Joel Jennings
Verified Expert in Engineering
Machine Learning Developer
Joel has a strong mathematics background and spent three years working as a software engineer at a consultancy firm, specializing in embedded software while gaining a broad knowledge of different technologies. He has worked as a machine learning engineer on a range of tasks, from implementing algorithms in research papers to engineering deployed machine learning systems. He is driven by projects that use exciting theories to solve real-world problems.
Portfolio
Experience
Availability
Preferred Environment
Emacs, Linux, Git
The most amazing...
...project I've worked on was using machine learning to decode neural signals being sent down the vagus nerve of a live subject.
Work Experience
Machine Learning and Software Engineer
Freelance
- Published a multi-agent reinforcement learning paper at ICML with Huawei.
- Deployed TensorFlow audio models to a Raspberry Pi using TensorFlow Lite. The audio was detected using a directional microphone and would allow the attached camera to focus on areas with anomalous sounds.
- Developed a demonstrator of the UK highways traffic data that provides real-time information about the states of the roads to enable operators to more quickly detect and respond to congestions and accidents.
- Created a Python Flask back end running on AWS to allow shoppers to offset their products' carbon through Shopify.
Machine Learning Research Lead
BIOS.health
- Developed a pipeline for analyzing peripheral nervous system data.
- Created an iOS Watch app for assessing patients' ability to perform a six-minute walk test.
- Managed a team of 6 ML researchers, engineers, and neural scientists.
Machine Learning Team Lead
PROWLER.io/ Secondmind.ai
- Created a time series modeling library in TensorFlow for developing Gaussian Process models with faster inference through stochastic differential equation techniques.
- Took responsibility for taking Gaussian process models from research code into a finance product using Kubernetes, Docker, and Airflow.
- Implemented neural network-based algorithms in TensorFlow that led to paper publications at machine learning conferences as part of the multi-agent reinforcement learning team.
- Served as the technical lead for a logistics time series forecasting customer project.
- Managed the professional development of several machine learning engineers and performed interviews and coding test reviews as part of the recruitment process.
Senior Embedded Software Engineer
Cambridge Consultants
- Developed a satellite remote sensing camera for the Zoological Society of London to study animals and prevent poaching, using an Atmel AVR and Raspberry Pi. The camera was deployed in Kenya and Antarctica.
- Created a virtual queuing wristband for theme parks involving NFC, Bluetooth, and LoRa on a Nordic nRF52 (based on a ARM Cortex M4). See Portfolio Projects for more information.
- Created iPad app for asset tracking for the placement of US internet cables for a telecommunications company.
- Developed a Bluetooth Low Energy EpiPen iPhone app, that guided users through how to perform an injection.
- Developed the firmware of a demonstrator of an energy harvested Bluetooth enabled insulin injector. This device was capable of communicating dosage amount to a smartphone, using only the energy from physically injecting the insulin.
- Wrote a tool to automatically generate C code for Bluetooth LE profiles for a semiconductor company.
- Developed Bluetooth audio applications using CSR hardware (now part of Qualcomm).
Experience
Mean Field Games
https://www.prowler.io/research/decentralised-learning-in-systems-with-many-many-strategic-agentsUnderground Asset Tracking
Virtual Queueing Wristband for a Theme Park
I wrote the bootloader to allow software updates over Bluetooth, implemented the framework, and the drivers for the LED display, as well as parts of the NFC interface that were used to allow the wristband to make payments and initiate queueing. I was responsible for optimizing power consumption.
Skills
Languages
Python, C, Embedded C, Python 2, Python 3, C++, Haskell, Rust, Java, Objective-C, Idris, TypeScript, Swift
Libraries/APIs
TensorFlow, NumPy, PyTorch, Matplotlib, Pandas, LAPACK
Platforms
Raspberry Pi, ARM Linux, Linux, Bluetooth LE, Amazon Web Services (AWS), Android, MacOS, Windows
Other
Artificial Intelligence (AI), Embedded Systems, Statistics, Algorithms, Machine Learning, Neural Networks, Sensor Data, Sensor Fusion, Hardware Drivers, Embedded Hardware, Bluetooth, Probabilistic Graphical Models, Bayesian Inference & Modeling, Bayesian Statistics, Deep Neural Networks, Reinforcement Learning, Deep Reinforcement Learning, Linear Algebra, Kalman Filtering, Hardware, Near-field Communication (NFC), LoRa, Consulting, People Management, Time Series, Mathematics
Tools
Emacs, Vim Text Editor, Git, GitHub, Bitbucket, Subversion (SVN)
Paradigms
Functional Programming, Object-oriented Programming (OOP), Agile, Management
Frameworks
Flask, Boost
Education
Ph.D. in BioPhysics
University of Cambridge - Cambridge, United Kingdom
Master's Degree in Computational Biology
University of Cambridge - Cambridge, United Kingdom
Bachelor's Degree in Management Studies
University of Cambridge - Cambridge, United Kingdom
Bachelor's Degree in Mathematics
University of Cambridge - Cambridge, United Kingdom
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