VLDB 2026 Research / reviewers in the wild / expert
Amruta Pai
dblp:254/5394
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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.
| Human-computer interaction and pervasive computing
1 paper |
Health and well-being technologies · 81% Wearable and physiological sensing · 19% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Health and well-being technologies
mobile health |
0.4 | 1 | 2019 | HealthSense: Software-defined Mobile-based Clinical Trials · MobiCom 2019 |
Health and well-being technologies › mobile health
mobile health sensing |
0.1 | 1 | 2019 | HealthSense: Software-defined Mobile-based Clinical Trials · MobiCom 2019 |
Wearable and physiological sensing
wearable sensing |
0.1 | 1 | 2019 | HealthSense: Software-defined Mobile-based Clinical Trials · MobiCom 2019 |
Methods — techniques the papers use, named apart from their topics
study state manager · 0.4cloud processing pipelines · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | HealthSense: Software-defined Mobile-based Clinical TrialsabstractWith the rise of ever-more sophisticated wearables and sensing technologies, mobile health continues to be an active area of research. However, from a clinical researcher point of view, testing novel use of the mobile health innovations remains a major hurdle, as composing a clinical trial using a combination of technologies still remains in the realm of computer scientists. We take a software-inspired viewpoint of clinical trial designs to design, develop and validate HealthSense to enable expressibility of complex ideas, composability with diverse devices and services while maximally maintaining simplicity for a clinical research user. A key innovation in HealthSense is the concept of a study state manager (SSM) that modifies parameters of the study over time as data accumulates and can trigger external events that affect the participant; this design allows us to implement nearly arbitrary clinical trial designs. The SSM can funnel data streams to custom or third-party cloud processing pipelines and the result can be used to give interventions and modify parameters of the study. HealthSense supports both Android and iOS platforms and is secure, scalable and fully operational. We outline three trials (two with clinical populations) to highlight simplicity, composability, and expressibility of HealthSense. Aidan Curtis, Amruta Pai, Nidal Moukaddam, Ashutosh Sabharwal |
MobiCom | 2 |