Mariusz Wiśniewski

Software Engineer

Zürich, Switzerland

Professional Skills

  • C/C++
  • Python
  • PyTorch and TensorFlow
  • Bash Scripting
  • Dart and Flutter
  • Java
  • PostgreSQL and MySQL

Others

  • Git
  • CMake
  • Docker
  • Ansible
  • Jenkins/GitLab CI/GitHub Actions
  • Computer Vision
  • Natural Language Processing
  • Linux, MacOS, Windows

Certificates

  • AWS Technical Essentials
  • Developing on AWS
  • DevOps Engineering on AWS
  • Bootlin Embedded Linux System Development
  • Intel AI Summer School

Foreign Languages

  • Polish: Native
  • English: C1, TOEFL iBT: 107
  • German: B1
  • Spanish: B1
  • Italian: A2

Hobbies

  • Filmmaking
  • Street Dance
  • Piano
  • Football

Contact

mariusz.krzysztof.wisniewski@gmail.com

Work Experience

Software Engineer | Positioning Product Driver Team

u-blox | Aug 2023 - Present
  • Leading the design and architecture of a global GNSS monitoring project, overseeing real-time data collection, network transmission, and cloud-based logging and visualization.
  • Developing, enhancing, and maintaining C++ drivers for market-leading GNSS receivers on Android Automotive and Windows, improving thread-safety, and streamlining testing setup and management by introducing Ansible.
  • Active member of the AI Center of Competence, providing expertise and support for AI projects across the company.

    • Software Engineer | PowerVR Graphics & Simulation Team

    Imagination Technologies | Apr 2021 - Sep 2021
  • While working in a two-person research project, designed and implemented a mobile GPU simulator based on the gem5 project.
  • Designed and maintained high performance GPU simulation models written in SystemC for the PowerVR graphics processors.

    • Software Developer | Baseband

    Nokia | Jul 2020 - Mar 2021
  • Worked in a R&D unit on the implementation and maintenance of the baseband service for new 5G solutions using C++ and Python.
  • Established myself as the go-to person in the domain testing area. The improvements I proposed to the pytest-based testing framework brought measurable performance benefits and were recognized at the functional area level.

    • Software Development Intern | Networking Division

    Intel Corporation | Jul 2019 - Jul 2020
  • Worked on the development of the driver for the cutting edge Infrastructure Processing Unit, IPU ASIC E2000, which is a collaborative achievement of Intel and Google Cloud.
  • Received managerial recognition for the contribution to the development of unit, component, and integration tests using the Google Test framework.
  • Improved Linux system administration and management skills while working with the Simics virtual platform.

    • Education

    Politecnico di Milano | Double Degree | Sep 2021 - Jul 2023

    Master in Computer Science and Engineering, Faculty of Electronics, Information and Bioengineering

    Wrocław University of Science and Technology | Mar 2021 - Mar 2023

    Master in Computer Engineering, specialization: Applied Computer Engineering in Medicine, Faculty of Information and Communication Technology, graduated with Excellent (A+)

    Wrocław University of Science and Technology | Oct 2017 - Jan 2021

    Bachelor in Computer Science, specialization: Applied Computer Engineering in Medicine, Faculty of Electronics

    Universidad Autónoma de Madrid | Erasmus+ | Sep 2018 - Jun 2019

    Computer Science, Faculty of UAM Polytechnic School

    Publications

    SE3D: A Framework For Saliency Method Evaluation In 3D Imaging | IEEE ICIP 2024

    Paper introduces new metrics to evaluate saliency methods for 3D CNNs and modifies ShapeNet, ScanNet, and BraTS datasets for benchmarking. The analysis reveals current 3D saliency methods fall short in performance, highlighting the need for advancements in the field..

    Awards

    Wrocław University of Science and Technology

  • Rector Scholarship for The Best Students | Mar 2021 - Feb 2022
  • 3rd highest GPA among 300 CS Master's degree students twice in a row
  • Rector Scholarship for The Best Students | Oct 2020 - Feb 2021
  • 21st highest GPA among 1,000 CS students in all years
  • Rector Scholarship for The Best Students | Oct 2018 - Jun 2019
  • 67th and 31st highest GPA among 1,300 CS students in all years

    • Projects

    Weakly Supervised 3D Object Detection | Python, PyTorch, TensorFlow

    Master's thesis research project focused on developing a novel approach to 3D object detection in medical imaging. The project utilizes weakly supervised 3D convolutional neural networks combined with model explainability techniques to generate bounding boxes around objects of interest within medical volumes. This research was conducted under the supervision of professors from both Politecnico di Milano and Wrocław University of Science and Technology.

    Story Maker | Dart, Flutter, FFmpeg

    Bachelor's thesis project involving the development of a mobile application using Flutter for both iOS and Android platforms. The app automatically generates short, story-like videos by selecting the best moments from user-specified files.

    The Hairdresser's | C++, STL, std::thread, ncurses

    A multithreaded C++ program simulating the operations of two competing hairdressing salons. The program employs the ncurses library to visually display the current state of each salon in real-time.

    Travelling Salesman Problem | C++, STL

    A C++ program solving the Travelling Salesman Problem using exact (brute force, dynamic programming, branch and bound), local search (simulated annealing, tabu search) and population-based (genetic algorithm, ant colony optimization) algorithms.

    Virtual Beamer | Java, JavaFX

    A Java application designed for synchronously sharing and displaying slides across multiple nodes within a LAN, controlled by a single leader node. It is capable of handling potential node failures while aiming to minimize the number of messages exchanged between nodes.

    Polish Fake News Detection | Python, TensorFlow, Transformers

    A web application developed by a team of five to detect fake news in Polish. The core of the application is a deep learning model trained on a dataset of 998 fake and 2,571 real news articles, which was also generated as part of the project. The application leverages natural language processing tools provided by the Common Language Resources and Technology Infrastructure (CLARIN-PL).