Curriculum Vitae

tatarchm@gmail.com | +4915788159993

EDUCATION

Albert-Ludwigs-Universität Freiburg Jan. 2016 — Feb. 2020
PhD (summa cum laude) in Computer Science
Computer Vision Lab, advisor Prof. Dr.-Ing. Thomas Brox
Final grade 0.0, with distinction

Albert-Ludwigs-Universität Freiburg Oct. 2012 — Mar. 2013
Master in Computer Science Apr. 2014 — Dec. 2015
Final grade 1.0, with distinction

“MATI” - K. I. Tsiolkovsky Russian State Technological University Oct. 2012 — Mar. 2013
Bachelor in Applied Mathematics and Informatics
Final grade 4,8, with distinction

PROFESSIONAL EXPERIENCE

Bosch, Renningen, Germany Nov. 2023 — now
Lead Research Scientist
AI Research Department

Bosch, Renningen, Germany May. 2020 — Oct. 2023
Research Scientist
AI Research Department

Albert-Ludwigs-Universität Freiburg, Germany Jan. 2016 — Feb. 2020
Research Assistant
Computer Vision Lab

Intel Labs, Santa Clara, USA May. 2017 — Nov. 2017
Research Intern
Intelligent Systems Lab, advisor Dr. Vladlen Koltun

Albert-Ludwigs-Universität Freiburg, Germany Jun. 2014 — Dec. 2015
Student Research Assistant
Autonomous Intelligent Systems Lab

GPSCOM, Moscow, Russia Dec. 2011 — Apr. 2014
Software Engineer

Crechet corp., Moscow, Russia Jun. 2011 — Dec. 2011
Software Developer

PUBLICATIONS

Google scholar citations: 4122.

Not including publications in Russian prior to 2015.

Referred papers

  1. B. M. Öcal, M. Tatarchenko, S. Karaoğlu and T. Gevers “SceneTeller: Language-to-3D Scene Generation” In ECCV, 2024

  2. R. Velastegui, M. Tatarchenko, S. Karaoğlu and T. Gevers “Image semantic segmentation of indoor scenes: A survey” In CVIU, 2024

  3. J. Kälble, S. Wirges, M. Tatarchenko and E. Ilg “Accurate Training Data for Occupancy Map Prediction in Automated Driving using Evidence Theory” In CVPR, 2024

  4. M. Tatarchenko, K. Rambach “Histogram-based Deep Learning for Automotive Radar.” In RadarConf, 2023

  5. J. Bechtold, M. Tatarchenko, V. Fischer and T. Brox “Fostering Generalization in Single-view 3D Reconstruction by Learning a Hierarchy of Local and Global Shape Priors.” In CVPR, 2021

  6. S. Mittal, M. Tatarchenko and T. Brox. “Semi-supervised semantic segmentation with high- and low-level consistency.” In TPAMI, 2019

  7. O. Mees, M. Tatarchenko, T. Brox and W. Burgard. “Self-supervised 3d shape and viewpoint estimation from single images.” In IROS, 2019

  8. M. Tatarchenko, S. R. Richter, R. Ranftl, Z. Li, V. Koltun, and T. Brox. “What do single-view 3d reconstruction networks learn?” In CVPR, 2019

  9. A. Böhm, M. Tatarchenko, and T. Falk. “ISOO^V2_DL - semantic instance segmentation of touching and overlapping objects.” In ISBI, 2019

  10. M. Tatarchenko, J. Park, V. Koltun, and Q.-Y. Zhou. “Tangent convolutions for dense prediction in 3d.” In CVPR, 2018 (Selected for spotlight oral)

  11. A. Dosovitskiy, J. T. Springenberg, M. Tatarchenko, and T. Brox. “Learning to generate chairs, tables and cars with convolutional networks.” TPAMI, Apr 2017

  12. M. Tatarchenko, A. Dosovitskiy, and T. Brox. “Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs.” In ICCV, 2017

  13. M. Tatarchenko, A. Dosovitskiy, and T. Brox. “Multi-view 3d models from single images with a convolutional network.” In ECCV, 2016 (Selected for spotlight oral)

  14. B. Frank, M. Ruhnke, M. Tatarchenko, and W. Burgard. “3d-reconstruction of indoor environments from human activity.” In ICRA, 2015

Preprints

  1. B. M. Öcal, M. Tatarchenko, S. Karaoğlu and T. Gevers “RealDiff: Real-world 3D Shape Completion using Self-Supervised Diffusion Models” In arXiv:2409.10180, 2024

  2. S. Mittal, M. Tatarchenko, Özgün Çiçek and T. Brox. “Parting with Illusions about Deep Active Learning.” In arXiv:1912.05361, 2019

Theses

  1. “Scalable 3D deep learning: methods and applications”, PhD thesis, 2020

  2. “Generating unseen views of objects with convolutional networks”, Master’s thesis, 2015

PROFESSIONAL SERVICES

Reviewer for IROS’18, ICCV’18, CVPR’18, CVPR’19 (outstanding reviewer), TPAMI’19, CVPR’20, IJCV’20, CVPR’21 (outstanding reviewer), RA-L’21, TPAMI’21, TPAMI’22, CVPR’23, CVPR’24

AWARDS

VDI-Förderpreis 2016
Sponsorship award of the Association of German Engineers
Awarded for the master’s thesis

MEDIA COVERAGE

3sat: Scobel 2016
TV program about AI
Mentioned the work “Multi-view 3D models from single images with CNNs”

PATENTS

Computer-implemented method and system for reconstructing an object captured by an imaging sensor, and training method 2022
DE patent “DE102021202711 A1””
J. Bechtold, T. Brox, V. Fischer and M. Tatarchenko

Tangent convolutions for 3D data 2019
US patent “US2019042883 AA”
J. Park, V. Koltun, M. Tatarchenko and Q.-Y. Zhou

LANGUAGE SKILLS

Russian (mother tongue), English (advanced), German (advanced)

TEACHING EXPERIENCE

PhD student supervision

Jonas Kälble Apr. 2023 — now
Image-based occupancy estimation
University of Saarland and Bosch

Melis Öcal Sep. 2022 — Mar. 2024
Generative modelling for 3D reconstruction
University of Amsterdam and Bosch Delta Lab 2

Ronny Xavier Velastegui Sandoval Oct. 2022 — Mar. 2024
3D semantic segmentation
University of Amsterdam and Bosch Delta Lab 2

Jan Bechtold Apr. 2021 — Mar. 2023
Single-view 3D reconstruction
University of Freiburg and Bosch

Master/bachelor/intern supervision

Yuchen Tao Oct. 2021 — Apr. 2022
Point cloud completion via direct measurement integration
Master intern at BCAI

Olesya Tsapenko Mar. 2019 — Sep. 2019
Point cloud colorization using sparse convolutions
Master’s thesis

Jan Bechtold Jun. 2018 — Dec. 2018
3D object detection using tangent convolutions
Master’s thesis

Lukas Wiens Dec. 2017 — Mar. 2018
Implementierung der Octree Generating Networks Deep Learning Architektur in Tensorflow
Bachelor’s thesis

Sudhanshu Mittal Mar. 2017 — Nov. 2017
Semi-supervised learning for real-world object recognition using adversarial autoencoders
Master’s thesis

Vladislav Tananaev Mar. 2017 — Jun. 2017
Semantic segmentation in point clouds with deep networks
Master’s thesis

University courses

Optimization (in German) WS 2019 — 2020
Lecture
Teaching assistant

Statistical pattern recognition 2018 — 2019
Lecture, selected classes
Lecturer

Computer vision 2018
Lecture, selected classes
Lecturer

Deep learning for biomedical image analysis 2016 — 2019
Seminar
Supervisor

Current works in computer vision 2016 — 2019
Seminar
Supervisor

Deep learning SS 2016
Lab course
Co-organizer and supervisor

Parking space detection SS 2015
Lab course
Co-organizer

SELECTED TALKS

Not including internal company/lab talks, not including talks prior to 2016.

3D deep learning: methods and applications Jul. 2020
PhD defence, Freiburg, Germany

3D deep learning: methods and applications Dec. 2019
5th Christmas Colloquium on Computer Vision, Yandex, Moscow

What do single-view 3d reconstruction networks learn? Jul. 2019
Dynamic Vision workshop, CVPR, Long Beach

Problems of single-image 3d reconstruction Sep. 2018
Intel Network on Intelligent Systems Workshop, Munich

Deep learning in computer vision and its applications to 3D data Jun. 2018
Optics Colloquium, University of Freiburg

Multi-view 3D models from single images with a convolutional network Dec. 2016
2nd Christmas Colloquium on Computer Vision, Skoltech, Moscow

Multi-view 3D models from single images with a convolutional network Oct. 2016
ECCV, Amsterdam

Graduation speech Jul. 2016
Graduation ceremony, University of Freiburg

VOLUNTEERING ACTIVITIES

Robotics workshop for Ukrainian kids May. 2022 — now
Organizer

Youth hackathon Freiburg Nov. 2019
Mentor