Personal details

Adnan L. - Remote

Adnan L.

Timezone: Eastern Time (US & Canada) (UTC-4)

Summary

As a Software / Machine Learning Engineer with numerous experiences, I take pride and excitement in the field! Offering my expertise in assisting clients with ML related projects and expanding my knowledge are important factors that draw me to this work. I earned my degree in Electrical Engineering from McMaster University, and continued on to pursue a graduate certificate in Artificial Intelligence from the University of Toronto.

Throughout my career, I have been involved in all stages of Machine Learning projects from data creation to applying different ML models. I have also been involved in applying different Artificial Intelligence models, such as Convolution Neural Network (VGG 16, resnet 50), Natural language processing (NLP), Generative Adversarial Network (GAN) and a simple 1-2 layer neural network models to real life datasets. In one of my projects, I engineered new features from the data and used them to train the machine learning model (Support vector machine). With this innovative approach, I achieved a 6-7% higher accuracy than the previous approach of passing the whole data as a feature.

Additionally, I also have 8 years of experience in desktop development using C# .net, further adding to my repertoire of skills.
Breaking down and solving problems is a crucial part of engineering and machine learning work – and a skill I would like to offer to your project needs!

Below, are some of my key technical skills:

• Languages: C#, Python, pandas, numpy, matplotlib Keras, Scikit-learn, WPF
• Applications: Visual Studio, Team Foundation Server, Anaconda, Jupyter notebook, SQL Management Studio

Work Experience

Software Research Application Developer
Sciex | Mar 2018 - Present
Python
C#
Keras
· Gathered simulated labelled data to test different machine learning techniques on the dataset in python jupyter notebook · Collected and consolidated data from different departments and labelled it for supervised learning · Tested and evaluated different machine learning and deep learning models · Evaluated performance, based on receiver operator curve (ROC) and changed threshold to have a proper balance between recall and precision
Software Developer
Thermo Fisher Scientific | Aug 2015 - Feb 2018
C#
Visual Studio
Azure devops server
· Developed Drivers for various type of medical instruments using C# in .NET Framework · Worked with the medical device manufacturer on how their instrument will be used in the lab and how to successfully integrate their software API · Coordinated with various project managers and integrators to successfully install the software component of projects · Trained customers on lab automation software (Momentum) and assisted in their scientific analytical experiment

Personal Projects

Malaria Detection using Deep learning IconOpenNewWindows
2019
Machine Learning
Deep Learning
· Implemented different Convolution Neutral Networks (CNN's) on malaria cell images · Achieved ~96% accuracy on validation set
Gerating Simpsons images using Generative Adversarial Networks IconOpenNewWindows
2019
Machine Learning
Neural Networks
Deep Learning
· Implemented GAN using Keras · After 500 epochs, the GAN was able to generate the desired image