CAP Research Group @ NTU

Innovation &
Fundamental Research

Recent Articles


Digitalisation plays a big role in shaping tomorrow’s energy future. EMA has been working with the industry and research community to co-create innovative solutions for the smarter use of energy and greater efficiency.

As Professor Wen Yonggang points out: “Singapore is projected to see its data center energy consumption increase by 2030. Managing energy demand and supporting this energy sector are thus of paramount importance. Our solution integrates with advanced algorithms to quickly pinpoint bottlenecks in the system and targets cooling at the specific points to improve energy efficiency of the data center.“


About Research Group

Introduction

CAP is an acronym for “Cloud Application and Platform Lab at School of Computer Engineering, NTU”. It is a leading research group in the area of cloud media computing, content delivery networks, datacenter architecture, and big data analytics. 


Mission

To conduct innovative and fundamental research in applications and platforms for cloud computing 
and
To practice a learning-based framework for system prototyping and performance optimization for large-scale networked computing systems


Vision

To incubate visionary technical leaders to drive future ICT advances

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Best Paper Awards

  1. Best Paper Award, 2019 IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), May 2019. For the paper titled “Joint Content Replication and Request Routing for Social Video Distribution Over Cloud CDN: A Community Clustering Method.”
  2. Best Paper Award, 2015 IEEE Multimedia Magazine, August 2015. For the paper titled “Towards Multi-Screen Social TV with Geo-Aware Social Sense.”
  3. Best Paper Award, 2019 IEEE International Conference on Visual Communications and Image Processing (VCIP’19), December 2019. For the paper titled “Toward Intelligent Visual Sensing and Low-cost Analysis: A Collaborative Computing Approach.”
  4. Best Conference Paper Award, 2019 IEEE Multimedia Communications Technical Committee (MMTC), December 2019. For the paper titled “DeepQoE: A Unified Framework for Learning to Predict Video QoE,” published on 2018 IEEE International Conference on Multimedia Expo (ICME’18).
  5. Best Paper Award Finalist (TOP 5 papers), 2018 IEEE International Conference on Data Mining (ICDM 2018), November 2018. For the paper titled “ResumeNet: A Learning-based Framework for Automatic Resume Quality Assessment.”
  6. Distinguished Paper Award Finalist (TOP 3 papers), 2017 International Joint Conference on Artificial Intelligence (IJCAI 2017), August 2017. For the paper titled “General Heterogeneous Transfer Distance Metric Learning via Knowledge Fragments Transfer.”
  7. Best Paper Award, 2016 IEEE Global Communications Conference, Exhibition & Industry Forum (Globecom 2016), December 2016. For the paper titled “Toward Effortless TV-to-Online (T2O) Experience: A Novel Metric Learning Approach.”

Supervisor

Yonggang Wen
Professor

Professor Wen Yonggang received his Ph.D. degree from Massachusetts Institute of Technology, USA, in 2008, his MPhil degree from Chinese University of Hong Kong, in 2001; and his BEng degree from University of Science and Technology of China, China, in 1999. His current research interests include cloud computing, data center, big data analytics, mobile computing, multimedia network and green ICT.

Project Lead

Xin Zhou
Research Fellow

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