Shujaat Hasan is an AI engineer with experience building computer vision and NLP models. He has worked as a freelance AI engineer and for companies in Kenya and India developing models using TensorFlow and Keras for tasks like lane detection, traffic sign classification, face detection and more. He has a PGDM in Big Data Analytics and a BTech in Electronics and Communication. His skills include computer vision, deep learning, machine learning, OpenCV, TensorFlow and Python.

1. Shujaat Hasan
​AI Engineer
New Global PG, 9th cross
Btm 1st Stage, maruthi nagar
Bangalore, 560029
(+91) 9721688797
(+91) 9874450183
hasanshujaat4@gmail.com
EXPERIENCE
Upwork, ​Bangalore, India — ​AI Engineer
September 2019 - PRESENT
Complete freelance projects for clients in fields ranging from computer
vision problems to machine translation and natural language processing.
Design, build, train and test the models for different areas of Artificial
Intelligence.
Working on an hourly basis as well as on project completion basis.
Little ltd, ​Nairobi, Kenya — AI ​Programmer
June 2019 - July 2019
Used OpenCv and Tensorflow for two Autonomous Vehicle Projects.
Applied traditional computer vision techniques for Lane Detection on city
roads.
Applied Deep learning techniques for Traffic sign classification model.
VGGNet Architecture used for Image classification Model.
Flyaway Corporation, ​India​ ​— ​Freelance Engineer
January 2019 - April 2019
Used Keras and Tensorflow for Face and emotion Detection Project.
Applied CNN and other deep learning for the completion of the project.
Responsible for building, training and testing the model.
Flyaway Corporation, ​Lucknow, India​ ​— ​Machine Learning
Engineer
May 2017 - July 2018
Design machine learning and deep learning systems.
Research and implement appropriate ML algorithms and tools.
Developed Model for image classification.
Applied CNN, AlexNet architecture, batch normalization, Dropout etc.
Different optimization techniques as well as hyperparameter techniques
were applied during and after training for better results.
SKILLS
Computer Vision, Deep
learning, Machine learning,
Object Detection, Face
recognition, Neural style
transfer, Image classification,
OpenCv, Tensorflow, Keras,
Numpy, Matplotlib, PIL,
Sequence Models.
CERTIFICATIONS
Coursera ​Neural Networks
and Deep Learning.
Coursera ​Improving Deep
Neural Networks.
Coursera ​Structuring Machine
Learning Projects.
Coursera ​Convolutional
Neural Networks.
Coursera ​Sequence Models.
Coursera ​Aerial Robotics.
PROGRAMMING LANGUAGES
Python
C++
Matlab

2. Mphasis, ​Pune, India​ ​— ​Associate Engineer
January 2016 - March 2017
Develop and execute a plan on patch management.
Written scripts in python for patching automation tasks.
Applied SCCM log files, provide patch management support and
maintenance windows operations.
Direct interaction with clients for the Game plan of Server patching.
EDUCATION
Centre for Development of Advanced Computing, ​Kolkata-
India — ​PGDM in Big Data Analytics
August 2018 - March 2019
Statistical analysis with R, Programming with python, Fundamentals of
Linux Programming, Java with Scala, cloud computing and HPC
application, Data collection and DBMS, Big data Technologies, Advanced
Analytics, Practical Machine learning.
Integral University, ​Lucknow- India — ​Bachelor of
Technology in Electronics and Communication
July 2011 - October 2015
Data Communication Network, Microwave engineering, VLSI design,
Biomedical instrumentation, Nano electronics, Non Conventional energy
resources, TV & satellite communication, Optical Communication, Digital
Image Processing, Filter Design, Control systems, Measurements and
instrumentation, Integrated circuits, Communication Systems,
Microelectronics Technology, Antenna and Wave Propagation, Industrial
Management, Digital Signal Processing, Digital Communication,
Microprocessors and Application, Power Electronics, Wireless
Communication.
PROJECTS
Traffic sign classifier ​— ​github.com/shujaat81
In this project, TensorFlow used for building VGGNet architecture to
classify traffic signs. Dataset used: German Traffic Sign dataset. This
dataset has more than 50,000 images of 43 classes.Model was able to
reach a +99% validation accuracy, and a 97% testing accuracy.
Advance lane Detection ​— ​github.com/shujaat81
In this project, Opencv used to apply traditional computer vision
techniques for lane detection on city roads. Camera calibration, canny
edge detection, perspective transform for bird’s eye view, etc.
PUBLICATIONS
Medium
(​https://medium.com/@hasa
nshujaat4​)
​Mathematics Behind Linear
Regression.

3. Faces and emotions detection for conference audience ​—
github.com/shujaat81
In this project ‘Haarcascade FrontalFace’ filter used for face detection,
and Deep learning approaches used for facial expressions.
Natural Scene Image Classification ​— ​github.com/shujaat81
In this project a deep learning model has been developed to classify real
world scenes from a given input image. Model has coast, forest,
mountain, street and highway as an output layer.