Recovering academic. Distinguished raggamuffin.
I'm a scientist, engineer, photographer and motorcyclist — though not necessarily in that order.
I'm fascinated with the process by which our minds create the world we experience and how psychology and philosophy can impact our lives.
I'm a culinary data scientist. I spend my days studying how customers interact with the menu of a large
Once upon a time, I was an academic researching human visual perception, including how image appearance changes with size and how perception of brightness & contrast influence the design of monitors. I have been an engineer, working at Adobe on photography apps such as Photoshop Fix, and at Dolby on the Vision line of high-end displays, amongst other things. Find many more interesting facts in my curriculum vitae.
I think the only excuse to not be learning is because you're dead (and even then I'm not positive). As such, I spend a lot of time reading.
While I crave movement, San Francisco is where I'm most often found. Prior to there, home has been Vancouver, Pittsburgh, Washington DC and a few other places.
At other times I've been a cyclist, martial artist, powerlifter and health nut. I may be again some day. I'm a pretty damn good cook.
A Twitter bot that posts the current water levels of major California reservoirs. The project is an attempt to better understand the place I live and the forces that shape my life here, and few things are more important to a Californian than the availability of water. Inspired by Kevin Kelly's excellent The Big Here.
Recognizing Image Style
The style of an image plays a significant role in how it is viewed. We predict the style of images, and perform a thorough evaluation of different image features for these tasks. Features learned in a multi-layer network generally perform best — even when trained for a different task.
Image Features in Python
The quality of features can make or break a machine learning project. At PyData, I presented ways to extract features from images using Python tools that can be readily used by developers familiar classification and clustering algorithms. See also: talk video and slides.
Scale-dependent perception of images
My doctoral research examined ways in which perception of images changes when they are viewed at different sizes. Due to the organization of the visual system, the appearance of blurred and sharpened edges depends on the width of the edge. Besides the study, we propose several methods to address the change.
- Developing on a remote server
- iBooks Highlights
- California WaterBot
- Adobe Photoshop Fix
- Recognizing Image Style
- Image Features in Python (talk) (slides)
Scale-Dependent Perception of Countershading: Enhancement or Artifact?
- Color Splash
- Manipulating Scale-Dependent Perception of Images (Ph.D.)
- Glare Encoding of High Dynamic Range Images
- Blur-Aware Image Downsizing
- Defocus Techniques for Camera Dynamic Range Expansion
- Dolby Vision display
- Photometric Image Processing for High Dynamic Range Displays
On-the-fly Reverse Tone Mapping of Legacy Video and Photographs
- Photometric Image Processing for High Dynamic Range Displays (M.Sc.)
- High Dynamic Range Techniques in Graphics: from Acquisition to Display
- Real Illumination from Virtual Environments (video)
- Volume Rendering for High Dynamic Range Displays
- High Dynamic Range Display Systems
- Implementing Performance Numerical Libraries on Graphics Hardware (B.Sc.)
Get in touch via email (my initials at this domain), Twitter or Facebook.
What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information…