Work with progressive organisation that gives me the opportunity to utilise my skills in achieving
common goals of the corporation and a bright personal career. Currently enrolled at the University of
Queensland for Master of Data Science. Three and a half years of work experience in a highly scalable
messaging platform and digital health web services. Passionate about software|data engineering & areas
of AI like deep learning, NLP & computer vision.
Master of Data Science
Data Science Capstone Project
Explainable Deep Learning for Coral Classification
Coral taxonomy is currently undergoing a ‘molecular revolution’ which is fundamentally altering our understanding of the systematics and evolution of reefs.
Importantly, molecular phylogenetic (tree of life) data is showing that micromorphological and microstructural features of the coral skeleton better reflect
species evolutionary relationships than traditional macromorphological traits. While the combination of molecular phylogenetics and morphological analysis has
facilitated better understanding of coral diversity, analysing microstructural features under the microscope is time-consuming and requires considerable expertise.
Furthermore, this integrated taxonomic approach cannot be applied to the tens of thousands of coral specimens in the Queensland Museums (QM) collections collected
before the time tissue preservation became necessary.
Machine learning could help overcome these problems by identifying and classifying species based on their skeletal morphology from high-resolution images,
providing a valuable tool for coral taxonomy. Importantly, machine-learning tools could then be applied to accurately identify the extensive historical
collections at QM, a task that would otherwise be completely unfeasible given the time required to examine each specimen.
The aim of the project is to build deep learning tools that can classify images of coral specimens into a hierarchical taxonomy also providing
explanations for the picked category (e.g., using https://github.com/marcotcr/lime). Methods include the use of computer vision models (e.g., pretrained imagenet models or training models from available coral image datasets).
Course's Semester 1
Operation Research & Mathematical Planning
Advanced Database Systems
Introduction to Data Science
Mathematics for Data Science
Course's Semester 2
Responsible Data Science
Machine Learning for Data Science
Applied Probability & Statistics
Course's Semester 3
Social Media Analytics
Data Analytics at Scale
Statistical Methods for Data Science
Data Science Capstone Project - Propose
Course's Semester 4
Summer Research Scholar | The University of Queensland
Research Topic: Artificial intelligence for the prediction and prevention of concussion
Used Mask RCNN framework to track players trained on the Cityscape Dataset and transfer learning.
Accomplished detection of human pose estimation in video gameplay from pre-trained coco human pose estimation model.
Implemented team tracking using OpenCV. Extracted video frames of tackles/concussions parsing from XML data.
Detected collision using intersection over union(IoU).
Supervisor: Dr Shakes Chandra
Cyberbullying is a crime where one person becomes the target of harassment, racism, toxicity and hate etc.
A sequential deep learning architecture: Embedding, Convolution, Max Pooling, Dense layers eliminates the
need for feature engineering and produces better prediction than traditional machine learning
approaches using the concept of word embedding using a high-level API of TensorFlow open-source library.
E-commerce has increasingly become more popular as well as customer's expectations. Olist, an ecommerce
platform, does not always predict an accurate delivery time. We go through the data science process to
reduce the error in estimating the delivery time. After explorative data analysis, we identify the
features that contributes to the longer estimated delivery time. In consideration to the findings of
the analysis we make recommendations that can be considered to improve delivery experience.
Bachelor of technology in computer science & technology from National Institute of Technology, Rourkela, India
Final year thesis on the study of an item based collaborative filtering, recommender System
Graduated with first-class grade