Demo Data from SIGIR 2026 / reviewers in the wild / expert
Joseph Telaak
dblp:377/0667
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0004-1152-8860ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 since 2021
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.
| Artificial intelligence
1 paper |
3D vision · 77% Autonomous driving · 12% Robot navigation and mapping · 12% | |
| Computer networks
1 paper |
Wireless sensing and localization · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › 3D vision › 3d object detection › 3d object localization
3d bounding box estimation |
0.8 | 1 | 2024 | Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles · MobiSys 2024 |
Computer vision › 3D vision
3d object detection |
0.8 | 1 | 2024 | Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles · MobiSys 2024 |
Wireless sensing and localization
mmwave sensing |
0.8 | 1 | 2024 | Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles · MobiSys 2024 |
Wireless sensing and localization › target sensing
vehicle detection |
0.8 | 1 | 2024 | Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles · MobiSys 2024 |
Robotics › Autonomous driving
perception |
0.2 | 1 | 2024 | Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles · MobiSys 2024 |
Robotics › Robot navigation and mapping
sensor fusion |
0.2 | 1 | 2024 | Poster: AutoSense: Reliable 3D Bounding Box Prediction for Vehicles · MobiSys 2024 |
Methods — techniques the papers use, named apart from their topics
mmwave radar signal processing · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Poster: AutoSense: Reliable 3D Bounding Box Prediction for VehiclesabstractWe propose AutoSense, a millimeter-wave (mmWave) wireless signal-based system for predicting 3D bounding boxes of vehicles. While cameras and LiDAR can be adversely affected by challenging weather conditions such as heavy rain, fog, or snow, mmWave signals are less susceptible to these environmental factors, making them more resilient. As a result, AutoSense can complement other sensors for accurate 3D bounding box predictions in all weather conditions. Hem Regmi, Reza Tavasoli, Joseph Telaak, Sanjib Sur 0001, Srihari Nelakuditi |
MobiSys | 3 |