Experience

Auckland Bioengineering Institute

• New Zealand
• Research Services
• 1 - 100 Employee

• Doctoral Candidate

  • Dec 2021 - Present

  Honours & Awards: • Winners - SPARC FAIR codeathon 2022 (organized by SPARC Data and Resource Center and NIH) Honours & Awards: • Winners - SPARC FAIR codeathon 2022 (organized by SPARC Data and Resource Center and NIH)



The University of Auckland

• New Zealand
• Higher Education
• 700 & Above Employee

• Graduate Teaching Assistant

  • Jul 2022 - Dec 2022

  • COMPSYS 306 : Artificial Intelligence and Machine Learning (2022 Semester 2) • COMPSCI 235 : Software Development Methodologies (2022 Semester 2) • COMPSCI 762 : Foundations of Machine Learning (2023 Semester 1) • COMPSYS 306 : Artificial Intelligence and Machine Learning (2022 Semester 2) • COMPSCI 235 : Software Development Methodologies (2022 Semester 2) • COMPSCI 762 : Foundations of Machine Learning (2023 Semester 1)



WSO2

• United States
• Software Development
• 700 & Above Employee

• Machine Learning Engineer

  • Sep 2020 - Nov 2021

  Worked in multiple research & development projects, in wide range of areas including Machine Learning (NLP) and performance optimization. Experienced in designing and developing production grade architectures using Azure based solutions. • Researched, engineered and deployed the initial phase of Choreo’s AI-assisted testing feature, using Python, Keras, Flask, Kubernetes and Azure DevOps pipelines. • Architected, developed and deployed Choreo’s AI-based anomaly detector with two other engineers, using Azure solutions (Azure DevOps pipelines, Azure Logic Apps, Azure Resource Manager Templates, Azure Stream Analytics, Azure Eventhubs, Azure Function Apps, Azure SQL), Ballerina, and Python, while adhering to security best practices, scaling requirements, and optimised resource usage. • Analysed Ballerina Language Server performance and identified the cause of a memory leak using JMeter and Eclipse Memory Analyser (MAT), which helped in the optimisation of resources in Choreo. • Contributed to automating the performance testing of Choreo by creating a library and a pipeline for system metrics collection using Python, Kusto, Seaborn, and Azure DevOps pipelines. Show less



Pearson

• United Kingdom
• Education
• 700 & Above Employee

• Software Research Engineer - Applied Research and Development

  • Sep 2018 - Sep 2019

  Carried out diverse Research and Development tasks in several projects, in wide range of areas including Machine Learning (Computer Vision, NLP) and Fullstack Development. • Collaborated with two other engineers to create the minimum viable product of AI-based Public Speaking Evaluator Service (APSES) while contributing to emotion detection and speech analysis features, using Python, Keras, OpenCV, Kaldi and Flask. • Investigated on Question and Answering and built the minimal viable product of a Chatbot, which answers students’ questions based on Pearson books and other documentation, using a modified version of the Bi-Directional Attention Flow (BiDAF) model, Python and Django. • Researched and engineered the minimal viable product which automatically classifies flashcards created by the system or users under available topics, using the Universal Language Model Fine-Tuning (ULMFiT) model, Python and Django. Show less