I am Haseeb Jan, from Pakistan. I have graduated from the University of Engineering and Technology Peshawar, with a Bachelor of Science in Electrical Engineering. After graduation, I am working as a Research Assistant at the National Center of Artificial intelligence (NCAI), Peshawar Pakistan.

I am fluent in several data processing, statistical analysis, and machine/deep learning in embedded systems, software, and languages, including Python3 (OpenCV2, Pandas, Scikit-Learn, Scikit-Image, and Tensorflow2), MATLAB, Power BI, Excel, SQL, Raspberry Pi, Nano Jetson, and DSP Based Systems.

During my Bachelor’s Degree, I worked on Artificial Intelligence in a microcontroller-based embedded system (designing an energy anti-theft system) with the Center Of Intelligent Systems & Network Research Lab (CISNR). Besides this, I had worked on three different projects relevant to my major. These Projects include “Underground Cable Fault Detector and Locator using Microcontroller”, “Implementation of V2V Communication on LTE-A network using NS3 and SUMO(paper)” and “Face Detection and Recognition System using artificial intelligence in MATLAB (computer vision)”.

After graduation, I joined as Machine Learning in Embedded Systems Expert with a StartUp named Zama Starga and companies called Deep Neural Labs, Code for Pakistan, from last two years I am working with the National Center of Artificial Intelligence as a machine learning developer on a Project named Safe City (our work revolve around making and deploying algorithms for automation using data analysis, classification, and detection on embedded systems). You will find more detail on my CV with LinkedIn, and GitHub profile.

I wrote a paper with my colleagues as an equal author named Smart Social Distancing for Covid-19 based on deep learning published in Springer Journal named Multimedia Tools and Applications (here). Recently, I wrote papers under the title The impact of technological advancement in Human Expression Recognition System, and Traffic Rule Violation Detection System using YOLOv3 localizer and submitted them to conferences named ICAI2022, and WCCI2022. At last, I did experimentation and achieved better results by creating an algorithm for training using a hybrid of backpropagation and evolution. The aim is to find the automatic solution for neural network designing and training (the journal paper is in the writing process).

A motivated, curious, and fast learner, willing to utilize my skills of machine learning and deep learning in my field of Electrical Engineering using Python3 modules TensorFlow, Sci-Kit Learn, with deploying modules such as Flask, and embedded systems like Nano Jetson, and Raspberry Pi with around more than 3 years of relevant experience in research and development.