Radek Mackowiak

Provided strategic oversight, led board meetings, and supported executive leadership in defining and achieving the company’s long-term goals.

Co-founded and led Copresence as CEO, building an AI computer-vision product from inception and assembling a team of IT experts across Switzerland and Germany.

Conducted computer vision research and authored scientific publications for conferences including CVPR and NeurIPS.

Led a 2D/3D analytics project focused on reconstructing power lines from aerial imagery data.

Directed development of a 2D/3D analytics pipeline to reconstruct power lines in 3D from aerial imagery.

Led research on smart data selection methods to build cost-effective machine-learning-based systems in an international, cross-time-zone project.

Led research on smart data selection methods for cost-effective machine-learning systems in an international setup across CET and PDT.

Performed computer vision research for autonomous driving, focusing on active learning, uncertainty estimation, and building trustworthy deep learning models for safe AI.

Conducted computer vision research for autonomous driving, focusing on active learning, reliable uncertainty estimation, and improving the trustworthiness of deep learning classification models.

Taught students how to implement effective image processing algorithms.

Taught students how to implement effective image processing algorithms.

Developed a custom deep learning-based inference pipeline.

Tutored students on implementing classic algorithms, standard data structures, and software engineering concepts.

Supported students by teaching classic algorithms, standard data structures, and core software engineering concepts.

Worked on Project VIRPA, developing state-of-the-art visual feature extraction techniques and implementing UX navigation concepts.

Developed state-of-the-art techniques for visual feature extraction from images and implemented UX navigation concepts for large video data.

Developed a RESTful web API and trained new employees on IT project management practices.

Developed a RESTful web API and helped train new employees on project management in IT.

Built UX navigation concepts to visually explore large linked text databases.

Developed an OpenGL-based iOS application to visualize high-dimensional plenoptic functions from light-field camera systems.

Developed an OpenGL-based iOS application as part of a bachelor thesis visualizing high-dimensional plenoptic functions from light-field camera systems.

Built an iOS client and a corresponding RESTful web API as a full-stack development effort.

Developed multiple iOS applications and optimized existing iOS applications.

Developed static web sites and database-driven web applications.

Activities and societies: Work included contributions to pedestrian intention recognition and dense depth estimation from light field data.

Industrial PhD candidate at Heidelberg University (HCI) conducting machine learning and computer vision research for autonomous driving and safe AI.

Industrial PhD Candidate focusing on Machine Learning and Computer Vision at Technische Universität Dresden from 2016 to 2019.

Activities and societies: Research included active learning, reliable uncertainty estimation, and improving trustworthiness of deep learning-based classification models for safer AI.

Industrial PhD candidate at TU Dresden focusing on machine learning and computer vision research for autonomous driving and safe AI.

Grade: A

Bachelor of Science in Computer Science & Digital Media (specialization: Signal/Image Processing) at HTW Berlin, grade A.

Completed Deep Learning Summer School 2016 at Université de Montréal.

Grade: A

Master of Science in Computer Science & Digital Media (specialization: Machine Learning, Computer Vision, Image Retrieval) at HTW Berlin, grade A.

Grade: 98.2%

Completed the Stanford/ Coursera online Machine Learning course (ml-class.org), grade 98.2%.

Grade: 98.2%

Completed the Machine Learning online course (ml-class.org) provided via Coursera/Stanford University with a grade of 98.2%.

Completed Deep Learning Summer School 2016 at Université de Montréal (CIFAR organizer).

Vocational training program for a Media Operator (Multi Media) at Multi Media Berufsbildende Schulen in Hannover.

Completed Media Operator vocational training at Multi Media Berufsbildende Schulen in Hannover.

Attended St.Ursula-Schule in Hannover from 1999 to 2006.