Mikk Kruusalu

Physics and Data Science

I am a master’s a student in Applied Physics and Data Science. Describing the world in a quantitative way and learning about the system’s behaviour by modelling is why I like studying physics.

In my free time I enjoy cooking, hiking, playing football, padel and other ball games.

Find my pdf CV here.

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Development Engineer

March 2023 - Present

CAFA Tech

  • Drone tether system control loop firmware.
  • Developed a battery pack control system PCB and firmware.
  • Energy Team Lead in developing a smallscale microgrid.
  • Machine learning model for classifying objects based on their trajectories.
  • Developed a Data Acquisition System based on Beckhoff PLC and Timescale database.
  • Rapid prototyping of heat engines.

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MSc Applied Physics and Data Science

Sep 2024 - Present

Tallinn University of Technology

Some notable courses I have had in Master’s are

  • scientific computing , where we had three finite element projects on the High Performance Cluster.
  • Deep Learning , where we explored several different neural network architectures by defining and training these on individual projects
  • Numerical Methods, where we implemented different numerical schemes to solving Partial Differential Equations (PDE), this was continuance on the analytical PDE course.

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Erasmus exchange student

Sep 2023 - Jan 2024

Denmark University of Technology

I had courses on

  • dynamical systems,
  • deep learning ,
  • experimental course in optic communications and state space models.

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Robot Technician

June 2022 - March 2023

Starship Technologies

  • Repaired mechanics and electronics including PCBs
  • Create tools to improve the robot’s repair process

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BSc Applied Physics

Sep 2021 - June 2024

Tallinn University of Technology

My thesis focused on modelling nerve signals and focused on the derivation of the governing equations and solving a PDE with different parametrs to understand the equations behaviour.

Some notable courses I had include

  • basic mathematics, such as linear algebra, caclulus I and II, complex analysis, odrinary differential equations, numerical methods,
  • basics in classical physics, such as mechanics, electrodynamics, optics, thermodynamics, etc.
  • basics in data science, such as probability theory, statistical methods and machine learning.

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Bike mechanic

June 2021 - Sep 2021

Hawaii Express

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