VLDB 2026 Research / reviewers in the wild / expert
Luke Jacobs
dblp:271/6872
· DBLP profile ↗
4ranked-venue papers
3as first author
4since 2021 · last 2026
0000-0002-3722-5508ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 3 · 2 first-author · 3 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 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.
| Computer networks
3 papers |
Internet of things and sensor networks · 51% Wireless sensing and localization · 35% Cellular and mobile networks · 10% |
Topics — the 9 heaviest of 9, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet of things and sensor networks
backscatter communication |
1.5 | 2 | 2024 | Integrated Two-way Radar Backscatter Communication and Sensing with Low-power IoT Tags · SIGCOMM 2024 Assessing Backscatter Link Quality Through Canopy · MobiCom 2024 |
Wireless sensing and localization
radar sensing |
1.1 | 2 | 2026 | Integrated Two-way Radar Backscatter Communication and Sensing with Low-power IoT Tags · SIGCOMM 2024 GreenScatter: Through-Canopy Soil Moisture Sensing with UAV-Mounted Radar · SenSys 2026 |
Internet of things and sensor networks
environmental sensing |
1.0 | 1 | 2026 | GreenScatter: Through-Canopy Soil Moisture Sensing with UAV-Mounted Radar · SenSys 2026 |
Internet of things and sensor networks › environmental sensing
soil moisture sensing |
1.0 | 1 | 2026 | GreenScatter: Through-Canopy Soil Moisture Sensing with UAV-Mounted Radar · SenSys 2026 |
Wireless sensing and localization
backscatter localization |
0.8 | 1 | 2024 | Integrated Two-way Radar Backscatter Communication and Sensing with Low-power IoT Tags · SIGCOMM 2024 |
Wireless sensing and localization › radar signal processing
FMCW radar |
0.8 | 1 | 2024 | Integrated Two-way Radar Backscatter Communication and Sensing with Low-power IoT Tags · SIGCOMM 2024 |
Cellular and mobile networks
integrated sensing and communication |
0.8 | 1 | 2024 | Integrated Two-way Radar Backscatter Communication and Sensing with Low-power IoT Tags · SIGCOMM 2024 |
Internet of things and sensor networks › wireless sensor network
environmental monitoring |
0.2 | 1 | 2024 | Assessing Backscatter Link Quality Through Canopy · MobiCom 2024 |
Physical-layer communications
modulation |
0.2 | 1 | 2024 | Integrated Two-way Radar Backscatter Communication and Sensing with Low-power IoT Tags · SIGCOMM 2024 |
Methods — techniques the papers use, named apart from their topics
template correlation · 0.8passive differential circuitry · 0.8chirp-slope-shift-keying · 0.8SNR · 0.8FMCW radar · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | GreenScatter: Through-Canopy Soil Moisture Sensing with UAV-Mounted Radar
Luke Jacobs, Ishfaq Aziz, Benhao Lu, Alireza Tabatabaeenejad, Mohamad Alipour, Elahe Soltanaghai |
SenSys | 1 |
| 2024 | Joint Soil and Above-Ground Biomass Characterization Using RadarsabstractSoil moisture sensing through biomass or vegetation canopy has challenged researchers, even those who use SAR sensors with penetration capabilities. This is mainly due to the imposed extra time and phase offsets on Radio Frequency (RF) signals as they travel through the canopy. These offsets depend on the vegetation canopy moisture and height, both of which are typically unknown in agricultural and forest fields. In this paper, we leverage the mobility of an unmanned aerial system (UAS) to collect spatially-diverse radar measurements, enabling the joint estimation of soil moisture, above-ground biomass moisture, and biomass height, all without assuming any calibration steps. We leverage the changes in time-of-flight (ToF) and angle-of-arrival (AoA) measurements of reflected radar signals as the UAS flies above a reflector buried under the soil. We demonstrate the effectiveness of our algorithm by simulating its performance under realistic measurement noises as well as conducting lab experiments with different types of above-ground biomass. Our simulation results conclude that our algorithm is capable of estimating volumetric soil moisture to less than 1% median absolute error (MAE), vegetation height to 11.1cm MAE, and vegetation relative permittivity to 0.32 MAE. Our experimental results demonstrate the effectiveness of the proposed method in practical scenarios for varying biomass moistures and heights. Luke Jacobs, Mohamad Alipour, Adam Watts, Elahe Soltanaghai |
IGARSS | 1 |
| 2024 | Assessing Backscatter Link Quality Through CanopyabstractBackscatter communication is well-suited for agriculture, forest sensing, and environmental monitoring due to its low power and maintenance requirements. It can support a range of applications, including reading sensor values such as soil moisture or nutrient levels, monitoring plant health, tracking animal movements, or detecting forest fires. In these settings, sensors and backscatter nodes are often placed deep in the forest or under the plant canopy, while the reader is positioned on a mobile node such as a drone flying above the canopy. Consequently, signal attenuation caused by canopy blockage remains a significant challenge. This paper explores the feasibility of using backscatter communication in such environments and argues that signal-to-noise ratio (SNR) is not the most reliable metric for evaluating link quality. Instead, we propose a new metric, called template correlation, which provides a more accurate assessment in low-SNR conditions. Our findings demonstrate that backscatter communication, with its low power consumption and minimalist hardware design at the tags, is effective for environmental monitoring, even in the presence of canopy attenuators like grasses or crops. Luke Jacobs, Avery Plote, Elahe Soltanaghai |
MobiCom | 1 |
| 2024 | Integrated Two-way Radar Backscatter Communication and Sensing with Low-power IoT TagsabstractIntegrated Sensing and Communication (ISAC) represents an innovative paradigm for enhancing spectrum and hardware utilization for both sensing and communication. A specific type of ISAC, radar backscatter communication, involves low-power nodes embedding data onto radar signal reflections rather than generating new signals. However, existing radar backscatter techniques only facilitate uplink communication from the tag to the radar, neglecting downlink communication. This paper introduces BiScatter, an integrated radar backscatter communication and sensing system that enables simultaneous uplink and downlink backscatter communication, radar sensing, and backscatter localization. This is achieved through the design of chirp-slope-shift-keying modulation on top of Frequency Modulated Continuous Wave (FMCW) radars, complemented by passive differential circuitry at the backscatter tags for low-power decoding. BiScatter also presents a packet structure compatible with off-the-shelf radars that offer accurate data processing and synchronization between radar and tag. We prototype this backscatter network in both 9GHz and 24GHz, demonstrating its capability to extend across different frequency bands. Our evaluations demonstrate that BiScatter supports two-way backscatter communication with BER lower than 10-3 up to 7m range and centimeter-level tag localization accuracy on top of off-the-shelf FMCW radars. The presented approach significantly augments the versatility and efficiency of ISAC for low-power devices. Ryu Okubo, Luke Jacobs, Jinhua Wang 0007, Steven M. Bowers, Elahe Soltanaghai |
SIGCOMM | 2 |