Hi, my name is
Pranav Pai
A part-time researcher, full-time AI engineer.
I’m someone who has grown through a global journey across the UAE, Scotland, England, and Australia, shaping a perspective that blends technical depth with cultural awareness. With a background in applied AI and a completed Master’s in Data Science from the University of Melbourne, I’ve built a strong foundation in how intelligent systems are designed, deployed and used in the real world.
I'm motivated by the belief that AI should be purposeful, responsible and grounded in real world impact. I care about building systems that are transparent, reliable and aligned with ethical principles, and I'm energised by work that bridges advanced research with practical applications that empower people and strengthen complex systems.
I aim to grow into a technical leader who contributes to meaningful innovation in AI, with human value and societal impact at the core. I'm committed to continuous learning, thoughtful collaboration and building technology that drives long term, positive change.
01.
Skills & Character
Character
02.
Education History
MS in Data Science (Specialisation in AI)
University of Melbourne
Melbourne, Australia
Key Subjects:
BSc in Computer Science
Heriot Watt University
Edinburgh, Scotland
Key Subjects:
Extra Credits in Econometrics and Machine Learning
London School of Economics and Political Science (LSE)
London, England
Key Subjects:
03.
Professional History
Generative AI Researcher
AURIN
2024 - 2025
Worked as a hands-on researcher developing and deploying generative AI workflows for the FAIR evaluation of urban datasets. Focused on designing state-of-the-art transformer pipelines, ensuring outputs met principles of findability, accessibility, interoperability, and reusability (FAIR).
Senior Machine Learning Engineer
DOOR Global
2024 - 2025
Developed and deployed advanced ML systems powering the DOORWAYS AI Comic Generator, fine-tuning state-of-the-art LLMs and Diffusion models for generative storytelling.
Data Analyst
University of Melbourne
2024
Built predictive models and performed strategic data analysis to enhance funding efficiency and optimize financial resource allocation.
Software Engineer
Vitality UK
2022-2023
Delivered secure, reliable, and highly automated software solutions, emphasizing data infrastructure automation, security protocols, and robust software testing methodologies to support scalable AI/ML systems.
Project Lead
AURIN
2024 - 2025
Led the project's technical direction and coordination, managing cross-functional efforts between AI researchers, data scientists, and stakeholders. Focused on translating research goals into technical requirements, prioritising execution, and ensuring the project delivered measurable impact.
Technology Lead
DOOR Global
2024 - 2025
Led multidisciplinary AI engineering and research teams, defining strategic direction, hiring key talent, and guiding product decisions for generative AI products.
04.
Research & Projects
Detecting Prohibited Items in X-ray Images Using Deep Learning
Investigated advanced deep learning models (Faster R-CNN, Spatial Transformer Networks, and RFBNet) for detecting occluded prohibited items in security X-ray imagery, demonstrating significant improvements in detection accuracy and robustness through tailored augmentation and rigorous validation strategies.
Modular Climate Misinformation Detection with Hybrid Retriever and LLMs
Researched a scalable, memory-efficient framework for climate claim verification using hybrid retrieval (BM25, MiniLM, Flan-T5) and dual-branch classification (RoBERTa and Flan-T5). Proposed an in-context reranker to improve retrieval and demonstrated efficient LLM deployment strategies under constrained environments.
Interactive Visualisation and Interpretability of SVMs
Conducted research on enhancing interpretability of Support Vector Machines (SVMs) through an interactive web-based visualisation framework. The study investigated kernel functions, hyperparameter sensitivity, and robustness under data noise, providing novel insights into model explainability and educational applications for ML practitioners.
Sidekick: Autonomous Multi-Tool AI Agent with LangGraph
Engineered an AI agent using LangGraph to autonomously perform complex tasks such as browser automation, file manipulation, and Python code execution. Integrated Playwright, async workflows, and Dockerized infrastructure with robust error handling and persistent memory for production-grade reliability.
Autonomous Research Agent with OpenAI Agents SDK
Built multi-agent research system with OpenAI Agents SDK for contextual query planning and automated report synthesis. Delivered Gradio interface with real-time feedback for autonomous research workflows.
Full-Stack Code Generation Agent using CrewAI Architecture
Developed CrewAI-powered engineering agent system converting natural language to production-ready applications with complete documentation and test coverage. Leveraged AST parsing and agent collaboration for automated code generation with deployment support.
TreeInsights: Scalable Urban Forestry Analytics Platform
Built a real-time analytics system to explore correlations between urban tree coverage and environmental variables using government datasets. Deployed a serverless architecture with Fission, Kubernetes, and Elasticsearch for scalable data ingestion, analysis, and interactive visualisation.
05.
Recommendations
Masoud Rahimi
Lead Data Scientist
AURIN
"Pranav would be an excellent addition to any team working in data science and AI. Through AURIN's Urban Data Futures program, he showed not just strong technical skills in generative AI, but also a calm, collaborative way of working. He framed problems clearly, tested his ideas rigorously, and explained trade-offs in plain language. He turned literature into practical, reproducible data-validation workflows, took feedback on board, and helped others do their best work. I'm confident he'll make a real, immediate contribution wherever he goes."
Hao Chen
Senior Data Scientist
AURIN
"It was a great experience supervising Pranav during his data science master project. He demonstrated strong technical skills, a solid understanding of research methods, and a proactive approach to problem-solving, using both traditional and LLM-based techniques. Wishing him all the best in his future data science and AI journey."
Ming Chen
Doctoral Researcher in Computer Systems
The University of Melbourne
"I had the pleasure of supervising Pranav Pai during his research project at the University of Melbourne, where he demonstrated remarkable depth in AI, machine learning, and large-language-model research. Pranav combined theoretical insight with strong experimental design and implementation skills, producing work of genuine academic quality. Pranav showed initiative in defining research directions, analytical rigour in evaluation, and clear communication in both written and oral presentations. His leadership and collaborative mindset greatly enhanced the team's productivity and research focus. I highly recommend Pranav for future opportunities in AI/ML research or graduate study — he has the intellectual curiosity, technical strength, and independence expected of a promising researcher."
Mark Diaco
Founder
DOOR Global
"Pranav Pai is an ambitious and driven professional who made significant contributions during his time at DOOR Global. His technical skills and work ethic were evident in the projects he engaged with, and he consistently sought to achieve high standards. At DOOR we appreciate Pai's contributions and wish him the best in his future pursuits."
Aston
PhD in NLP
The University of Melbourne
"I had the pleasure of working with Pranav Pai on projects at DOOR Global. He has a deep understanding of LLM-driven pipelines, especially in using large language models as agents, and is equally strong in deployment and integration. Beyond his technical knowledge, Pranav is also excellent at communicating across engineering teams, ensuring that complex ideas are translated into actionable solutions. His combination of technical expertise and collaborative spirit makes him a highly valuable teammate."
Saad Sheikh
Practice Leader – Cloud, Data, AI & Automation
Ex-Dell Technologies
"I worked closely with Pranav on a number of projects in Data and AI , i found him a highly skilled professional in Machine Learning and Deep Learning, with a talent for translating complex user stories into fully functional, scalable software solutions. His expertise in designing robust system architectures and his collaborative spirit make him an exceptional team player who consistently contributes to group success. His strong work ethic, dedication to quality, and excellent communication skills set him apart, making him an asset to any role requiring technical or business acumen. I highly recommend him for any role in this innovative space and will like to work with him again ."
Simon Bradley
Service Architect
Vitality UK
"I've had the pleasure of working closely with Pranav for the last year or so. He was very quick to understand our API architecture and CI/CD pipeline, and very soon became a valued member of our sprint team at Vitality. He delivered a wide variety of services that were consumed by internal and external customer and business clients, all within estimated timescales and of great quality."
Rosmery Lentini
Tech Delivery Manager
Vitality UK
"Reliable, kind and hard worker. It's has been an absolute pleasure working with Pranav for a year, he's been always very helpful, supporting any critical business needs and arising priorities, delivering expected quality requirements and in a timely manner. Always kind, respectful for others and ready to help colleagues during busy and stressful times. I am glad to have worked with him and have no hesitation recommending him to potential employers."
Dilara Özel
Researcher Counsellor Ph.D., SEP
University of Glasgow
"Pranav attended my Data Analysis course for four weeks and he has been one of the hardworking students in my class. He is a responsible and productive student. He is seeking different opportunities to learn and I think the Data Analysis course is an example of it. It was a pleasure to meet him. I believe that he can have the maximum benefit and contribution if you have an opportunity to work together."
06.
Additional Information
Core Soft Skills
Open Source Projects
Active contributor to AI/ML open source projects including TensorFlow and PyTorch libraries.
Research & Publications
Conduct research and work towards publishing findings in academic journals and IEEE conferences on AI and machine learning.
Tech Events & Networking
Active attendee at tech conferences and meetups across Australia, networking and staying connected with the tech community.
Mentorship
Actively mentor junior developers and students through coding bootcamps and online platforms.
Continuous Learning
Stay current with AI research papers, experiment with open source repositories, and read books on ML system design.
Outdoor Activities
Regular hiking enthusiast exploring Australia's trails and maintaining fitness through consistent gym training.