Jo Ueyama

Jo Ueyama

Universidade de São Paulo

H-index: 28

Latin America-Brazil

About Jo Ueyama

Jo Ueyama, With an exceptional h-index of 28 and a recent h-index of 22 (since 2020), a distinguished researcher at Universidade de São Paulo, specializes in the field of Internet of Things (IoT), Ad Hoc Networks, Mobile Health, Environmental Informatics.

His recent articles reflect a diverse array of research interests and contributions to the field:

A deep learning workflow enhanced with optical flow fields for flood risk estimation

Water level identification with laser sensors, inertial units, and machine learning

Performance analysis of a Vehicular Ad Hoc network Using LoRa technology and IoT devices in Amazon Rivers

MADCS: A Middleware for Anomaly Detection and Content Sharing for Blockchain-Based Systems

Privacy-enhancing technologies in federated learning for the internet of healthcare things: a survey

FLORAS: urban flash-flood prediction using a multivariate model

On-line Estimators for Ad-hoc Task Execution: Learning Types and Parameters of Teammates for Effective Teamwork

Maximizing portfolio profitability during a cryptocurrency downtrend: A Bitcoin Blockchain transaction-based approach

Jo Ueyama Information

University

Position

Professor of Computer Science @ (USP)

Citations(all)

3981

Citations(since 2020)

2313

Cited By

2504

hIndex(all)

28

hIndex(since 2020)

22

i10Index(all)

76

i10Index(since 2020)

47

Email

University Profile Page

Google Scholar

Jo Ueyama Skills & Research Interests

Internet of Things (IoT)

Ad Hoc Networks

Mobile Health

Environmental Informatics

Top articles of Jo Ueyama

A deep learning workflow enhanced with optical flow fields for flood risk estimation

Applied Intelligence

2024/4/22

Water level identification with laser sensors, inertial units, and machine learning

Engineering Applications of Artificial Intelligence

2024/1/1

Performance analysis of a Vehicular Ad Hoc network Using LoRa technology and IoT devices in Amazon Rivers

Ad Hoc Networks

2024/1/1

MADCS: A Middleware for Anomaly Detection and Content Sharing for Blockchain-Based Systems

Journal of Network and Systems Management

2023/7

Privacy-enhancing technologies in federated learning for the internet of healthcare things: a survey

2023/6/16

FLORAS: urban flash-flood prediction using a multivariate model

Applied Intelligence

2023/6

On-line Estimators for Ad-hoc Task Execution: Learning Types and Parameters of Teammates for Effective Teamwork

2023/5/30

Maximizing portfolio profitability during a cryptocurrency downtrend: A Bitcoin Blockchain transaction-based approach

Procedia Computer Science

2023/1/1

An Evaluation of Iron Ore Characteristics Through Machine Learning and 2D LiDAR Technology

IEEE Transactions on Instrumentation and Measurement

2023/12/13

Machine Learning for Enhanced Credit Risk Assessment: An Empirical Approach

Journal of Risk and Financial Management

2023/11/27

Jo Ueyama
Jo Ueyama

H-Index: 19

A module-based framework to emotion recognition by speech: a case study in clinical simulation

Journal of Ambient Intelligence and Humanized Computing

2023/11

Evaluating Conveyor Belt Health With Signal Processing Applied to Inertial Sensing

2023/10/25

Artificial neural networks applied to time series for flood prediction

2023/9/25

Enhancing Water Level Identification with a Barcode-Patterned Panel and Machine Learning

2023/9/25

Federated system for transport mode detection

Energies

2022/12/6

Blockchain-aided and privacy-preserving data governance in multi-stakeholder applications

IEEE Transactions on Network and Service Management

2022/11/28

A river flooding detection system based on deep learning and computer vision

Multimedia Tools and Applications

2022/5

A blockchain-based protocol for tracking user access to shared medical imaging

Future Generation Computer Systems

2022/4/21

Exploiting smart contracts in PBFT-based blockchains: A case study in medical prescription system

Computer Networks

2022/7/5

A Blockchain-based Data Governance with Privacy and Provenance: a case study for e-Prescription

2022/5/2

See List of Professors in Jo Ueyama University(Universidade de São Paulo)