Daniel Skauge

InMind develops intelligent robots for industrial manufacturing. - Designed and built the full-body control stack for an 18-DoF humanoid robot, integrating ROS 2, ros2_control, sensors, FPGA firmware, and motor controllers. - Built the teleoperation stack used to operate the robot and collect demonstrations for robot learning. - Train and evaluate PyTorch-based visuomotor imitation-learning policies for manipulation, connecting demonstration data, control, sensing, and on-robot evaluation for high-mix manufacturing tasks. - Work across C++ and Python to debug and improve the full robot-learning loop, from hardware and control through data collection and learned-policy behavior.

- Engineered time-series forecasting models which reduced prediction error by 43% for Nordic energy market prices. - Optimized data processing and analysis workflows using pandas, improving efficiency for the team.

Developed a custom transformer model in PyTorch, achieving over 90% accuracy in illegal ship activity detection. This validated the technology and laid the groundwork for Vake’s maritime risk assessment strategy.

- Trained a deep learning model for detection and classification of urban litter, achieving over 80% accuracy. - Captured and annotated a dataset of over 10,000 real-world images, expanding detection to 12 additional classes.

Hosted organization-wide courses in AI and public speaking.

Led a national AI Startup event by managing a 10-person team, securing record attendance of 150+ participants.

BRAIN NTNU is a student-led initiative affiliated with NTNU's Department of Computer Science and the Norwegian Open AI Lab, aiming to connect students with the AI industry and research community.

- Hosted live science shows - Led programming workshops

- Developed a controller for a military ATV, enabling autonomous navigation. - Implemented replay of logged telemetry data in simulation to calibrate control parameters, resulting in a 50% improvement in path following accuracy.

Worked in a team to train the computer vision model that led to victory at the TAU international robotics competition

Key courses: - Machine Learning - Optimization and Control - Linear Algebra and Calculus - Algorithms - C/C++ - Digital Signal Processing - Computer Vision. - Modeling and Simulation

Selected participant in Y Combinator’s AI Startup School, a two-day San Francisco conference for technical students and recent graduates. Learned from leading AI researchers, founders, and industry leaders on building with AI and the future of AI startups

Specializing in advanced robotics and machine learning coursework