Jeremi Wójcicki, Numerical Optimization Developer in Milan, Metropolitan City of Milan, Italy
Jeremi Wójcicki

Numerical Optimization Developer in Milan, Metropolitan City of Milan, Italy

Member since November 11, 2020
Jeremi obtained a PhD in mechatronics engineering and has over seven years of research experience in the field of industrial engineering/manufacturing and two years running independent IT/R&D consulting projects. He specializes in modeling and optimizing systems, with expertise in machine learning methods, programming, embedded systems, and IoT. He decided to leave academia with the ambition of having a stronger impact in real-life applications.
Jeremi is now available for hire




Milan, Metropolitan City of Milan, Italy



Preferred Environment

CUDA, Docker, Linux, Windows 10, Visual Studio, C++, MATLAB, Python 3, Anaconda

The most amazing...

...thing I've accomplished was founding a startup, Pixelent, aiming to revolutionize teleoperation of robots with an advanced, stereoscopic vision system.


  • Senior Consultant and Developer

    2019 - PRESENT
    • Developed and implemented novel technologies and execute data science projects for European companies. I was responsible for carrying out projects from the conceptual phase through requirements definition, development, and deployment.
    • Developed a web platform for energy consumption monitoring, visualization, and forecasting for the printing industry using machine learning.
    • Created a shop floor and cloud connectivity solution for industrial machinery using open communication models.
    • Designed an ultra-low power IoT wearable device powered by an energy harvester and software stack to acquire and visualize data on an Android device.
    Technologies: Artificial Intelligence (AI), Qt 5, Scikit-learn, Jupyter Notebook, Jupyter, Python, Machine Learning, Machine Vision, Linux, Anaconda, Data Science, Time Series, Forecasting, Data Pipelines
  • Founder

    2020 - 2020
    Entrepreneur First
    • Generated deep-tech business ideas in the field of industry 4.0 and smart factory, and validated their feasibility and potential.
    • Contacted hundreds of stakeholders: potential customers, technology providers, and industry experts for insights and market validation.
    • Networked with a global community of entrepreneurs and innovators.
    Technologies: Startup Funding, Deep Learning, Entrepreneurship
  • Postdoctoral Researcher

    2017 - 2020
    CNR-STIIMA, Italian National Research Council
    • Developed an intelligent machine component: smart CNC spindle. I developed a sensory system, an embedded edge node (IoT), algorithms for analysis of acquired data, and communications with other systems, including a cloud back end.
    • Created a high-performance, GPU-accelerated implementation of Eulerian motion magnification algorithm to amplify micromotions of objects in high-speed video feeds.
    • Modeled, simulated, and optimized a discrete-manufacturing system for metal parts production to improve overall performance (minimize net present cost) and decrease environmental impact.
    • Conceived, obtained funds, and executed research projects. I established and managed relationships with relevant industrial partners and published research findings in top-tier scientific journals.
    • Mentored, coordinated, and led several early-stage researchers and senior students in carrying out research projects or thesis work.
    Technologies: Signal Processing, Real-time Systems, Computer Vision, Machine Vision, CUDA, Machine Learning, Machinery, Numerical Simulations, Optimization, Numerical Methods, Internet of Things (IoT), Time Series, Video Analysis
  • Co-founder and CEO

    2016 - 2017
    • Created a working prototype of a stereoscopic vision system for teleoperation of unmanned vehicles, consisting of a robotic dual camera head, an image acquisition platform based on NVidia Tegra, and a software stack for streaming and VR rendering.
    • Sat at the table on multiple occasions with investors and entrepreneurs looking for means to VC fund my business.
    • Won a startup award at the "Kraków Business Starter" competition (second place out of 109 contenders).
    • Led a team of two developers (hardware and software) in a pre-seed startup to develop an MVP. I defined technical requirements, supervised execution, and reviewed deliverables.
    Technologies: OpenGL, Qt 5, Computer Vision, Virtual Reality (VR), Machine Vision, Mechatronics
  • Early Stage Researcher

    2013 - 2017
    CNR-ITIA, Italian National Research Council
    • Created physics-based mathematical models to predict the energy expenditure of CNC machines during production. These numerical digital-twins were composed of analytical, numerical, and simulation sub-models.
    • Developed a sophisticated, hierarchical optimization algorithm to minimize energy demand and processing rate of industrial machines, introducing optimal machine parameter set-up and management policy choice.
    • Performed cost-effectiveness analysis of various policies for manufacturing system management applied to industrial partners use-case.
    • Collaborated and synchronized my work with other researchers, research groups, and partners, disseminating obtained research results in top-tier scientific journals and conferences.
    Technologies: Signal Processing, Real-time Systems, Optimization, C++, Numerical Simulations, Numerical Methods, MATLAB, Data Science
  • Junior R&D Specialist

    2012 - 2013
    Rcc Nova
    • Initialized and developed a product line of embedded controllers for the railway industry: a tram pantograph control system and train vacuum sanitary system. Yield from that project constituted a fair portion of the company's revenue.
    • Participated in industrial measurement (NVH) campaigns for international customers.
    • Performed software testing for an international client whose main product was a software suite for industrial measurements.
    Technologies: Signal Processing, Real-time Systems, Embedded C, Embedded Hardware


  • Energy Monitoring and Forecasting Web Application

    I developed a web application with a back end to collect, store, and analyze energy data from power consumption sensors located at customers' locations. It included a machine learning random forest regression model to forecast future demand based on historical data and customer meta-data. I also created a front end to visualize data and predictions.

  • Hierarchical Modeling and Optimization Framework for Machine Energy Prediction

    In this research work, I created a framework to mathematically model energy demand and processing rate of operations and technological processes in industrial machinery. It combined the use of analytical, simulation, and black-box models (numerical digital-twins).

    My work included using regression methods for model identification and sophisticated optimization algorithms to minimize energy use and ensure the highest productivity. I was responsible for the delivery of this project, which being part of a larger European research project, had an allocated budget of €250,000.

  • GPU Accelerated Implementation of Motion Magnification Algorithm

    I implemented an Eulerian motion magnification algorithm developed by MIT exploiting GPU acceleration, which allows efficient processing of large, high frame-rate video captures. The purpose is to extract micro motions invisible to the human eye for various industrial applications, e.g.:
    - Intuitive operational deflection shapes visualization
    - Dynamic analysis of micro-motions without using accelerometers


  • Languages

    Embedded C, Python, C, C++, SQL, PHP
  • Tools

    MATLAB, Visual Studio, Jupyter, Git
  • Other

    Mechatronics, Machine Learning, Numerical Modeling, Numerical Optimization, Machine Vision, Deep Learning, Regression, Manufacturing, Embedded Systems, Computer Vision, Signal Processing, Artificial Intelligence (AI), Robotics, Numerical Methods, Numerical Simulations, Optimization, Machinery, Entrepreneurship, Startup Funding, Virtual Reality (VR), Embedded Hardware, Neural Networks, Hyperparameters, Problem Structuring, Convolutional Neural Networks, Sequence Models, Business Analysis, Business Management, Computer Vision Algorithms, Simultaneous Localization & Mapping (SLAM), Internet of Things (IoT), Time Series, Forecasting, Video Analysis, Natural Language Processing (NLP), Big Data
  • Libraries/APIs

    NumPy, Pandas, TensorFlow, Scikit-learn, Matplotlib, OpenCV
  • Paradigms

    Real-time Systems, Data Science
  • Frameworks

    Ruby on Rails (RoR), Qt 5
  • Platforms

    Anaconda, Linux, Docker, CUDA, Jupyter Notebook
  • Industry Expertise

    Project Management
  • Storage

    Data Pipelines


  • PhD in Mechanical Engineering
    2013 - 2017
    Politecnico di Milano - Milan, Italy
  • Master's Degree in Mechatronics
    2007 - 2012
    AGH University of Science and Technology - Cracow, Poland
  • Student Exchange Participant in Electrical Engineering
    2011 - 2011
    University of Central Florida - Orlando, FL, USA


  • Deep Learning Specialization by
  • Machine Learning by Stanford Online
  • CUDA Programming on NVidia GPUs
    JULY 2018 - PRESENT
    University of Oxford
  • Management Essentials for PhDs
    Politecnico di Milano
  • Certified Matlab Associate
    APRIL 2017 - PRESENT
  • Business Management and Entrepreneurship
    JUNE 2015 - PRESENT
    ESADE Business School

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