Fan Zhang

Orcid: 0000-0001-6463-0907

Affiliations:
  • Chinese Academy of Sciences, Institute of Computing Technology, State Key Laboratory of Computer Architecture, Beijing, China


According to our database1, Fan Zhang authored at least 16 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
OpenClinicalAI: An open and dynamic model for Alzheimer's Disease diagnosis.
Expert Syst. Appl., 2025

2023
OpenClinicalAI: An Open and Dynamic Model for Alzheimer's Disease Diagnosis.
CoRR, 2023

WPC: Whole-picture Workload Characterization.
CoRR, 2023

Cross-Layer Profiling of IoTBench.
Proceedings of the Benchmarking, Measuring, and Optimizing, 2023

2022
EAIBench: An Energy Efficiency Benchmark for AI Training.
Proceedings of the Benchmarking, Measuring, and Optimizing, 2022

2021
OpenClinicalAI: enabling AI to diagnose diseases in real-world clinical settings.
CoRR, 2021

AIBench Training: Balanced Industry-Standard AI Training Benchmarking.
Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2021

2020
AIBench: An Industry Standard AI Benchmark Suite from Internet Services.
CoRR, 2020

AIBench: An Agile Domain-specific Benchmarking Methodology and an AI Benchmark Suite.
CoRR, 2020

2019
Landscape of Big Medical Data: A Pragmatic Survey on Prioritized Tasks.
IEEE Access, 2019

2018
AIoT Bench: Towards Comprehensive Benchmarking Mobile and Embedded Device Intelligence.
Proceedings of the Benchmarking, Measuring, and Optimizing, 2018

Edge AIBench: Towards Comprehensive End-to-End Edge Computing Benchmarking.
Proceedings of the Benchmarking, Measuring, and Optimizing, 2018

AIBench: Towards Scalable and Comprehensive Datacenter AI Benchmarking.
Proceedings of the Benchmarking, Measuring, and Optimizing, 2018

2017
Work-in-Progress: Maximizing Model Accuracy in Real-time and Iterative Machine Learning.
Proceedings of the 2017 IEEE Real-Time Systems Symposium, 2017

AccurateML: Information-aggregation-based approximate processing for fast and accurate machine learning on MapReduce.
Proceedings of the 2017 IEEE Conference on Computer Communications, 2017

CloudMix: Generating Diverse and Reducible Workloads for Cloud Systems.
Proceedings of the 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), 2017


  Loading...