乔尔·詹宁斯，英国剑桥的开发者
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乔尔·詹宁斯

验证专家  in 工程

机器学习开发人员

位置
剑桥，英国
至今成员总数
2019年12月20日

乔尔 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.

算法机器学习嵌入式系统CPythonPython 2Python 3NumPy覆盆子πTensorFlowPyTorch深度神经网络嵌入式硬件蓝牙概率图形模型传感器融合

Availability

兼职

首选的环境

Emacs, Linux, Git

最神奇的...

...project I've worked on was using machine learning to decode neural signals being sent down the vagus nerve of a live subject.

工作Experience

机器学习与软件工程

2020年至今
自由
  • Published a multi-agent reinforcement learning paper at ICML with Huawei.
  • Deployed TensorFlow audio models to a 覆盆子π 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.
技术:Python, PyTorch

机器学习研究负责人

2020 - 2021
BIOS.健康
  • 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.
技术:机器学习，PyTorch

机器学习团队负责人

2017 - 2020
小偷.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, 码头工人, 和气流.
  • 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.
技术:统计学，Python, TensorFlow, PyTorch

高级嵌入式软件工程师

2013 - 2016
剑桥顾问
  • Developed a satellite remote sensing camera for the Zoological Society of London to study animals and prevent poaching, 使用Atmel AVR和树莓派. 该摄像机被部署在肯尼亚和南极洲.
  • Created a virtual queuing wristband for theme parks involving NFC, 蓝牙, 和罗拉在北欧nRF52(基于ARM Cortex M4)上. 有关更多信息，请参阅Portfolio Projects.
  • Created iPad app for asset tracking for the placement of US internet cables for a telecommunications company.
  • 开发了蓝牙低功耗EpiPen iPhone应用程序, 指导用户如何执行注射.
  • Developed the firmware of a demonstrator of an energy harvested 蓝牙 enabled insulin injector. This device was capable of communicating dosage amount to a smartphone, 只使用身体注射胰岛素的能量.
  • Wrote a tool to automatically generate C code for 蓝牙 LE profiles for a semiconductor company.
  • Developed 蓝牙 audio applications using CSR hardware (now part of Qualcomm).
技术:嵌入式C、C、咨询

平均野外游戏

http://www.PROWLER.io/research/decentralised-learning-in-systems-with-many-many-strategic-agents
在一个顶级人工智能会议上发表的研究中, I was responsible for performing experiments and validation for using 强化学习 to play games that involved thousands of agents. This involved creating and training neural networks in TensorFlow. The techniques developed in the paper could be used for placing mobile network points for major public gatherings.

地下资产追踪

Underground asset tracking is a huge issue when it comes to such things as digging in the ground and trying to avoid hitting existing utilities. I worked on a universal mobile app that allows engineers to query and locate any underground cabling. The app initially targeted the iPad but was built with technologies that allowed for its subsequent port over to Android. Titanium框架与Java一起使用, objective - c, and JavaScript to bring together all the essentials in connecting an iPad to a 蓝牙 device and data visualizations for the assets via the Google Maps API.

主题公园的虚拟排队手环

I was part of a team that developed a wristband to create a virtual queuing waterpark in Florida. 这个设备有蓝牙、罗拉和NFC无线电. It had to have tiny power consumption to allow it to last all day and also had to be waterproof. 它使用了北欧nRF52 SoC(基于ARM Cortex M4).

我编写的引导加载程序允许通过蓝牙进行软件更新, 实现框架, 以及LED显示屏的驱动, as well as parts of the NFC interface that were used to allow the wristband to make payments and initiate queueing. 我负责优化电力消耗.

语言

Python, C, 嵌入式C, Python 2, Python 3, C++, Haskell, 生锈, Java, objective - c, 伊德里斯, 打印稿, 斯威夫特

库/ api

TensorFlow, NumPy, PyTorch, Matplotlib, Pandas, LAPACK

平台

覆盆子π, ARM Linux, Linux, 蓝牙 LE, Amazon Web Services (AWS), Android, MacOS, Windows

其他

人工智能(AI), 嵌入式系统, 统计数据, 算法, 机器学习, 神经网络, 传感器数据, 传感器融合, 硬件驱动程序, 嵌入式硬件, 蓝牙, 概率图形模型, 贝叶斯推理 & 建模, 贝叶斯统计, 深度神经网络, 强化学习, 深度强化学习, 线性代数, 卡尔曼滤波, 硬件, 近场通信(NFC), 罗拉, 咨询, 人员管理, 时间序列, 数学

工具

Emacs, Vim Text Editor, Git, GitHub, Bitbucket, Subversion (SVN)

范例

Functional Programming, Object-oriented Programming (OOP), Agile, Management

框架

瓶,促进

2010 - 2013

Ph.D. 在生物物理学

剑桥大学-剑桥，英国

2009 - 2010

计算生物学硕士学位

剑桥大学-剑桥，英国

2008 - 2009

管理学学士学位

剑桥大学-剑桥，英国

2005 - 2008

数学学士学位

剑桥大学-剑桥，英国

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