Summary
Overview
Work History
Education
Skills
Activities
Work Availability
Work Preference
Interests
Timeline
SoftwareEngineer
Sahand Vahidnia

Sahand Vahidnia

Senior Machine Learning Engineer
NSW

Summary

Skilled Machine Learning Engineer with a PhD and extensive experience in computer vision, natural language processing, and time series analysis. Proven expertise in developing models for cognitive load classification, using physiological and behavioral data, and conducting systematic literature reviews on cutting-edge machine learning methods. Adept at utilising datasets for human pose estimation, fine-tuning models like Detectron, ViT, custm models, and LLM implementation. Practical experience with data preprocessing, model training, and front-end development for AI-driven projects, alongside a strong foundation in ML deployment technologies and Python project structuring. Active in collaborative academic and industry-focused initiatives, including leadership in AI education roles.

Overview

8
8

Years of Machine Learning experience

13
13

Years of software development expeience

Work History

Senior Machine Learning Engineer

Sydney Informatics Hub (SIH)
Sydney, NSW
4 2024 - Current
  • Working at Sydney Informatics Hub, a core research facility, across multiple roles: machine learning engineering, data science, software engineering, and data engineering across multiple projects including:
  • Pose Estimation and Game-play Technique Prediction (ongoing): Research and development of a computer vision pipeline to extract 3D player pose, Analysis of player pose and game-play techniques, Using Python, PyTorch, and CV pipelines to fine-tune and estimate pose and parametric shape
  • Geo Data Science Project: Developing Exploratory data analysis (EDA) and visualisation tools, Analysis and prediction of geopolitical incidents and events in spatiotemporal dimensions, Using Python, geopandas, pandas, scikit-learn, and other relevant data science tools
  • Designed, implemented and evaluated new models and rapid software prototypes to solve problems in machine learning and systems engineering.
  • Developed custom machine learning algorithms for specific industry needs, resulting in improved performance and efficiency.
  • Worked closely with domain experts to ensure accurate representation of problem context within developed models, enhancing their real-world applicability.
  • Collaborated with cross-functional teams to integrate machine learning solutions into existing software systems, streamlining processes and boosting productivity.
  • Modeled predictions with feature selection algorithms.

Research Associate

The University of New South Wales, ADFA
Canberra, ACT
05.2024 - 10.2024
  • Worked as a research associate at the University of New South Wales on AI related projects
  • Cognitive Workload Classification: Research and development in understanding aviators' workload balance, using AI and machine learning techniques, Simulation data analysis and feature engineering, Using Python, Tensorflow, Pandas, and other tools and technologies
  • Conducted thorough literature reviews to identify gaps in knowledge and inform future research directions.
  • Utilized statistical packages to analyze data and create visualizations.

Data Science Software Engineer

Sydney Informatics Hub (SIH)
Sydney, NSW
01.2023 - 04.2024
  • Plant Available Water Prediction Project: Developing a comprehensive Nextflow pipeline for data processing and modelling, deployable across GCP batch, AWS, and on-premise environments, Utilising Python to develop efficient modules for managing geospatial data ingestion, preprocessing, training, prediction, post-processing, and modelling, Key technologies used include Docker, TensorFlow, rioxarray, geopandas, and rasterio, Preparing reports and dynamic documentation (Sphinx) to communicate the outcome with stakeholders
  • Aerial Segmentation Project: Engineering and implementing an end-to-end training and prediction software for identifying local climate zones, addressing significant challenges in converting georeferenced data to annotations and vice versa, Using Python addressing significant challenges in converting georeferenced data to annotations and vice versa, and model development, Key technologies used include Pytorch, rioxarray, geopandas, rasterio, pandas, and OpenCV, Collaborated with an agile (scrum) team and collaboration through GitHub, code reviews, and pair programming practices, Utilised GitHub Actions and other CI/CD tools
  • Data Engineering and Consultation Project: Refining a Terraform infrastructure for enhanced security and consistency, leading to the development of a sensitive data de-identification pipeline, Utilising Oracle database in AWS RDS, AWS Glue, and EC2, all orchestrated via Terraform
  • Developed scalable and maintainable code, ensuring long-term stability of the software.
  • Developed reusable components that significantly reduced development effort on multiple projects.
  • Established efficient communication channels within the team, leading to better collaboration among members during project development phases.
  • Developed custom machine learning algorithms for specific industry needs, resulting in improved performance and efficiency.
  • Developed advanced graphic visualization concepts to map and simplify analysis of heavily-numeric data and reports.
  • Streamlined data ingestion pipelines by automating repetitive tasks, reducing processing times significantly while maintaining high-quality outputs.

PhD Researcher in Computer Science

The University of New South Wales
02.2019 - 06.2023
  • Led a novel research project in topic analysis in AI utilising Natural Language Processing (NLP) and Expert Systems: Significantly contributed to the fields of Science of Science and AI, as evidenced by my published work, such as in the highly regarded journal article accessible at ESWA, Developed and released open-source, containerised software solutions, enhancing the reproducibility and accessibility of research findings within the scientific community, Worked collaboratively with fellow researchers, supervisors, and the broader scientific community to share insights, gather feedback, and enhance the overall quality and impact of my research

Research Assistant

Australian National University, Research School of Management
11.2021 - 03.2022
  • Worked at RSM on a sophisticated multi-criteria decision support system: Led the end-to-end engineering and development of the decision support system, ensuring the software fully met the client's specifications and operational requirements, Utilised Python and popular data science libraries, Actively engaged with the client through regular meetings to accurately scope the project and refine its requirements

Research and Development Engineer (R&D)

Istanbul Technical University, Aerospace Research Centre (AI Research Lab)
01.2018 - 01.2019
  • Worked across multiple roles and projects
  • Significant projects are as follows: Structural Health Monitoring for General Electric (GE) Turkey: Researched and developed a state-of-the-art non-destructive algorithm aimed at monitoring the structural integrity of gas turbines, Utilised machine learning (computer vision) via TensorFlow (and Python) to analyse and predict potential failures, Led the team, managing the development in an agile environment, guiding the team in using proper software engineering practices such as using GitHub and relevant tools, Delivered an end-to-end training and prediction software, training material for GE, in addition to a published Q1 journal article
  • Autonomous Driving Vehicle System for AVL Turkey: Developed advanced deep learning models for object tracking under challenging conditions, Deployed models on Nvidia Jetson boards, showcasing exceptional real-time performance, Utilised a combination of TensorFlow, Torch, and lower-level libraries in Python and C++ to achieve high accuracy and speed, meeting AVL Turkey's stringent requirements for embedded system performance, Actively collaborated with cross-functional teams and industry partners, providing expert insights into machine learning and software engineering best practices

Research and Development Engineer (R&D)

Ankara University
01.2016 - 01.2017
  • Worked across multiple projects in dynamic teams
  • Significant projects are: LiverVIsion Project: Significantly contributed to the development of LiverVision, a medical software for liver segmentation, detection, measurement, and interactive visualization, Some technologies used are C++, ITK, VTK, and Qt, Collaborated with partners including Ankara University Hospital and under nondisclosure agreements with pharmaceutical clients, aimed to advance liver transplant and diagnosis processes, Received media coverage in newspaper (page 4) and national news
  • Other projects: Contributed to research and development of computer vision and OCR software for external clients

Programmer and Software Engineer

Raham Co. (now dissolved)
01.2011 - 01.2014
  • Served as a full-stack developer across numerous projects: Led the end-to-end web development process, ensuring the creation of robust, scalable, and user-friendly digital solutions, Utilised the PHP, MySQL, JavaScript stack for building secure, efficient, and responsive applications, incorporating best practices and emerging technologies, Worked closely with team members with agile and scrum strategies, collaborated through Git and other tools

Education

Ph.D. - Computer Science

The University of New South Wales
01.2019 - 01.2023

M.Sc. - Computer Engineering

Ankara University
01.2014 - 01.2016

B.Sc. - Information Technology Engineering

Azarbaijan Shahid Madani University
01.2008 - 01.2013

Skills

Natural Language Processing

Activities

  • Program committee member at ICONIP 2021
  • Program committee member at ICONIP 2022 (chair candidate)
  • Reviewer at IEEE Transactions on Computational Social Systems
  • Reviewer at IEEE Transactions on Cybernetics
  • Active reviewer at Scientometrics journal

Work Availability

monday
tuesday
wednesday
thursday
friday
saturday
sunday
morning
afternoon
evening
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Work Preference

Work Type

Full Time

Work Location

HybridRemoteOn-Site

Important To Me

Company CulturePersonal development programsCareer advancement

Interests

Software Development

Artificial Intelligence

Computer Vision

Natural Language Processing

Expert Systems

Timeline

Research Associate

The University of New South Wales, ADFA
05.2024 - 10.2024

Data Science Software Engineer

Sydney Informatics Hub (SIH)
01.2023 - 04.2024

Research Assistant

Australian National University, Research School of Management
11.2021 - 03.2022

PhD Researcher in Computer Science

The University of New South Wales
02.2019 - 06.2023

Ph.D. - Computer Science

The University of New South Wales
01.2019 - 01.2023

Research and Development Engineer (R&D)

Istanbul Technical University, Aerospace Research Centre (AI Research Lab)
01.2018 - 01.2019

Research and Development Engineer (R&D)

Ankara University
01.2016 - 01.2017

M.Sc. - Computer Engineering

Ankara University
01.2014 - 01.2016

Programmer and Software Engineer

Raham Co. (now dissolved)
01.2011 - 01.2014

B.Sc. - Information Technology Engineering

Azarbaijan Shahid Madani University
01.2008 - 01.2013

Senior Machine Learning Engineer

Sydney Informatics Hub (SIH)
4 2024 - Current

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Sahand VahidniaSenior Machine Learning Engineer