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About us

Our team has a wealth of experience in the field of software development and IT project management. 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.
Our team members regularly contribute to various scientific papers. See a list here.
Our customers

We are an interdisciplinary team to ensure a diversity of knowledge

Rustam Antia (PhD)

Intermediate

Pytorch, Keras, Reinforcement Learning, Functional Programming

Expert

Python, 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.

David Berscheid

Intermediate

Python, R, NLP, Computer Vision

Expert

Angular, Javascript, Nosql

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, frontend developer and co-founder of deep choice. Now he is supporting the dida machine learning team in gaining visibility and obtaining exciting projects.

Moritz Besser

Intermediate

C++, Pandas, Deep Learning, Tensorflow, Computer Vision, NLP

Expert

Labview, Python, Data Analysis, Solid State Physics, Extreme Conditions Experimental Physics

During the whole of his studies of experimental physics at the TU Dresden Moritz was working at the Max Planck Institute (CPfS) in the extreme conditions lab. Besides giving him a profound technical understanding it made him an expert in LabVIEW and the field of solid state research. His fascination for Machine Learning and a genuine ability to explain complex matters makes him the perfect bridge between the industry and our expert technicians.

Michael Borinsky (PhD)

Intermediate

Opencv, Tensorflow

Expert

C++, Python, Mathematical Statistics, Scipy, Opengl, Computer Vision

While studying physics at HU Berlin, Michael was already contributing to CERN’s Root data analysis framework. With his coding abilities and his mathematical skills obtained during his dissertation in quantum physics, he supports the machine learning team.

Felix Brunner

Intermediate

Tensorflow, Numpy, Scipy, Scikit Learn

Expert

Python, Pandas, Econometrics

Felix has a background in Economics and Finance and is currently working towards his PhD in the field. Over the course of his studies, he developed a strong interest in machine learning, which led him to deepen his data science and programming skills. Prior to joining dida, he has already collected practical insights into management consulting and quantitative finance.

William Clemens (PhD)

Intermediate

Numerical Optimization, Computer Vision, Shell Scripting, R

Expert

Cuda, 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.

Fabian Dechent

Intermediate

C++, C++, Linux, MATLAB, Java, Deep Learning Theory, Cuda

Expert

Python, 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.

Adrian Dietlein (PhD)

Intermediate

Python, MATLAB, Quantitative Finance

Expert

Machine Learning, Mathematical Modeling, NLP

Adrian has a background in Mathematics, with a PhD from LMU Munich and a PostDoc at IST Austria. Within his research, he investigated problems in Mathematical Quantum Mechanics. After leaving academia, Adrian worked in asset management as a quantitative strategist. During this time he developed a strong interest in modern statistical modelling and machine learning. At dida, Adrian supports the machine learning team in NLP tasks.

David Djambazov

Intermediate

NLP, Pyspark, Tensorflow, R

Expert

Python, Numpy, Film Editing, Communication

Combining a data science Master’s degree from UC Berkeley with an eye for good storytelling, David has an unusual background. After looking for gravitational waves at Caltech as a Physics major, he moved to a Wall Street bond trading desk before pursuing a media and filmmaking career that saw him dive into a diverse set of subjects. Machine Learning projects he has worked on include, among others, non-English NLP problems and computer vision methods applied to satellite data. At dida he is excited to learn about clients’ needs and explore smart solutions in a sales, communication and technical capacity.

João Vitor Fonseca

Intermediate

Python, C++

Expert

Communication, 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.

Astrid Gansekow

Acting as the point of contact among executives, employees, clients and other external partners, Astrid is responsible for managing the information flow at dida. After some years as an Executive Assistant in the software sector she’s supporting us with her experienced organizational and accounting skills.

Maximilian Glass

Intermediate

Graphql, Java, Python, C#, R

Expert

UI, UX, Typescript, Vue.js

Max makes sure that users are able to interact intuitively with our software products. As full-stack developer/UX designer in one, he constantly strives to combine clean designs with uncompromising functionality.

Fabian Gringel

Intermediate

Java, Python, NLP

Expert

Mathematical 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.

Ana Guerra

Intermediate

Java, Python, NLP, Machine Learning, Annotation Tools

Expert

Brazilian Law

Ana has a background in law and linguistics and is currently doing her masters in computational linguistics, machine learning and artificial intelligence. Inspired by a fascination for language and learning, Ana developed an interest in combining law and technology. While doing her master’s at the University of Potsdam, she supports our data management team.

Philipp Jackmuth

Intermediate

Numpy, Scipy, R

Expert

Python, 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

Intermediate

R, Pytorch, Numpy, Stochastics

Expert

Python, MATLAB

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.

Angela Maennel

Intermediate

Python, Numpy, Computer Vision

Expert

Tensorflow, Symplectic Topology, Analytical Problem Solving

After finishing her master’s degree in mathematics at ETH Zürich with honors, Angela continued her studies abroad in Hong Kong and the US. During this time, her interest gradually turned to machine learning and she specialized into the field. At dida Angela enjoys applying her analytical problem solving skills to natural language processing and computer vision tasks which fascinate her.

Kirsten Matthias

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.

Lorenzo Melchior

Intermediate

Tensorflow, C++, C++, Java, R

Expert

Python, Pytorch, Numpy, Pandas, Linux

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)

Intermediate

Computer Vision, Signal Processing, Optimal Control

Expert

Python, C++, Applied Probability Theory, Deep Learning, Software Engineering, Nonparametric Models

After his studies of mathematics (FU Berlin), Mattes is currently pursuing his Phd doing research on machine learning models for time series problems in physics and signal processing. He has been involved in several large AI projects and is experienced in transforming recent research results and experimental solutions to production software.

Konrad Mundinger

Intermediate

Statistical Learning Theory, Python, Tensorflow, Pytorch

Expert

Stochastic Analysis, Probability Theory, Deep Learning, Numpy

During his studies of mathematics (TU Berlin) with a focus on probability theory and functional analysis, Konrad found that the most beautiful applications of these mathematical branches lie in the field of machine learning. Always striving for a profound mathematical understanding of the algorithms and ideas behind them, he now supports the machine learning team at dida in NLP and computer vision tasks.

Marty Oelschläger (PhD)

Intermediate

C++, C++, Python, Fortran, Keras

Expert

Nonequilibrium 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.

Pier Giorgio Rayme

Intermediate

Coq/agda, Topological Data Analysis

Expert

Python, 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.

Emilius Richter

Intermediate

Deep Learning, Tensorflow, Keras, SQL

Expert

Python, MATLAB

During his studies of physics (FU Berlin) Emil developed his passion for machine learning, biophysics, and medical engineering. He worked as a software developer for an MRI research group, where he could apply his skills in deep learning to medical breathing scans. At dida he supports the Sales team in technical questions and in the acquisition of new ML projects.

Lorenz Richter (PhD)

Intermediate

R, Non Convex Optimization, Computer Vision

Expert

Statistical 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.

Tiago Sanona

Intermediate

Pyspark

Expert

Python, 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.

Till Schäfer

Intermediate

Pytorch, Julia, Numerical Optimization

Expert

High Dimensional Statistics and Probability Theory, Nonlinear Optimization, Python

During his studies of mathematics at the HU Berlin, Till developed an affinity for statistical and optimization problems. The attraction for him lies in understanding and discovering the mathematical theory on the one hand, and in bringing the problem in a computer-readable form, on the other. Through his one and a half years of work at the WIAS Berlin, he was able to deepen both his programming skills and his scientific approach.

Jakob Scharlau

Intermediate

Pytorch, NLP, Haskell

Expert

Python, 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)

Intermediate

NLP, Computer Vision, Optimization, Tensorflow

Expert

Probability 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.

Tobias Sterbak

Intermediate

Speech Recognition, Devops, Natural Language Generation, Docker, Spark

Expert

Python, 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)

Intermediate

Tensorflow, Clojure, Java, Statistical Learning, Computer Vision, NLP

Expert

Python, 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.

Johannes Stutz

Intermediate

Python, Pytorch, Fast.ai, Computer Vision

Expert

Airbus 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)

Intermediate

Java, C++, C++, Pytorch, Matplotlib, Software Engineering, Machine Learning, Deep Learning, Computer Vision

Expert

Python, 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)

Intermediate

Java, NLP, Computer Vision, Reinforcement Learning

Expert

Python, 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.

Frank Weilandt (PhD)

Intermediate

Deep Learning, Keras, NLP, Computer Vision

Expert

C++, Python, Topological Data Analysis

After studying mathematics at the University of Bonn, Frank used Python and C++ for data analysis in several research groups: For computer vision at a Fraunhofer Institute in Sankt Augustin, during his PhD studies about the numerical simulation of dynamical systems in Cracow, Poland, and as a Post-doc for topological data analysis in Bremen. Having taught programming in Polish, his next challenge is teaching computers to understand language.

Jona Welsch

Intermediate

Pytorch, Computer Vision, Pandas, C++, NLP

Expert

Python, Tensorflow, Numpy, Scipy, Semantic Segmentation, OOP

During his studies in physics (TU Dresden, Heidelberg University) Jona was able to acquire skills in imaging, numerical methods, and machine learning. He worked on optimisation methods at the German Cancer Research Center and did research on the explainability of Deep Learning models at Heidelberg University. Before his time at dida, Jona worked at a global IT consultancy and led the development of a Deep Learning product for radiology.

Daniel Zuares

A graphic designer with previous experience working as a marketing writer in the startup industry. Daniel approaches visual design from the viewpoint of content with emphasis on storytelling and aesthetic experience. His educational background includes Master of Arts in English and History at the University of London (UCL) and 2 years professional training in design for branding at Shenkar College for Design.

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