About us

After his studies of mathematics with a minor in theoretical physics at the Goethe University of Frankfurt Rustam honed his analytical problem solving skills completing a PhD at the University of Texas at Austin where he did research in derived algebraic geometry. Looking for new challenges in the real-world he turned to machine learning. At dida he now specializes in deep learning and in particular computer vision.

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.

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.

Since his Master studies in business administration at HU Berlin, David’s focus has always been on working with technological products and services. Typically, on the interface of development and management, before joining dida, he gained experiences as a data scientist. Now he is supporting the dida machine learning team in gaining visibility and obtaining exciting projects.

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.

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.

Yana is a business informatics student at TU Berlin where she developed a keen interest in statistics which, combined with her enthusiasm for languages, led her to Natural Language Processing at dida.

Will developed his mathematical and coding skills during his studies in theoretical physics at Warwick and Cambridge Universities. Before joining dida, he did his PhD in string theory and quantum chromodynamics at the University of Southampton. Currently, Will specializes in computer vision.

While studying theoretical physics at the Humboldt University of Berlin, Fabian specializes in numerical simulation and machine learning tools, as well as their applicability for quantitative physics problems. As a scientific assistant at the Max-Planck Institute of Light, he has gathered experience in applying these techniques to simulation data of a quantum optical hardware setup. Being particularly interested in mathematical insight and explainability, at dida he supports the machine learning team.

Markus is a physicist and entrepreneur with a deep understanding of mathematics, statistics, and machine learning. He leverages his unique background to guide dida’s clients toward data-driven solutions that optimize their operations and maximize impact.
Prior to dida, Markus founded the programmatic buying platform realzeit and focused on software and deep tech investments at the venture capital firms Nauta Capital and DTCF.

Nico Enghardt is a Physics Student at FU Berlin with a passion for clever model design, driven by a challenge’s constraints. He aims to maximize the impact of a solution while using small and efficient models. Thus he helps our team solving real-world problems with state-of-the-art methods.

Carmen is a design and digital creation student at UOC (Universitat Oberta de Catalunya). With a keen eye for detail and a strong interest in Machine Learning, at dida Carmen collaborates with the Marketing Team to create compelling visuals.

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.

Mary is a Computational Engineering Science student at TU Berlin with experience in data analysis and a strong interest in machine learning, NLP and cloud computing. Alongside her studies, she supports smartextract’s team.

Liel wrote their PhD in theoretical Physics, at the Niels Bohr Institute in Copenhagen, and subsequently spent many years moving around Europe as a Postdoc. In this time they worked on different problems in quantum gravity, always using computer simulations to understand the behavior of the model. Now, Liel decided to change tracks and is excited to explore machine learning and solve real world problems.

Sevval is a Business Informatics student at TU Berlin. She’s particularly enthusiastic about developing innovative marketing strategies for machine learning products, showcasing her unique blend of business and technical skills. With a genuine interest in AI and technology, she brings a fresh perspective to our team, helping to drive creative marketing solutions.

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.

While studying Physics at Bogazici University, Kutay focused on theoretical physics and entered the field of machine learning through his involvement in a university research group. He worked on a range of machine learning projects, enhancing his skills in data handling, model training, and analysis. Currently, as a master’s student at Freie University in Berlin, Kutay continues to explore the intersection of computational physics and machine learning. Alongside his studies, he supports the machine learning team at dida.

Philipp advises our customers on which processes to automate. He makes sure that the value-add of the project materializes as planned. Before founding dida, the statistician (TU Berlin) was part of the management team which grew Beko Käuferportal GmbH from a small startup to 300+ employees.

Manu has nurtured a strong passion for Governance and Public Policy during his Masters studies at the University of Passau. His theoretical knowledge of the political process is further enriched by practical experience in various German public institutions. At dida, Manu supports the growth of the “Public Sector” field by contributing insights on strategy and innovation.

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”.

Laura studies Mathematics at the Technical University of Berlin. She deepens her knowledge in the machine learning team at dida.

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.

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.

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.

Philipp completed his bachelor’s studies in Computer Science at Leipzig, specializing in Natural Language Processing. His interest in foreign languages motivated him to study Italian philology for a year. Currently, he is pursuing a master’s degree in general Computer Science, with a focus on machine learning.

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.

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.

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.

During his studies of physics (FU Berlin) Emil developed his passion for machine learning, computational neuroscience and medical engineering. In his master thesis at Charité Berlin, he developed Bayesian Inference methods for whole-brain models and simulations. At dida he supports the sales team in the acquisition of new ML projects and strategic research collaborations.

Jakob studied Theoretical Physics (Uni Heidelberg) and worked on the intersection of quantum information theory and thermodynamics. He then discovered his enjoyment of programming and his interest in machine learning. At dida, he works in computer vision and with time series data from production processes.

Konrad cultivated his mathematical modeling skills while studying at HU Berlin. A graduate scholarship from Berlin Mathematical School led him to investigate the mathematical foundations of quantum fields. After transitioning from the quantum to the classical world, his interests have shifted to the analysis of probabilistic models and deep neural networks.

Anton is fascinated by the breakthroughs of Representation Learning and is passionate about driving AI innovation for common good. Having a broad profile, Anton has interest in latest research, recognizes the importance of building robust machine learning systems and keeps an eye on business requirements.

Ilia has a background in physics and additional profound knowledge in data analysis and web development. At dida, he is responsible for the front-end infrastructure of our software products. Following key principles of frontend development such as responsive and intuitive design, accessibility, and high performance, he strives to create an ideal user experience.

Augusto studied computer engineering in Brazil and holds a PhD in mathematics (University of Notre Dame, USA) on the role of algebraic topology as a foundation of quantum field theory. At dida, he works on NLP applications, including everything from research to backend development.

Marcin is a Mathematics Master’s student at HU-Berlin specializing in mathematical statistics and stochastic processes. He’s especially enthusiastic about finding real-world applications of complex mathematical concepts. This, together with his interests in computer science and linguistics, led him to machine learning.

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.

After his studies in physics (FU Berlin, UPMC and ENS Paris), Max obtained his PhD in theoretical quantum and solid state physics (FU Berlin). His knowledge in scientific programming has been complemented by experience in software architecture and development through his work in the software industry. At dida he works as a Machine Learning Scientist at the interface of science and software development.

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.

Isabell earned her PhD in stochastic analysis from TU Berlin and subsequently pursued a postdoctoral position. Seeking a more practical and impactful direction, she transitioned into the field of machine learning. At dida, she works as a Machine Learning Scientist, leveraging her expertise to contribute to innovative solutions.