With an interdisciplinary team having a strong background in both theory and practice, we have a wealth of experience in the field of software development and IT project management and are proud to contribute to the advancements of scientific and applied machine learning. We take pride in never losing sight of our customers' goals and attach great importance to designing projects from the outset in such a way that both time and budget constraints are met. Some of our employees contribute remotely from other European countries, but most of us work in our modern office in the heart of Berlin.
We are pleased that our team members regularly contribute to various scientific papers - see a list here.
Our view is that the inflation of existing blackbox solutions on the market is suited only for a subset of the tasks that process automation faces today. This is why we focus on tailoring AI solutions to specific use cases, with a focus on deep technical details and robust deployment.
Dr. Lorenz Richter
CTO & Co-founder
Rustam Antia (PhD)
IntermediatePytorch, Keras, Reinforcement Learning, Functional Programming
ExpertPython, Deep Learning, Derived Algebraic Geometry, Analytical Problem Solving
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.
IntermediatePython, R, Computer Vision, NLP, SQL
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.
ExpertProduct Development, Business Models
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 Bugden (PhD)
IntermediateComputer Vision, Optimization, Tensorflow
ExpertMathematical Modelling, Python, Deep Learning, Pytorch
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.
William Clemens (PhD)
IntermediateNumerical Optimization, Computer Vision, Shell Scripting, R
ExpertCuda, C++, Torch, Tensorflow, Deep Learning, Python, Mathematical Statistics
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.
IntermediateC, C++, Linux, MATLAB, Java, Deep Learning Theory, Cuda
ExpertPython, Monte Carlo Simulation, Time Series Analysis
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.
João Vitor Fonseca
ExpertCommunication, Sales, Digital Governance
After graduating in Administration and Law with stays at Harvard and Brown, João decided to focus on Digitalization and Big Data in an Executive Master at the Hertie School of Governance. With his experience in investment attraction and his excellent communication and negotiation skills, he helps dida achieve its market and sales goals.
IntermediateJava, Python, NLP
ExpertMathematical Modeling, Optimization, Physical Simulations
Due to his studies of mathematics and philosophy (HU Berlin, Uni Bochum) combined with his interest in foreign languages, Fabian is naturally attracted to projects in the field of computational linguistics. Before joining dida, Fabian dealt with physical simulations at Max Planck Institute for iron research and at TU Berlin.
Eva Höning (PhD)
IntermediatePython, Machine / Deep Learning
ExpertAnalytical Problem Solving
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.
IntermediateNumpy, Scipy, R
ExpertPython, SQL, Pandas, Data Analysis, Regression Models
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.
Yan Yan Lau
IntermediateR, Pytorch, Numpy, Stochastics
During her study of maths and computer science at Saarbrücken, Yan Yan discovered her interests in machine learning and stochastics. Fascinated by the rigorous beauty of maths and intrigued by the hidden patterns behind phenomena, she finds machine learning a field where her passion is realized. At dida, she supports the machine learning team in computer vision tasks.
Ma Li (PhD)
IntermediatePython, Deep Learning, C, Computer Vision
ExpertNumber Theory, Analytical Problem Solving, C
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.
Jan Macdonald (PhD)
IntermediateJulia, Pandas, Tensorflow, Keras
ExpertPython, Pytorch, Deep Learning, Inverse Problems, Image Processing
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.
IntermediateBash, C, C++, GO, Java
ExpertPython, Linux, GCP, Docker
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.
Mattes Mollenhauer (PhD)
IntermediateComputer Vision, Signal Processing, Optimal Control
ExpertPython, C++, Applied Probability Theory, Deep Learning, Software Engineering, Nonparametric Models
Mattes obtained his PhD in mathematics at FU Berlin, where he performed research in high-dimensional statistics and machine learning. He has transformed experimental solutions to production software in a variety of applied fields including aerospace engineering, remote sensing and image analysis.
Iaroslava is a computer science student at TU Berlin with a keen interest in machine learning, particularly in the field of natural language processing. Alongside her studies, she supports the machine learning team at dida.
Marty Oelschläger (PhD)
IntermediateC, Python, Fortran, Keras
ExpertNonequilibrium Physics, Asymptotic Methods, Perturbation Theory
During his studies in physics (HU Berlin) Marty investigated optimization and inverse problems, utilizing Python and Fortran. In his PhD thesis (Max Born institute) he focussed on fluctuation-induced phenomena, where he investigated the interplay of classical and quantum statistics. During this time he gained experience in code development and design in C and C++ and developed interest in machine learning. After his PhD he focussed on Deep Learning and Image Recognition.
Thanh Long Phan
IntermediatePytorch, NLP, Computer Vision, Matplotlib
ExpertTensorflow, 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.
Pier Giorgio Rayme
IntermediateCoq/agda, Topological Data Analysis
ExpertPython, NLP, Topology, Logic
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.
Lorenz Richter (PhD)
IntermediateR, Non Convex Optimization, Computer Vision
ExpertStatistical Learning Theory, Deep Learning, Python, Mathematical Statistics, Julia, Tensorflow
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.
ExpertPython, Deep Learning, Bayesian Inference, Brain Modeling, Simulation Based Inference
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.
ExpertPython, Pandas, Numpy, Statistical Data Analysis
After finishing a bachelor degree in mathematics at the University of Porto, Tiago worked on various data science related optimization and automation tasks for a renowned Portuguese manufacturing company.
This experience led him to pursue a master’s in data science at the University of Potsdam. At dida Tiago currently spends most of his time optimizing algorithms for pattern recognition in image data.
IntermediatePytorch, NLP, Haskell
ExpertPython, Computer Vision, Theoretical Physics, Quantum Information Theory
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 Schultka (PhD)
IntermediateNLP, Computer Vision, Optimization, Tensorflow
ExpertProbability Theory, Python, Deep Learning, Pytorch
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.
IntermediateDeep Learning, Software Engineering, Cloud Platforms
ExpertPython, Tensorflow, Explainable AI, Computer Vision
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.
IntermediateSpeech Recognition, Devops, Natural Language Generation, Docker, Spark
ExpertPython, Keras, Tensorflow, NLP, Pytorch, Software Architecture, Spacy, Nltk
After some years in the software industry, Tobias decided to go into consulting. He holds a degree in pure mathematics from HU Berlin. Tobias is experienced in deploying machine learning models into production and he advises us in all things concerning natural text data.
Augusto Stoffel (PhD)
IntermediateTensorflow, Clojure, Java, Statistical Learning, Computer Vision, NLP
ExpertPython, Numpy, Geometry and Topology, Category Theory
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.
IntermediatePython, Pytorch, Fast.ai, Computer Vision
ExpertAirbus A320, Flight Operations
Usually working as an airline pilot, Johannes is currently pursuing a second career in data science. As a Machine Learning Consultant at dida he specializes in remote sensing projects. He helps to identify our customers’ needs and to develop suitable technical solutions.
Sebastian Thomas (PhD)
IntermediateJava, C, C++, Pytorch, Matplotlib, Software Engineering, Machine Learning, Deep Learning, Computer Vision
ExpertPython, Tensorflow, Keras, NLP, Pandas, Scikit Learn, Latex
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.
Petar Tomov (PhD)
IntermediateJava, NLP, Computer Vision, Reinforcement Learning
ExpertPython, ABAP, Tensorflow, Complex Dynamical Systems
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.
Maximilian Trescher (PhD)
IntermediateSoftware Architecture, Scipy, SQL
ExpertPython, Java, Numpy, Pandas, Solid State Physics
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.
Iris van Baarsen
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.