Profile
Jillur Quddus is a computational mathematician, polyglot software engineer and published author who specialises in the design and engineering of innovative, high-performance, ethical and secure artificial intelligence (AI) systems. Jillur is also the founder of HyperLearning AI which he started with the aim of improving accessibility and diversity in the fields of applied mathematics, scientific computing and artificial intelligence, as well as to ensure that AI delivers real and positive social impact.
Jillur's core areas of expertise include graph theory, designing real-time neural interfaces for smart devices, applying artificial intelligence to emerging infectious disease modelling and preventative healthcare, and combatting Dark Web-enabled crime. Jillur has deep experience of working within central and local government, healthcare, intelligence and law enforcement, and has worked extensively across the world including in Japan, Singapore, Hong Kong, Malaysia, Australia, New Zealand and the United Kingdom.
計算数学者のJillur（ジラー）は、重大組織犯罪、金融犯罪、詐欺、サイバー犯罪と対抗することを目的とした、注目の最先端解析およびデータに関する技術ソリューションを設計・開発する仕事に世界中で従事してきました。日本、ニュージーランド、シンガポール、マレーシア、香港、英国と、長年の経験があります。
Core Skills
- Software Engineering
Python • Java • Spring Framework • JavaScript • Node.js • SQL • Gremlin • Linux • Shell Scripting - Distributed Computing
Apache Spark • Dask • PyTorch • TensorFlow • Apache TinkerPop • Apache Kafka • NoSQL • Elasticsearch - Data Science and Artificial Intelligence
Statistical Learning • Machine Learning • Deep Learning • Graph Theory • Natural Language Processing - Public Cloud
Amazon Web Services (AWS) • Google Cloud Platform (GCP) • Google Firebase • Elastic Cloud • Linode
Selected Professional Experience
- Joint Biosecurity Centre - Lead Data Scientist
Jillur led an expert team of globally leading mathematicians, epidemiologists, AI research fellows and technology professionals, responsible for rapidly developing bleeding-edge disease modelling systems. By utilising the latest research in machine learning and artificial intelligence, the systems were capable of modelling the global transmission of COVID-19 in near real-time, and simulating the impact of non-pharmaceutical interventions (NPIs) such as lockdown events. The resultant disease models enabled the Scientific Group for Emergencies (SAGE) to identify both known and previously unknown clusters of COVID-19 outbreaks, coupled with the ability to understand both the key drivers of transmission between localised clusters, and the likely impact of NPIs. - Government (UK) - Lead Artificial Intelligence Engineer
Jillur led an expert team of intelligence officers, cryptographers, analysts and subject matter experts responsible for combatting Dark Web-enabled serious organised crime, including child sexual exploitation & abuse (CSEA) and human trafficking, through the analysis of anonymous decentralised networks and cryptographic protocols. - Local Government (UK) - Lead Data Scientist & Java Engineer
Jillur designed and built an award-winning artificial intelligence system capable of autonomously detecting, classifying and prioritising cases of potholes and fly-tipping in real-time through the development of a bespoke deep convolutional neural architecture and neural interface capable of processing images at 45fps with less than 25ms latency delivering up to 40 detection events per second, integrated with a bespoke Android mobile app and GPS location services.
Selected Open Source Projects
- Teddy - Project Owner & Lead Developer
Opinionated open-source content management system (CMS) and static site generator (SSG) that focuses on simplicity and easy content management.
Website • Source Code - Cerebro - Project Owner & Lead Developer
Virtual reality (VR) enabled interactive 3D visualisation and exploration of small to medium sized graphs.
Website - Python Taster Course - Project Owner & Lead Developer
A fun and interactive introduction to both the Python programming language and basic computing concepts using programmable robots.
Website • Source Code
Publications
- Machine Learning with Apache Spark
Uncover patterns, derive actionable insights and learn from big data using MLlib.
Amazon • Google Play • Waterstones
Languages
- English • Native
- Japanese 日本語 • Advanced (日本語能力試験 JLPT N2)
- Chinese Cantonese 廣東話 • Conversational