Demo Data from EDBT 2026 / reviewers in the wild / expert
Mathew Laibowitz
dblp:33/1823
· DBLP profile ↗
4ranked-venue papers
2as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Visual content generation and editing · 100% | |
| Human-computer interaction and pervasive computing
2 papers |
Ubiquitous computing and smart environments · 65% Wearable and physiological sensing · 22% Collaborative and social computing · 13% | |
| Computer networks
1 paper |
Internet of things and sensor networks · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Energy-efficient computing · 100% |
Topics — the 6 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visual content generation and editing › video editing
automatic video editing |
0.1 | 1 | 2010 | Multimedia content creation using societal-scale ubiquitous camera networks and human-centric wearable sensing · ACM Multimedia 2010 |
Visual content generation and editing
multimedia content creation |
0.1 | 1 | 2010 | Multimedia content creation using societal-scale ubiquitous camera networks and human-centric wearable sensing · ACM Multimedia 2010 |
Internet of things and sensor networks
wireless sensor network |
0.1 | 1 | 2007 | CargoNet: a low-cost micropower sensor node exploiting quasi-passive wakeup for adaptive asychronous monitoring of exceptional events · SenSys 2007 |
Wearable and physiological sensing
on-body sensing |
0.0 | 1 | 2010 | Multimedia content creation using societal-scale ubiquitous camera networks and human-centric wearable sensing · ACM Multimedia 2010 |
Energy-efficient computing
energy harvesting |
0.0 | 1 | 2007 | CargoNet: a low-cost micropower sensor node exploiting quasi-passive wakeup for adaptive asychronous monitoring of exceptional events · SenSys 2007 |
Collaborative and social computing › social interaction › social interaction analysis
group interaction analysis |
0.0 | 1 | 2006 | A sensor network for social dynamics · IPSN 2006 |
Methods — techniques the papers use, named apart from their topics
video stitching · 0.2sensor fusion · 0.2custom low-power circuit design · 0.1sensor deployment study · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Multimedia content creation using societal-scale ubiquitous camera networks and human-centric wearable sensingabstractWe present a novel approach to the creation of user-generated, documentary video using a distributed network of sensor-enabled video cameras and wearable on-body sensor devices. The wearable sensors are used to identify the subjects in view of the camera system and label the captured video with real-time human-centric social and physical behavioral information. With these labels, massive amounts of continually recorded video can be browsed, searched, and automatically stitched into cohesive multimedia content. This system enables naturally occurring human behavior to drive and control a multimedia content creation system in order to create video output that is understandable, informative, and/or enjoyable to its human audience. The collected sensor data is further utilized to enhance the created multimedia content such as by using the data to edit and/or generate audio score, determine appropriate pacing of edits, and control the length and type of audio and video transitions directly from the content of the captured media. We present the design of the platform, the design of the multimedia content creation application, and the evaluated results from several live runs of the complete system. Mathew Laibowitz, Nan-Wei Gong, Joseph A. Paradiso |
ACM Multimedia | 1 |
| 2010 | Identifying and facilitating social interaction with a wearable wireless sensor network
Joseph A. Paradiso, Jonathan Gips, Mathew Laibowitz, Sajid Sadi, David Merrill, Ryan Aylward, Pattie Maes, Alex Pentland |
Pers. Ubiquitous Comput. | 3 |
| 2007 | CargoNet: a low-cost micropower sensor node exploiting quasi-passive wakeup for adaptive asychronous monitoring of exceptional eventsabstractThis paper describes CargoNet, a system of low-cost, micropower active sensor tags that seeks to bridge the current gap between wireless sensor networks and radio-frequency identification (RFID). CargoNet was aimed at applications in environmental monitoring at the crate and case level for supply-chain management and asset security. Custom-designed circuits and sensors were utilized to minimize power consumption and cost in a practical prototype. The CargoNet nodes are capable of asynchronous multimodal wakeup on exceptional events at extremely low power (Quasi-Passive Wakeup) with adjustable thresholds that adapt to dynamic environments. Accordingly, CargoNet has been seen to monitor, log, and report conditions inside a typical shipping crate while consuming under 25 microwatts of average power. To demonstrate the feasibility of the prototype system, several tests and deployments were conducted in the laboratory and aboard various transport conveyances. Mateusz Malinowski, Matthew Moskwa, Mark Feldmeier, Mathew Laibowitz, Joseph A. Paradiso |
SenSys | 4 |
| 2006 | A sensor network for social dynamicsabstractThis paper describes the design and architecture of the UbER-Badge, a wireless sensor node and wearable display designed to facilitate group interaction in large meetings and acquire a wide range of data for analyzing social dynamics. The platform design and its application suite are described. Data is presented that shows the social patterns developing across large events and indicates that certain individual characteristics (interest, affiliation) can be determined from the sensor data from deployments of this system with groups of over 100 people. Mathew Laibowitz, Jonathan Gips, Ryan Aylward, Alex Pentland, Joseph A. Paradiso |
IPSN | 1 |