Jeffrey Hightower

Software Engineering Manager

Google Inc.
651 North 34th Street
Seattle, WA 98103



Google Maps for mobile
Google Maps for mobile
|| I work to put a visually stunning map, powerful local search tool, and full-featured navigation system in your pocket.
Squeezable Haptics
SqueezeBlock: A Squeezable Interface for Mobile Devices || Touch is underused as a human-computer interface. Our SqueezeBlock prototype was an electro-mechanical system to realize a virtual spring. It could programmatically alter its squeezability, shape, and texture patterns to convey information to its user in an eyes-free fashion.
Remote Control Identity Inference
Remote Control Identity Inference || Accelerometers and key press sensors embedded in embedded devices such as television remote controls can be used to distinguish household members based on the unique way each person wields the remote. This personalization capability can be used, for example, to enhance digital video recorders with show recommendations per family-member instead of per device.
Low Power Face Recognition on a netbook
Low Power Face Recognition || Mobile computer vision brings new possibilities to everyday experiences. For example, face recognition and visual location detection enable easy authentication and simple reminders as you walk through the world. This project was about making cutting-edge computer vision and perception algorithms practical on mobile devices through platform-integrated machine learning, low power networking, and parallelization in the network cloud.
InertiaDot (YouTube vido)
|| The InertiaDot is a compact self-contained battery-operated 6 degree-of-freedom Bluetooth-wireless Attitude and Heading Reference System (AHRS). It features a 2000 degree per second rotational response and fits in a 27x30x8mm package weighing only 9.8 grams. AHRS computation is done on-board, based on a non-linear estimation filter developed for the DIY Drones UAV DevBoard from work of [Mahoney et al. 2006].
Mobile Sensing Platform
|| To research mobile inferrence of user behavior and context, the University of Washington and Intel Labs Seattle designed a device called the Mobile Sensing Platform (MSP) for real-time processing of sensor traces, activity inference, and conversation understanding. We built 100 MSPs to give to collaborators in the research community.
Place Lab || Place Lab established the viability of the radio-beacon location technology that is a core capability in most modern smartphones and mobile devices. Read an overview paper or watch me give a research talk about Place Lab.
Reno: Location Sharing
Reno: Location Sharing || Reno was a peer-to-peer, mobile, location-enhanced messaging service forshadowing modern commercial services like Dodgeball, Foursquare, Google Latitude, and Facebook check-ins. We developed Reno to investigate techincal and social issues around disclosing an individual's location including why, when, and what people want to share about their location; the effectiveness automatic location disclosure; strategies to achieve plausible deniability; and understanding how place and activity are used to communicate plans, intentions and provide awareness.
SpotON || The SpotON ad hoc radio location hardware was early work to determine the position of individual nodes in an ad hoc wireless network. My SpotON signal strength measurement circuitry was used in the radio design of the original Berkeley motes.
The Location Stack
The Location Stack || My old PhD thesis work on design and sensor fusion for location-enhanced computing.