maxim.tk
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Munich, Germany · TU Munich (TUM)
About Maxim Mjakinin
M.Sc. Student in Automation & Robotics · Robotics Software & Control
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Academic Journey & Progression (Werdegang)

Okt. 2026 – Present Munich, Germany
Active Master's Studies
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Technical University of Munich (TUM)

School of Computation, Information and Technology (CIT) · Dept. of EI

M.Sc. Electrical and Computer Engineering (EI)
Specialization: Automation & Robotics

Advanced graduate studies focused on spatial kinematics & dynamics (Screw Theory, PoE), autonomous mobile systems, nonlinear control theory, Lyapunov stability, model predictive control (MPC), optimal decision making, and computer vision.

Automation & Robotics Spatial Kinematics Nonlinear Control ROS 2 Munich
2026 Coursera · Prof. Kevin Lynch
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Northwestern University

Northwestern University

Center for Robotics and Biosystems

Modern Robotics: Mechanics, Planning, and Control Specialization
Rigorous 6-Course Program Completed (2026)

Intensive study of modern geometric robotics based on screw theory and Lie groups (SO(3), SE(3)). Implemented complete Python solutions for forward and numerical inverse kinematics (Newton-Raphson), open/closed chain dynamics (Euler-Lagrange and recursive Newton-Euler algorithms), collision-free trajectory generation, and mobile manipulator feedback control.

Screw Theory (PoE) Manipulator Dynamics Trajectory Generation Python Codebase
Okt. 2025 – Okt. 2026 Berlin, Germany
Graduate Studies · Robotics & Machine Learning
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Technische Universität Berlin (TU Berlin)

Fakultät IV · Master Program in Computer Engineering

M.Sc. Computer Engineering (Graduate Studies)
Focus: Cognitive Systems, Machine Learning & Autonomous Robotics

Advanced graduate studies specializing in machine learning and autonomous robotic perception:

  • ▸ Applications of Robotics and Autonomous Systems — Completed with grade 1.0 (sehr gut) (9.0 LP)
  • ▸ Machine Learning 1-X & Machine Learning 2-X (24.0 LP total) — Deep theoretical formulations & neural networks
  • ▸ Computer Vision Project — Development of rigcal for multi-camera rig calibration in ROS / RViz
  • ▸ Statistische Nachrichtentheorie (Statistical Communications Theory, 6.0 LP)
Robotics (Grade 1.0) Machine Learning 1 & 2 Computer Vision (rigcal) TU Berlin
Okt. 2022 – Aug. 2025 Berlin, Germany
Graduated Nov. 2025 · B.Sc.
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Technische Universität Berlin (TU Berlin)

Fakultät IV · Elektrotechnik und Informatik

B.Sc. Technische Informatik (Computer Engineering)
Bachelor Thesis Graded 1.7 (gut) · Erstprüfer: Prof. Dr. Benjamin Blankertz

Comprehensive engineering foundation across systems programming, computer architecture, digital logic, operating systems, and discrete mathematics. Bachelor Thesis: Systematischer Vergleich von Ant Colony Optimization und Constraint Programming zur Lösung von Akari-Puzzles (Erstprüfer: Prof. Dr. Benjamin Blankertz, Note 1.7). Coursework highlights: Hardwarepraktikum (1.7), Projekt Symbolische Künstliche Intelligenz (1.0), Halbleiterbauelemente (2.3), Systemprogrammierung, Rechnernetze und Verteilte Systeme, Elektrotechnik & Messtechnik.

Computer Engineering Thesis Grade 1.7 Hardwarepraktikum (1.7) C++ / Optimization SAT Solving Berlin

Robotics Philosophy & Embodied AI

Autonomous Robotics Pipeline
Perception Sensor Fusion
Vision Rig Calibration
Planning Optimal MPC
Kinematics Screw Theory & PoE
Control Nonlinear & Lyapunov
Action ROS 2 Architecture

Hands-On Engineering & Tech Stack

Robotics & ROS

ROS 2 Modern Robotics Screw Theory / PoE Inverse Kinematics RViz2 / URDF

Languages & Core

Python 3 (NumPy) C++ (C++17/20) C Linux / Bash Git / GitHub CI

Vision & Calibration

OpenCV rigcal (Rig Calibration) PyTorch CNNs Extrinsics

Control & Hardware

Nonlinear Control Lyapunov Analysis PLC / SPS / Sensoric Architecture VHDL / Digital Logic
Open to Opportunities · Munich / Hybrid
Munich, Bavaria

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