Simeon Bamford

Neural and Neuromorphic Engineering and Machine Learning

I find neural systems fascinating, and I love to engineer them. I have decades of experience with AI and its applications.

I've worked from machine learning and computational neuroscience, through neuromorphic sensors and processors, to prosthetic systems and wet biology.

In particular, I've developed lots of know-how as a neuromorphic engineer, creating electronic circuits which mimic computation in nervous systems. These circuits, integrated on microchips, often use electrical currents to imitate currents in our nerve cells and brains. I'm therefore skilled at mixed-signal (analogue, asynchronous digital) silicon chip design and test (VLSI - CMOS, CIS), as well as PCBs, FPGA logic and software, from algorithms to applications.

As an entrepreneur and technologist, I've been involved in the commercialisation of neuromorphic vision sensors, also known as event cameras or dynamic vision sensors. This has taken me into dozens of commercial R&D departments and I've developed an unparalleled insight into the current attempts of many major companies to adopt neuromorphic technology.

I've also worked on cloud deployment (AWS) of deep learning models for natural language processing; I've learnt Tensorflow, Lambda serverless compute and Gremlin graph database. This high-level focus on practical applications of neural networks has complemented my understanding of their low-level properties.

Recently I've been further developing applications of event-based perception, for robotics. At IIT our robot is equipped with event-based sensors for both vision and touch. I've been mixing 3D geometrical algorithms and deep learning models for perception.

I see huge potential in neural computation, AI and robotic technology to assist us and improve our lives. I'm also very curious to understand more about how our nervous systems allow us to function, and how our mental lives arise.

Projects (past and present)

Key publications

(Further publications are listed in project-specific pages; see also google scholar)