Expert in Analog, Mixed-Signal, Low-Power VLSI, SOI, SOS, Image Sensors, Sensors, Biomedical Instrumentation,
Expert has experience with sensors, VLSI circuits and sensors interfaces, sensor networks, imager sensor networks, image sensors, biomedical circuits and systems. He also has experience in SOI, SOS design, silicon on insulator, and silicon on sapphire process, as well as analog and mixed-signal design of VLSI systems and circuits.
Expert provides custom analog IC design, mixed-signal and RF design, IC layout and verification, and development services for board design and system design. He also creates mixed-signal and analog modules for SoC and ASIC chips that are used in applications such as analog-front-ends (AFE) and transceiver modules for wireless, imaging, sensor interface, and communications. He has experience in chip design, board design and system design for sensors, sensor networks, and interfaces.
Expert has experience in the design and development of retinal implants and artificial vision sensors, image sensors, bio inspired sensors, biomimetic image sensors, and neuromorphic engineering sensors.
Expert has experience in biosensors design for patch clamp applications, neural recordings, neural stimulators, and telemetry.
Expert takes hints from nature and from other scientific research fields to add and improve on the performance, efficiency, and dynamic range of sensory circuits and systems. He targets biomedical application and uses modern fabrication technologies and thoughtful targeted design to engineer systems to improve everyday life and to help the scientific endeavor of understanding life at the pillars of creation.
We are developing synthetic models of the mammalian visual system in hardware. We design both bio-inspired image sensors
and hardware visual processing circuits.
This work was featured in the media (MSNBC, New York Times podcast, the Economist, International Business Times, Science
Daily, gizmag, Yale News, to name a few - Google "Neuflow" or "NeoVision + Expert" to get them all) in the Fall 2010.
We are developing bio-inspired neuromorphic algorithms and neural processing hardware to model the ventral pathways of the
mammalian visual system.
What does it take for a microchip to be able to:
- Find and categorize objects of interest in a scene?
- How do you find and define points of interest in a scene? Which attention algorithms?
- Is segmentation, stereo, optical flow and object categorization related? How?
- How can we track an object in the scene when its features change with each frame?
- How do we infer high-order behavior from a movie? What did that person just do in this movie?
Our goal is to provide an artificial vision system that is capable of performing at the same levels of the human visual system. In
order to do this, we embed all the top computer vision algorithms and vision neuroscience findings into a complex computer
designed to replicate human vision.
For this purpose, we are developing NeuFlow: a dataflow computer for bio-inspired visual processing aimed at speeding up the
computations of state-of-the-art vision algorithms and holistic vision systems. NeuFlow is a custom microprocessor with arrays
of computing elements suited to accelerate computations on videos and streaming data (data flow).
NeuFlow was first implemented for convolutional neural networks. These networks have been successfully used in many
recognition and classification tasks including document recognition, object recognition, face detection and robot navigation, and
combined with our Dataflow Computer, they can perform in real-time on megapixel-size video streams. Applications are in robotic
vision, security, monitoring and also in posture recognition, assisted living and remote care of elderly patients.
Expert may consult nationally and internationally, and is also local to the following cities: Chicago, Illinois - Joliet, Illinois - Champaign, Illinois - Indianapolis, Indiana - Fort Wayne, Indiana - South Bend, Indiana - Gary, Indiana - Hammond, Indiana - Bloomington, Indiana - Muncie, Indiana
|Year: 2004||Degree: Ph.D.||Subject: Electrical and Computer Engineering||Institution: Johns Hopkins University|
|Year: 1999||Degree: M.S.||Subject: Electrical and Computer Engineering||Institution: Johns Hopkins University|
|Year: 1997||Degree: M.S.||Subject: Electronics Engineering||Institution: University of Trieste, Italy|
|Years: 2011 to Present||Employer: Undisclosed||Title: Associate Professor||Department: Biomedicall Engineering||Responsibilities: Expert teaches two course/year, leads research, and advises graduate students.|
|Years: 2004 to 2011||Employer: Yale University||Title: associate professor||Department: Electrical Engineering||Responsibilities: Expert teaches two course/year, leads research, and advises graduate students.|
|Associations / Societies|
|Expert is a member of IEEE and CMOC (Connecticut Micro Opto Consortium).|
|He serves on the CMOC board.|
|Awards / Recognition|
|Presidential early career award for science and engineering by president barack Obama, 2010|
|Publications and Patents Summary|
|Expert has >100 articles and >5 patents.|
|Italian||Expert is fluent in speaking, reading, and writing Italian.|
|Chinese||He can speak and read Chinese at an "average" level.|
|Korean||Expert can speak and read Korean at a basic level.|