Hooman Habibi, Developer in Eindhoven, Netherlands
Hooman is available for hire
Hire Hooman

Hooman Habibi

Verified Expert  in Engineering

Software Developer

Eindhoven, Netherlands
Toptal Member Since
December 23, 2021

Hooman is a senior engineer with 15 years of experience in various analytical fields. He started his education as an electrical engineer and got his Ph.D. in 2009. in signal processing. Equally capable of leading teams and delivering directly, Hooman has worked on various signal processing, machine learning, mathematical modeling, and data analysis projects.


Modeling, Time Series, Python, Jupyter Notebook, Regression, Data Science...
Machine Learning, Regression, Neural Networks, Classification...
NXP Semiconductor
MATLAB, Machine Learning, Sensor Fusion, Regression, Time Series, Data Science...




Preferred Environment

Python, Jupyter Notebook, Spyder, MATLAB

The most amazing...

...work I've done is to develop predictive models and signal processing algorithms for multiple products used by millions of people.

Work Experience

Senior Algorithm and Sensor Fusion Engineer

2019 - PRESENT
  • Developed signal processing algorithm for a product such as gas sensor ASIC in a high-level language like Python, based on data-driven models.
  • Collaborated and guided firmware development in C, including fine-tuning algorithms for numerical stability.
  • Performed data analysis and reporting of product performance.
Technologies: Modeling, Time Series, Python, Jupyter Notebook, Regression, Data Science, Data Analytics, Data Analysis, Object-oriented Programming (OOP), Research, State Machines, SQL

Senior Algorithm and Sensor Fusion Engineer

2015 - 2019
  • Developed data-driven algorithms to convert environmental sensors data to usable outputs such as gas concentrations, techniques like linear regression, PCA, neural networks were used.
  • Collaborated in creating and writing multiple patents.
  • Acted as the directly responsible individual for algorithm work package and presentation during product development for key customers.
  • Developed grey-box physics-based models to interpret and identify the boundaries of our data-driven approach for key customers.
  • Oversaw development of a framework from measurement, to data processing, model building, and integration. I developed an algorithm for the correction of sensor readings in smartphones.
  • Developed pipelines to analyze large time-series datasets as part of the R&D stage of sensor development, including automatic report generation.
Technologies: Machine Learning, Regression, Neural Networks, Classification, Mathematical Modeling, Sensor Data, Sensor Fusion, Kalman Filtering, Time Series, MATLAB, Python, TensorFlow, Android, Data Science, Data Analytics, Data Analysis, Object-oriented Programming (OOP), Research, State Machines

Signal Processing and Sensor Fusion Engineer

2014 - 2015
NXP Semiconductor
  • Developed scripts to scan and choose sensor data in Android smartphones to be used in machine learning models.
  • Improved performance of models used to correct for sensor signal distortion.
  • Developed scripts for automatic features selection for regression models.
Technologies: MATLAB, Machine Learning, Sensor Fusion, Regression, Time Series, Data Science, Data Analytics, Data Analysis, Object-oriented Programming (OOP), Research, State Machines

Ph.D. Candidate

2009 - 2014
Eindhoven University of Technology
  • Researched and published algorithms for adaptive control of a nonlinear circuit in an RF receiver aiming to suppress strong interfering signals.
  • Developed and researched systems in collaboration with other Ph.D. candidates to reduce distortion in RF transceivers by using a digitally controlled adaptive circuit. Led and supervised the building of a prototype to validate the research.
  • Researched and published algorithms to estimate and compensate for nonlinear distortion in RF transceivers.
  • Improved my presentation skills and won the best presentation award at a conference.
Technologies: Mathematical Modeling, Simulations, Presentations, Hardware Design, MATLAB, LaTeX, LabVIEW, Estimators, Control Systems, Adaptive Control Systems


2006 - 2009
Freelance Engineer
  • Worked on simulation of DVB S2 transmitter in MATLAB. The code was used to generate test vectors for VHDL implementation of transmitter processing parts.
  • Collaborated in developing a studio-grade video over IP transmission system. The processing code was implemented on a Xilinx FPGA in VHDL and included forward error correction, interleaving, and buffering.
  • Worked on simulation of the development of RS error correction codes in VHDL for a data transmission link.
Technologies: MATLAB, VHDL, Digital Signal Processing

MOX Gas Sensor—Signal Processing and Firmware

MOX sensors offer a low-cost solution for measuring gases of interest in the environment, suitable for mass-market adoption for air quality measurement and control applications. The sensor, however, provides a low-quality signal that needs further processing to extract quantities of interest.

I was one of the main contributors for required signal processing, mathematical modeling, and regression building for several products.

Environmental Sensor Application for Smartphones

Environmental sensors like temperature and humidity can be placed in smartphones to measure ambient conditions. However, the sensor readings are affected by various conditions specific to the phone, like self-heating and delayed response.

I worked on machine learning and sensor fusion methods to enable fast and accurate measurement of ambient conditions, using various techniques like nonlinear modeling and regression, time series forecasting, and filtering.
2009 - 2014

Ph.D. Degree in Signal Processing

Eindhoven University of Technology - Eindhoven, The Netherlands

2004 - 2006

Master's Degree in Signal Processing

Sharif University of Technology - Tehran






Data Science, Object-oriented Programming (OOP)


Python, C, Java, VHDL, SQL


Jupyter Notebook, Android


Regression, Estimators, Adaptive Control Systems, Digital Signal Processing, Data Analytics, Data Analysis, Research, Mathematical Modeling, Estimations, Signal Filtering, Presentations, Machine Learning, Classification, Sensor Fusion, Time Series, Modeling, Simulations, Exploratory Data Analysis, Nonlinear Optimization, Neural Networks, Sensor Data, Kalman Filtering, Hardware Design, Control Systems, State Machines

Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.


Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring