Dr. Mustahsin Adib

I am working on MOx electronic nose. The goal of my thesis is to improve the existing sensor system as well as develop a new concept sensor. As we use the gas sensor as electronic nose, machine learning algorithm is necessary. We use LDA, which is a supervised training method. I also have a decent product development experience in collaboration with international partners while working for an EU project. The goal of the project was to develop a smart fire alarm for a company from Denmark using our eNose.

I wrote my MSc thesis at BST in 2013. I worked on an ambient temperature estimation technique using bmp280. With the help of my FEM simulated model, I proved that, without physically changing the bmp280 it is impossible to estimate the ambient temperature. I’ve implemented one of the proposals recommended by my simulation. I’ve also developed an adaptive algorithm inspired by KALMAN filter to estimate the room temperature.

As a HiWi, I worked on a LIDAR based anemometer project, where wind speed was measured in order to optimize the operation of a wind turbine. Back scattered LASER light from airborne aerosol particle was used as a signal for the system. My task was to make a primary FEM simulated model and compare the simulation with experimental data.

As a HiWi, I have worked in a project named „Fast scanning LASER range finder for adaptive robotics in industry and logistics". The project goal was to build a complete, accurate and rapid environmental perception sensor system for Automated guided vehicles (AVGs). My task was to to design a signal generator for the LASER modulation along with a clock pulse for our Analog to Digital Converter (ADC) at maximum speed.

Optical communication, Opto-electronic Components, Optical Engineering, Wave-guides, LASER.