👋 Hello, World! (Please Note: This README may not be up to date.)

I'm a recent graduate from KTH Royal Institute of Technology(HAVENT ACTUALLY GRADUATED YET, SOON), where I completed an Engineering Physics program (Swedish: Civilingenjör inom Teknisk Fysik) with a Master of Science in Engineering (MSc Eng), Machine Learning. As a passionate Machine Learning Engineer and Data Scientist, I love diving into complex problems and surfacing with solutions that matter.

Deeply fascinated by generative modeling, I've delved into various realms such as Variational Methods, Normalizing Flows, and Diffusion Models, always on the lookout for intriguing patterns and novel applications. The intersection of data engineering and machine learning is another field that captures my interest, and you'll find projects here that showcase this synergy.

In this digital repository, you'll find an array of projects where I've applied my skills, displaying my fascination with the interplay of physics, data, and AI.

Feel free to dive in, and let's connect if you're interested in collaborating or discussing ideas!

• 📫 How to reach me:
• Email: [email protected]
• Phone nr: +46 (0) 705 33 44 28

Data Analyst, Trade Finance Bank Management Team (2018 - 2020)

• Assisted in setting up requirements for analyzing risk-adjusted financial performance.
• Automated special requests for import/export letters of credit (LC), providing support to the TFBM team.
• Continued to verify the accuracy and robustness of data files destined for the Central Data Warehouse (CDW), similar to my previous work.

Business Analyst, Trade & Working Capital (2018 - 2018)

• Assisted in a project focused on the migration of Supply Chain Finance products from Nordea Finance to Nordea Bank. The project's goal was to enable the bank to utilize a more advanced, internal ratings-based approach to calculate necessary capital for credit risk.
• My responsibilities included verifying the accuracy and robustness of data files designated for the Central Data Warehouse (CDW), and to define specific parts of these files.

Civil Engineering Summer Internship (April 2016 - September 2016)

• Developed a computational tool consisting of formulas to calculate hydraulic flows and evaporation rates in urban stormwater drainage systems.
• Created models to predict the behavior of stormwater based on roadway gradients, pipeline capacity, water storage, and controlled infiltration into the ground.
• These models were primarily used for predictive analysis and not for the actual design and optimization of the infrastructure.
• This project was undertaken on behalf of Atkins Global in collaboration with the Ministry of Transport in Abu Dhabi, UAE, to help them understand and predict stormwater behavior.

I'm proficient in:

• Python
• R
• Matlab
• SQL
• Scala
• VBA

I'm a beginner and currently improving my skills in:

• C++
• Java

I have extensive experience with:

• PyTorch
• TensorFlow
• OpenCV
• scikit-learn
• pandas

I'm experienced with:

• Google Cloud Platform
• AWS
• Azure
• Git