Tim P.

Tim P.

Senior Python Engineer

Germany
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About Me

Tim is a proficient full-stack developer with 5 years of software development experience, academic and industry, currently focusing on Python. He wrote his Master's thesis for the M.Sc. Robotics, Cognition & Intelligence program at TU Munich on molecular dynamics simulations and AI in bioinformatics. Tim is passionate about solving problems with technology and has previously worked in Germany and the United States. Furthermore, he has gained experience as a remote developer in Boston as part of a real-time image analysis research division at Texas Instruments.

Work history

UpStack
UpStack
Senior Python Engineer
2021 - Present (3 years)
Remote
  • Create and develop innovative software solutions for different clients across a broad range of industries.

  • Participate in scrums consisting of cross-functional teams, both software and hardware.

  • Ensure that features are being delivered efficiently and on-time.

TU Munich Bionanotech
TU Munich Bionanotech
Software Engineer/Research Assistant
2019 - 2021 (2 years)
Germany
  • Automated and manipulated oxDNA simulations for DNA-origami in C++ and Python.

  • Automated electron microscopy (EM) image analysis with Python and OpenCV. Conducted various lab procedures connected to the self-assembly and analysis of Bionanotechnology based on DNA-origami: agarose-gel purification, uranium-sample staining, EM image collection.

  • Tested EM images for DNA-origami fabrication quality standard. I also assisted in the publication of ”Biophysics in the cell”.

LMU Hospital
LMU Hospital
Research Assistant
2019 - 2019
Germany
  • Investigated the application of Graph Convolutional Neural Networks to combine genetic and MRI brain scan data.

  • Designed and tested a bioinformatics model in R for early-stage Alzheimer’s disease detection.

  • Fused fMRI and genetic patient data for improved predictions.

Texas Instruments
Texas Instruments
Software Engineer
2016 - 2018 (2 years)
United States of America
  • Developed ML algorithms with Python caffe-jacinto, PyTorch and TensorFlow for autonomous driving. Improved real-time image analysis with efficient Convolutional Neural Networks.

  • Designed and assembled a circuit board that showcases an application of OPA-365 and C2000 in HEV/EV. Developed embedded C firmware for C2000 micro-controller.

  • Developed a comprehensive sales analysis tool for quality testing in Python and improved system integration to produce a 10x search performance increase.

Portfolio

Lead Engineer - Power Rail Noise Analyzer
Lead Engineer - Power Rail Noise Analyzer

This reference design is an active pass-band filter connected to the analog-to-digital converter (ADC) in a C2000™ microcontroller (MCU). The system senses ripple and noise on the power rail in the band of interest. The Fast-Fourier Transformation (FFT) algorithm analyzes the harmonic content of the signal and allows for switching frequency detection. The analysis enables adaptive real-time switching frequency dithering in high-power applications and better electromagnetic compatibility interference (EMI) control. Alternatively, ripple counters in feedback-less positioners can benefit the design. I designed & tested PCB layout and developed embedded-C firmware.

Python Developer - Electron Microscopy Image Analysis
Python Developer - Electron Microscopy Image Analysis

I automated information extraction for thousands of images using OpenCV. OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code.

Python ML Researcher - Convolutional Neural Networks for Autonomous Driving
Python ML Researcher - Convolutional Neural Networks for Autonomous Driving

Acted as Python ML researcher at Texas Instruments - developed and compared real-time data analysis models with Caffe Jacinto, Pytorch & Tensorflow. A convolutional neural network (CNN) approach is used to implement a level 2 autonomous vehicle by mapping pixels from the camera input to the steering commands. The network automatically learns the maximum variable features from the camera input, hence requires minimal human intervention.

Education

Master of Science in Robotics, Cognition & Intelligence
Master of Science in Robotics, Cognition & Intelligence
Technical University Munich
2018 - 2021 (3 years)
Bachelor of Science (B.S.), Applied Mathematics - Magna cum laude
Bachelor of Science (B.S.), Applied Mathematics - Magna cum laude
Wentworth Institute of Technology
2016 - 2018 (2 years)