Mr. Suryansh SHARMA

Software Engineer

University of Technology, Sydney

Biography

Suryansh SHARMA is a Software Engineer (S.E.) in the School of Mechanical and Mechatronics at the University of Technology Sydney. His work has been on convolutional neural networks, machine learning, natural language processing, and robotic operating system (ROS). He completed his Masters in 2021 from the University of Technology, Syndey and was also awarded Dean’s List in 2020 and 2021 while having a W.A.M. of 88.25 across his 2 years of study.

Interests

Computer Vision
Machine Learning
Robotics

Education

Master in Information Technology, 2021
University of Technology, Sydney
Bachelor of Technology, 2018
Birla Institute of Technology, Mesra

Skills

Python

Python Programming Language

Computer Vision

Object detection & Object Segmentation

Machine Learning

Regression and Clustering

Robotic Operating System(R.O.S)

Operating System to build robotic applications

Docker

Deployment using containers

Unix

deploying software using linux servers

PowerBI and Office365

Power BI for creating dashboards for gathering insights on a dataset

Java

Java Programming Language

Experience

Software Engineer

University of Technology, Sydney

August 2022 – Present Sydney

Software Engineer at the School of Mechanical and Mechatronics at UTS. The product consists of working on multiple components in the domains such as natural language processing and robotics. Required Skill:

Docker
Computer Vision
Python (Programming Language)
Natural Language Processing (NLP)
Robot Operating System (ROS)

Software Engineer

University of Technology, Sydney

November 2021 – July 2022 Sydney

Software Engineer-AI(Deep Learning). The project utilizes Deep Learning techniques to perform Search And Rescue Operations (SARS) in flooded areas; detect objects of interest and rescue them by dropping life-saving pods. The project was in collaboration with Australia4Innovation and LQTDU Vietnam. Required Skill:

TensorFlow
PyTorch
OpenCV
Python (Programming Language)
Deep Learning

Casual Academic

University of Technology, Sydney

January 2016 – Present Sydney

Tutored three subjects during my postgrad study; Deep Learning & Convolutional Neural Networks(CNN), Python for Data Visualization and .NET application development.

Research Internship

University of Technology, Sydney

November 2020 – February 2022 Sydney

Research Internship under U.T.S. supervisor Dr Nabin S. (Senior Lecturer and Co-Director Intelligence Drone Lab) in the domain of Computer Vision using Machine and Deep Learning techniques. Consists of working on Computer Vision-based problems and publishing the obtained experimental results. Required Skill:

TensorFlow
PyTorch
OpenCV
Python (Programming Language)

Accomplishments

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

Coursera Dec 2020

See certificate

Python(Basic)

HackerRank Sep 2020

See certificate

Data@ANZ Virtual Experience Program Partcipant

ANZ Jul 2020

See certificate

Convolutional Neural Networks

Coursera Aug 2018

See certificate

Deep Learning Specialization

Coursera Aug 2018

See certificate

Sequence Models

Coursera Aug 2018

See certificate

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

Coursera Aug 2018

See certificate

Neural Networks and Deep Learning

Coursera Jul 2018

See certificate

Structuring Machine Learning Projects

Coursera Jul 2018

See certificate

Structuring Machine Learning Projects

Coursera Jul 2018

See certificate

Machine Learning A-Z™: Hands-On Python & R In Data Science

Udemy Sep 2017

See certificate

Deep Learning A-Z™: Hands-On Artificial Neural Networks

Udemy Sep 2017

See certificate

Complete Python Bootcamp: Go from zero to hero in Python 3

Udemy Aug 2017

See certificate

Projects

Human Detection In Flooded Areas

A project done at my time as software engineer at UTS for Search And Rescue Operation. The aim of the project was to fly drones in the flooded areas and deploy life vests to the people drowning.

Social Distancing Estimator

A Deep Learnign based solution to detect clusters of people in real time on drone footage to determine appropriate physical distancing is in place, and can alert people if they are putting others at risk for COVID-19.

Breast Cancer Classification

The project consists of a convolutional neural network which can classify the input images to identify the presence of Invasive Ductal Carcinoma (IDC). Our aim to help reduce the probability of human error in classification of Invasive Ductal Carcinoma (IDC) in breast cancer analysis while saving time.

Koala Detection in Wildfire

The aim of this project is to detect the animals living in the wild and identify the impact of bushfires on their health, done as part of the subject Industry Project in my 3rd Semester of Master’s at UTS.