thesis investigating the reliability of deep learning for imaging and computer vision tasks in terms of interpretability, robustness, and accuracy. At dida he works as a Machine Learning Researcher at the interface of scientific research and software development.
As a graduate in engineering and business (M.Sc., RWTH Aachen), Julius bridges the gap between technology and its application. Julius has several years of management experience in tech companies and coordinated a funding program for technology spin-offs for a university association. At dida, Julius develops the business field "Public Sector".
After working for several years at Scientific Publishing Houses (Springer Verlag, de Gruyter, here: Purchase, Production, Online Producing), Kirsten worked in the accounting and tax department for 11 years. A main interest of hers is the automation of accounting processes, where she can rely on her experiences as an application developer (Electronic Publishing). She sees accounting as data processing out of multiple sources rather than as the result of multiple single steps.
During his studies in mathematics and computer science [FU Berlin], Lorenzo found his passion for machine learning and statistics. He is experienced in image recognition, regression problems and in working with time series data. His dev-ops skills earn him regular praise by his collegues.
After receiving his PhD from University Paris VI, Ma Li worked for several years as a number theorist at Bielefeld University. He gradually turned his interest to areas with more real-world applications and is now pursuing a career in Deep Learning.
With a background in translation and a fresh passion for coding, Mariangela brings a unique perspective to front-end development. Adhering to key principles of front-end development, such as responsive layouts, smooth user interactions, and accessibility, she actively contributes to ensuring each project is executed with precision. Mariangela is committed to reshaping how users interact with our software, emphasizing both functionality and an enjoyable journey.
Mark has a background in mathematics and physics, completing his PhD in String Theory and higher-dimensional black holes (Australian National University, Canberra). During postdocs in the Czech Republic (Charles University, Prague) and Germany (Max Planck Institute, Konstanz), he developed an interest in, and experience with, neural networks and machine learning. At dida he works as a Machine Learning Scientist, bridging the gap between theoretical and practical.
During their studies in physics (HU Berlin) Marty investigated optimization and inverse problems, utilizing Python and Fortran. In their PhD thesis (Max Born institute) they focused on fluctuation-induced phenomena, where they investigated the interplay of classical and quantum statistics. During this time they gained experience in code development and design in C, C++, and Python and developed interest in machine learning. After their PhD they focused on Deep Learning and works at dida in the role as ML Scientist as well as Project Lead and Project Manager.
Nicole brings her passion for efficient workflows and extensive experience in Quality Management from the E-Commerce sector into the realms of personnel and office management. Her interdisciplinary studies in Culture and Technology provide the foundation for a versatile approach to addressing operational challenges.
After his studies (LMU München) and PhD (HU Berlin) in theoretical physics, Petar worked for several years as an IT consultant with projects at different DAX companies. In the last years he developed his passion for machine learning and specialized in this field. Petar is supporting the machine learning team as a developer and project manager.
Pier studied mathematics in Bologna and Bonn and graduated with a thesis in homotopy theory. His interest in philosophy of language as well as topological data analysis (TDA) led him to investigate the mathematical foundations of machine learning and interesting applications of TDA to NLP. Besides working at dida, he is pursuing a second master's degree in Cognitive Systems in Potsdam.
Job Titles:
- Pytorch, Keras, Reinforcement Learning, Functional Programming / Expert
Sebastian studied and received his PhD in mathematics at RWTH Aachen University, specializing in abstract homotopy theory. As a lecturer, he held lectures and tutorials at TU Dortmund, at C.v.O. University of Oldenburg as well as at his alma mater, in particular for computer science students. Since his school days, he has also had a passion for languages. From these experiences and interests Sebastian developed strong competencies in computer science, machine learning and NLP, which he uses to support dida's machine learning team.
Job Titles:
- Expert / Tensorflow, Python, Numpy, Pandas, Functional Analysis
During his studies of mathematics (HU Berlin) with a focus on differential geometry and functional analysis, Long developed his passion for programming. In his Master thesis he focused on Image Processing, where he investigated the existence of a solution for a minimization problem. In the process, he discovered his interest in machine learning.