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Hiroaki Nishi

Professor

Keio University

Japan

Research Interests

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Professors in Japan

About

Hiroaki Nishi is a Professor at Keio University in Japan (country code: 81). His research focuses on trajectory anonymization, edge computing, and deep reinforcement learning, as evidenced by his recent articles. He explores innovative solutions in areas such as content-based anonymization, IoT device synchronization, and residential electric load forecasting.

Articles (20)

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Collaborators (3)

Hao Ran Chi

Instituto de Telecomunicações

PORTUGAL

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Tomasz Kryjak

assistant professor

AGH University of Science and Technology

POLAND

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Rui L. Aguiar

Universidade de Aveiro

PORTUGAL

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Hiroaki Nishi

Research Interests

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Articles (20)

Collaborative Industrial Internet of Things: Transitioning Toward Industry 5.0

Hardware-Accelerated Graph Neural Networks: An Alternative Approach for Event-Based Audio Classification and Keyword Spotting on SoC FPGA

Sigma-Branch: Hierarchical Single-Path Network Reconstruction for Dynamic Inference With Reduced Active Parameters

Hardware-Accelerated Event-Graph Neural Networks for Low-Latency Time-Series Classification on SoC FPGA

Optimization of Personalized Dataflow Management System in the Mobile Network and MEC Environment

Accelerator for Trajectory Anonymization Using Map Matching

Access Control Management System for Edge Computing Environment Using Tag-Based Matching and Cache Injection

FPGA Live Migration of Content-Based Anonymization Mechanism with Network Consistency

Hardware Implementation of MQTT Broker and Precise Time Synchronization Using IoT Devices

Hierarchical Multiobjective Distributed Deep Learning for Residential Short-Term Electric Load Forecasting

Hardware Implementation of MQTT Broker and Precise Time Synchronization Using IoT Devices

Digital Watermarking for Anonymized Data With Low Information Loss

Sustainable Energy Consumption

Sustainable Energy Consumption

Thermal Energy Storage Performance of Tetrabutylammonium Acrylate Hydrate as Phase Change Materials

Adaptive control method of HVAC for uniformizing comfort at Japanese residential living rooms using deep reinforcement learning

Consistency Guaranteed Multi Container Migration for Smart Community Network Services

Purchasing behavior prediction model for real stores considering product cluster and time-series patterns

IoT-based monitoring for smart community

RPC: An Approach for Reducing Compulsory Misses in Packet Processing Cache

Collaborators (3)

Hao Ran Chi

Tomasz Kryjak

Rui L. Aguiar

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