Osama Nadeem

Software Engineer, Deep Learning Researcher and Android Developer
Machine Learning Resume Android Developer Resume

A highly versatile machine learning engineer / researcher and computer vision expert with almost 2 years of programming experience specifically in deep learning. I have wide interests in technology in general, but my deepest knowledge is in deep learning and android development.

Besides that, I love hiking, traveling, social events, reading books, and especially photography (Check out my instagram).

My Recent Publication:
O. Nadeem, M.S. Saeed, M.A. Tahir and R. Mumtaz, ”A Survey of Artificial Intelligence and Internet of Things (IoT) based approaches against Covid-19”, Published in IEEE-Honet 2020. Read Here.

Notable Projects

F-Attendance

Android application for taking student attendance using AI Face Recognition. Any teacher could create a new class in the application, and students can then mark their attendance for that lecture using facial recognition.

Tools Used: ResNetV1 (CNN model), Tensorflow/Keras, Dlib, Firebase RealtimeDB, Java, Android SDK

F-Attendance Demo
Image showing the F-Attendance application

Customer Feedback using AI

Python module developed using Tensorflow, for Customer Feedback using live videos. The video and audio will be processed by our machine learning model and predict the customer feedback using smart emotion recognition.

Tools Used: Python, Tensorflow/Keras, Librosa, OpenCV, PyAudio, Convolutional Neural Networks (CNNs)

Customer Emotion Recognition - Demo
Image for Customer Emotion Recognition using AI



WinnieBot - An Interactive AI Chatbot

An intelligent chatbot to perform different useful tasks such as obtain any movie information, weather updates and forecast of any global city just by using speech or text.

Tools Used: Natural Language Processing (NLP), Node.js, Rest APIs, Java, Android SDK

WinnieBot - Github Repo
WinnieBot - Demo Picniq web application

TGS Salt Identification Challenge

Algorithm that can automatically and accurately identify if a subsurface target is salt or not. Used dataset from Kaggle and built the model using UNET architecture.

Tools Used:Python, Tensorflow, Numpy, Matplotlib, Scikit-learn

TGS Salt Identification Project - Github Repo

TGS Salt Identification model

Check out more projects at my  
For project demos, check out my  

Experience

Application Engineer

LMKR
  • Developed new visualization features in GeoGraphix, the flagship suite of applications by LMKR.
  • Troubleshooting existing GeoGraphix workflows and introducing alternatives for better results and usability.
  • Used agile practices and test driven development techniques to develop reliable software.
July 2021 - Current

Android Developer (Project based)

Ovex Technologies
  • Responsible for implementing new solutions/feature-sets and maintaining existing applications for Android.
  • Interacting with the backend team for developing the app workflow for a smooth user experience.
  • Built Android apps with back-end API integration to improve the customer experience and cut down on development time.
August 2020 - June 2021

Deep Learning Research Fellow

TUKL R&D Lab for Artifical Intelligence and Machine Learning, NUST
  • Worked on EuroSAT multispectral dataset using supervised and unsupervised techniques, and improved image classification accuracy to 99.10%.
  • Reviewed conventional deep CNNs for classification (AlexNet, VGG, ResNet, Inception and MobileNet).
  • Reviewed image segmentation architectures (U-Net, FCN) and performed semantic segmented on TGS Salt Identification dataset using these architectures.
Sep 2019 - Jan 2020

Education

National University of Sciences and Technology (NUST), Pakistan

Bachelor of Science in Computer Science

CGPA: 3.22/4.0 (80.5%),   Major semester GPA: 3.63


Major Courses: Artificial Intelligence, Advanced Programming, Digital Image Processing, Advanced Topics in Deep Learning, Data Warehousing and Data Mining, Data Structures and Algorithms, Computer Networks

Sep 2017 - June 2021

Skills

Programming Languages & Tools
Technical Skills
  • Python, Tensorflow/Keras, OpenCV, Dlib, Scikit-learn, Pandas
  • Java, Android SDK, Firebase, Volley/Retrofit, Picasso, React Native
  • Bootstrap, Javascript, Node.js and SQL
  • Git, Ubuntu, Latex
Soft Skills
  • Teamwork
  • Leadership
  • Problem Solving
  • Communication

Additional Courses

  • Deep Learning Specialization by Andrew NG - Coursera. Certification
  • Machine Learning Specialization by Andrew NG - Coursera
  • Computer Vision (CS231n) - Stanford University
  • Data Science Courses from DataCamp (multiple). Certificatons

Awards & Achievements