Sajid- Ur-Rehman

COMSATS Institute of Information and Technology

Bachelor's degree, Engineering

January 1, 2008 – January 1, 2012

Air University

Master of Science - MS, Artificial Intelligence

N/A – Present

Fathom.io

Data Science Consultant

August 1, 2025 – Present

Aramco - Dhahran · On-site

Tata Consultancy Services

Data Science Consultant

December 1, 2023 – August 1, 2025

Aramco · On-site

NorthBay Solutions

Associate Architect (Machine Learning and Data Science)

June 1, 2023 – November 1, 2023

Islamabad, Islāmābād, Pakistan · Hybrid

DARVIS

Engineering Manager (Data Science & AI)

November 1, 2022 – April 1, 2023

ToktoAI

DEVELOPMENT HEAD/ ML ARCHITECT

October 1, 2021 – November 1, 2022

Assistech Solutions

Machine Learning Team Lead

October 1, 2020 – September 1, 2021

Experts Vision Engineering and Technology Innovations- EVEATI PVT LTD

PRINICIPAL MACHINE LEARNING ENGINEER AND TECHNICAL HEAD | Co-Founder

August 1, 2017 – October 1, 2020

4C Gate Co. Limited

Senior Machine Learning Engineer

June 1, 2016 – July 1, 2017

Saudi Arabia

Ezah Company for technologies, King Abdul Aziz Road Riyadh

Machine Learning Specialist

June 1, 2015 – May 1, 2016

Riyadh, Saudi Arabia

Experts Vision Engineering and Technology Innovations

AI Engineer | Co-Founder

April 1, 2012 – May 1, 2015

Machine Learning Algorithm for Insurance Company using AI and computer vision techniques

November 1, 2018 – Present

We are developing a product through which process of estimating claim amount of damaged cars during accident will be automated. We will train our system with a data of different car pictures before and after accident, will get an estimate of car damage through image processing techniques and then will give an estimate of reimbursement amount. We used image processing and machine learning algorithms to accomplish this project.

Employees management system using AI algorithms

November 1, 2018 – Present

This system covers different modules like HR, projects management, tasks management, finance and client’s management. We are using machine learning techniques along with asp.net web application to provide unique solution. This system can also track employees’ behaviour through machine learning and image processing techniques and hence can increase employees’ performance and also provide an automated and precise evaluation system of employees’ performance. By using this system, we can solve one of the biggest problem of employee’s performance.

Home and office Automation using Internet of things

July 1, 2018 – Present

We controlled and monitored different appliances through web and mobile apps. This app is really useful for monitoring usage of different appliance and also controlling devices like magnetic door locks etc. We used Node.js, Mqqt for software and also used Arduino along with sensors for hardware.

Teslar- product for solar companies

December 1, 2017 – January 1, 2019

In this project we used different IOT and machine learning techniques to provide optimized power scheduling to consumers. We also did several predictive analyses like solar panel production prediction, service/maintenance etc. We developed a complete management system for solar companies to deal with consumers and staff. We developed mobile and web applications for manager and consumers.

Patients waiting time prediction algorithm demo for King Fahad Medical hospital

November 1, 2017 – Present

I developed an algorithm to forecast patients waiting time in different stages, like vital sign, doctor triage, pharmacies etc. I used machine learning techniques like neural network and KNN for calculating waiting time.

Feasibility report for face recognition for security and surveillance in KFMC

October 1, 2017 – November 1, 2017

I worked on a demo project of face recognition for security and surveillance purposes for command and control centre of KFMC. I presented a detailed report having all the constraints and scenarios for implementing face recognition system.

Ranking of different products on ecommerce stores like Ebay, Amazon by scapping and then applying machine learning techniques

October 1, 2017 – July 1, 2018

We scrapped different products from Amazon, ebay and other e-commerce stores and then applied our machine learning algorithm to ranked them. We analyzed different aspects of products like price, sentiments of consumers, authenticity of reviews etc. We gave negative points to products having fake reviews or some other tampering.

Replica of Hawkeye for Tennis game using Artificial Intelligence and computer vision algorithms

September 1, 2017 – December 1, 2017

Hawkeye is used to track the movement of ball in different games like Cricket, Tennis etc. Price of Hawkeye is really high (USD 60,000) and it’s difficult for local clubs to adopt this technology. We got a project to develop a similar technology with less features and low cost (<USD1000). Computer vision and predictive analysis algorithms were used in this project.

Demo of Arabic OCR from Iqama

August 1, 2017 – Present

I developed an algorithm to read name of person, Iqama number, date of birth and Iqama expiry date from an Iqama image. Later on we are going to add face verification feature in it. It will be used to verify patients using insurance card in different hospitals. I used machine learning and image processing techniques for it.

Lead a team for installation and customer support of Zius keyless door security system.

December 1, 2015 – Present

I Lead a team for installation and customer support of Zius keyless door security system at Al-Jazera News, Riyadh, Saudi Arabia. All doors were linked to SQL server.

License Number Plate recognition system for vehicles management

August 1, 2015 – December 1, 2015

Developed a vehicle management system based on number plate recognition. Time of entry and exit are recorded in our database. I used Canon IP cameras for taking video and then machine learning and image processing techniques to recognize number. System was handed over to the hardware team.

Employee Management System with face recognition

July 1, 2015 – November 1, 2016

Developed an employee management system and with facial recognition based attendance system. I used IP cam for taking images and then used machine learning techniques like Neural networks, support vector machine. I developed this system using MATLAB and c#.

Electricity Load And Price Forecasting

March 1, 2015 – Present

Basic aim of this project was to develop a model that would help in forecasting the electricity loads and their costs by designing a machine learning algorithm that’s capable of learning from previous data records. Data used was that of Australian Electrical Company. The temperature data is taken from the Bureau of Metrology (BOM) whereas the load and pricing data was taken from the company’s website. The data contains historical hourly temperatures, system loads and day-ahead electricity prices from the AEMO on NSW and Temperature data of Sydney Observatory from the BOM. We used three different Machine learning regression techniques (Artificial Neural Networks, Support Vector Regression, Bayesian Regression) and compared their prediction errors.

4. Electric Load Scheduling

September 1, 2013 – November 1, 2013

This project encompasses optimization of scheduling problem of home appliances. We know that any modern house is equipped with a vast array of electronic gadgets, but we also know that power supplier companies charge their consumers with an electricity tariff which fluctuates during 24 hours. We have proposed an algorithm which ensures that minimum cost is incurred by the consumers. The optimization technique which we have used in this algorithm is ‘Genetic Algorithm’, which is a meta-heuristic inspired by the biological evolution.

Radical Distribution Network Reconfiguration Using DNN And PSO

February 1, 2013 – May 1, 2013

Service restoration is an important aspect of power system design that caters the restoration of power to un-faulted area under blackout after an emergency condition. Once a fault takes place, the number of customers in the blackout area mainly depends upon the effectiveness of the load restoration mechanism. There are typically a large number of feeders with even larger number of switches in a distribution system and it’s not humanly possible to restore the service to an out of service area solely based on past experiences.

Design of intelligent water distribution framework

June 1, 2012 – Present

We designed an intelligent water distribution framework that makes use of machine learning algorithms (regression analysis) to control the flow of water between two farms after an irrigation event has taken place in one of them. Data to train and test the model was obtained from the WSN sensors placed at different points in the fields. In case of an irrigation event at one farm, the algorithm determined if the runoff water pathway between the two farms needed to be opened or not. If yes, then after analysing security measures, it predicted how much amount of water should be allowed to pass before automatically closing the pathway again

Stock Prediction using newspapers

May 1, 2012 – July 1, 2012

Aim of this project was to develop an algorithm that would help in predicting the future stock volumes (closing daily official volume for each trading day) of three leading companies (IBM, NETFLIX, IBM) by analysing their previous stock data and newspaper headlines. Purpose is to foretell the stock market trends by analysing the financial knowledge found online and then by using machine learning to interpret the text of news headlines. News headlines can have positive, negative or neutral impact on the day’s stock prices.