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Gustavo Batista

Has grant

Associate professor

University of New South Wales

Australia

Research Interests

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Recent Grants

Grant: Close

Monitoring real-time insect pests in agriculture and environment

Open Date: 2014-11-21

Close Date: 2017-11-30

Grant: Close

Research on geo-spatial marine biology data mining using time series, text mining and visualization

Open Date: 2013-11-01

Close Date: 2015-10-31

Grant: Close

Intelligent sensor for controlling agricultural pests and disease-vector insects

Open Date: 2013-06-01

Close Date: 2015-05-31

Grant: Close

Complexity-invariance for classification, clustering and motif discovery in time series

Open Date: 2012-07-01

Close Date: 2014-06-30

Grant: Close

Machine learning with sets of unbalanced data

Open Date: 2007-06-01

Close Date: 2009-05-31

Articles (20)

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2027

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AUSTRALIA

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Juliano Corbi

Professor Assistente

University of Sao Paulo

BRAZIL

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Gustavo Batista

Research Interests

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Recent Grants

Articles (20)

Self-supervised Learning for Time Series Classification via Redundancy Reduction and Wavelet-Based Data Augmentation

Real-Time and Trustworthy Classification of IoT Traffic Using Lightweight Deep Learning

ContinualCropBank: Object-Level Replay for Semi-supervised Online Continual Object Detection

From fair graphs to fair data: a DAG-based approach to mitigating bias in AI systems

Mosaic: An Accurate and Efficient Kernel-Based Multivariate Time Series Classifier

Poster Abstract: Privacy-Generalisation Trade-Offs in Federated Learning for Cross-Room Wi-Fi Sensing

Using Temporal Features to Improve Accuracy in Multivariate Pattern Analysis (MVPA) of M/EEG Data

Pedestrian trajectory prediction using goal-driven and dynamics-based deep learning framework

Towards Behavior Grammar-Driven IoT Network Traffic Generation using MUD Specifications

Nosy Layers, Noisy Fixes: Tackling DRAs in Federated Learning Systems using Explainable AI

Towards Label Shift Adaptation for Robust IoT Device Identification

AA-mDLAM: An accelerated ADMM-based framework for training deep neural networks

Charting a Fair Path: FaGGM Fairness-Aware Generative Graphical Models

FastFlow: Early Yet Robust Network Flow Classification using the Minimal Number of Time-Series Packets

Label Shift Estimation With Incremental Prior Update

Match: A Maximum-Likelihood Approach for Classification under Label Shift

MetaQuant: A framework for metaheuristic based quantification

Predicting IoT Device Vulnerability Fix Times with Survival and Failure Time Models

Revisit Time Series Classification Benchmark: The Impact of Temporal Information for Classification

Can microplastic contamination affect the wing morphology and wingbeat frequency of Aedes aegypti (Diptera: Culicidae) mosquitoes?

Collaborators (8)

Aditya Joshi

Rohitash Chandra

Hassan Habibi Gharakheili

Sushmita Ruj

Salil Kanhere

Sanjay Jha

Natasha Fernandes

Juliano Corbi

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