ACM-HK Student Research and Career Day

The 10th ACM-HK Student Research and Career Day

Co-organized by ACM-HK and Microsoft Research Asia

November 19th, 2013

The Hong Kong University of Science and Technology


The Research and Career Day is an annual event organized by ACM (Hong Kong Chapter). The event provides an excellent opportunity for computer science/engineering students from all universities in Hong Kong and Macau to gain exposure in conference, to present their innovative research work, and to share research ideas and experiences. Through this event, we aim at fostering an environment to promote closer interactions and collaborations among students and to promote R&D awareness in Hong Kong and Macau.

Registration Closed.


  • 2013-11-08: We are happy to announce that Microsoft Research Asia Hong Kong Day will be co-located with ACM PG day on Nov 19th.
  • 2013-11-05: We are happy to announce that Microsoft is willing to sponsor the best poster and best demo award, we name the awards as "ACMHK-Micorsoft Best Poster Award" and "ACMHK-Microsoft Best Demo Award.
  • 2013-10-20: The Posters and Demos submission deadline has been extended to 28th Oct 2013.
  • 2013-08-20: The site is online.


10:00-12:15Microsoft Research Asia Hong Kong Day Program. detailsIAS Lecture Theatre
13:30-13:35Open RemarksLTB
13:35-14:20 Keynote: From Snowden to Big Data, Prof. Lionel Ni, HKUSTLTB
14:20-15:20Research Seminars by MSRA Researchers:
15:20-16:30Coffee break, Poster/Demo/Junior Research Award Poster.
  • Sheng Cai(CUHK) - GROTESQUE: Noisy Group Testing (Quick and Efficient)
  • Chun Lam Chan(CUHK) - Stochastic Threshold Group Testing
  • JIA Ru(PolyU) - An Investigation on the Simulation of Priority and Shortest - Job-First Scheduling in Cloud Computing
  • Xiao Xiao(HKUST) - Hitting Sweet Spots in Type-Feedback JavaScript Engine
  • Kaiyong Zhao(HKBU) - G-BLASTN: accelerating nucleotide alignment by graphics processors
  • You Li(HKBU) - Accelerating the Scoring Module of Mass Spectrometry- Based Protein Identification Using GPUs
  • Xingyu Zeng(CUHK) - Multi-Stage Contextual Deep Learning for Pedestrian Detection
  • Xinxin Mei(HKBU) - Green GPU Computing by Voltage/Frequency Scaling
  • Yan Cai(CityU) - Deadlock Detection in Multithreaded Programs
  • Rui Zhao(CUHK) - Unsupervised Salience Learning for Person Re-identification
  • Rui Zhao(CUHK) - Person Re-identification by Salience Matching
  • Pak Hou Che(CUHK) - Reliable Deniable Communication: Hiding Messages in Noise
  • Man-Kwun Chiu(HKUST) - Manifold Reconstruction
  • Chao Dong(CUHK) - AdVisual: A Visual-based Advertising System
  • Qian Chen(HKBU) - VERDICT: Privacy-Preserving Authentication of Range Queries in Location-based Services
  • Farzin Haddadpour(CUHK) - On AVCs with Quadratic Constraints
  • Wei Zhang(CityU) - FashionAsk: A Multimedia based Question-Answering System
Junior Research Award:
  • XIAO, Jiang(HKUST)
  • Liang ZHENG(CityU) - Smart Spectrum Access Algorithms in Mobile TV White Space Networks for Utility Maximization
  • Li Chen(HKUST) - Towards Minimal-Delay Deadline-Driven Data Center TCP
  • Jianping Shi(CUHK) - Parsing visual data for image understanding via matrix factorization, sparse and low-rank representation
  • Chun Lam CHAN(CUHK) - Stochastic Group Testing
  • Qian Chen(HKBU) - Privacy-Preserving Query Authentication
  • Ting Yao(CityU) - Annotation for Free: Video Tagging by Mining User Search Behavior
outside area of LTJ and LTK
16:30-18:30 Best Research Presentation
Session 1:
  • Jameel, Mohammad Shoaib(CUHK): Latent Concept and Topic Models for Readability Problem in Information Retrieval
  • Cheng LONG(HKUST): Spatially-Oriented Data Analytics and Processing
  • CAI, Sheng(CUHK): Sparse Recovery – Algorithms and Applications
Session 2:
  • Jiangchuan Zheng(HKUST): Towards effective context pattern discovery from mobile data and its applications
  • Lu Wang(HKUST): Wireless Communication
  • Li Jiang(CUHK): Yield and Reliability Enhancement for 3D Ics
Room 2464
18:30-20:30Banquet and CeremonyG/F restaurant

Lionel M. Ni: From Snowden to Big Data
The top-secret surveillance data-collection and data-mining program, PRISM, has recently been made public by Edward Snowden, a former employee of the CIA and the NSA. PRISM is essentially a Big Data approach to national security. Indeed, the potential power of Big Data has gradually been recognized in many domains. However, the term Big Data has also led to much confusion and controversy. In this talk, I will first attempt to clarify the meaning and implications of Big Data by distinguishing the essential differences between Big Data and data. This part will focus on the emerging applications, which have been made possible, how our way of thinking should be changed, and why new technologies should be developed. Then, I will talk about the “Big Data Triangle”, the combination of ideas, data and technology, which extracts deep insight and great value from Big Data. I will use actual traffic data to demonstrate the value of Big Data obtained from my research team. Finally, I will discuss how our government could react to the Big Data era and what should be learned from the Snowden disclosures in order to develop the right policies.
Lionel M. Ni is Chair Professor in the Computer Science and Engineering Department at HKUST. He also serves as the Special Assistant to the President and Dean of HKUST Fok Ying Tung Graduate School. He was the Chief Scientist of the National Basic Research Program of China (973 Program) on Wireless Sensor Networks and is participating in a new 973 program on Big Data. His research papers have been highly cited, over 17,000 times according to Google Scholar. He is the owner of seven US/China patents with more than 15 patents pending. He is a fellow of IEEE and Hong Kong Academy of Engineering Sciences. He received the Overseas Outstanding Contribution Award from China Computer Federation in 2009, the First Class Award in Natural Sciences for Research Excellence by the Ministry of Education, China in 2010, and the Second Class Award in Natural Sciences for Research Excellence by the State Council, China in 2011.
Wei Chen: Computational Social Influence
Social influence is deeply weaved into the fabric of human society and affects every aspect of human life. Computational social influence is aimed at empowering social influence with computational tools such as modeling, algorithm design, and data mining. In this talk, I will provide a brief overview of our recent studies on influence diffusion dynamics and the influence maximization problem, which is the problem of selecting a small number of seed nodes in a social network such that their influence coverage after the influence diffusion process is maximized. I will conclude the talk with some discussions on future directions in computational social influence.
Wei Chen is a Senior Researcher at Microsoft Research Asia, Beijing, China. He is also an Adjunct Professor at Tsinghua University. His research interests include computational and game theoretic aspects of social networks, algorithmic game theory, distributed computing, and fault tolerance. He won the prestigious William C. Carter Award in 2000 in the area of dependable computing, for his seminal dissertation work on the quality of service of failure detectors. His co-authored paper on a novel game-theoretic approach for community detection in social networks won the best student paper award in ECML PKDD 2009. He has done a series of impactful work on social influence dynamics and social influence maximization, which appeared in recent KDD, ICDM, SDM, WSDM, ICWSM, and AAAI conferences, and are widely cited in the research community. He is a co-author of the monograph “Information and Influence Propagations in Social Networks” to be published by Morgan & Claypool Publishers. For more information, you are welcome to visit his home page at
Hong Z. Tan: Fingertip Haptics and its Application in Touch-based Consumer Products
The field of haptics, sensing and manipulation through the sense of touch, has witnessed a rapid development in the recent years, thanks to a plethora of consumer products with haptic effects. However, most people still associate haptics with the mere vibrations in mobile phones. In this talk, I will provide an overview of haptic technologies that bring touch feedback sensations to the fingertips, as opposed to shaking up the whole device. I will then showcase several ongoing projects for restoring haptic feedback on touch screens, providing a glimpse into a future of human computer interactions where we touch the screen and the screen touches us back.
Hong Z. Tan is a Senior Researcher and Research Manager with the Human Computer Interaction Group at Microsoft Research Asia, and a Professor of Electrical and Computer Engineering at Purdue University. She is known internationally as a leading expert on haptics psychophysics, taking a perception-based approach to solving engineering problems. She received her Bachelor's degree in Biomedical Engineering from Shanghai Jiao Tong University. She earned her Master and Doctorate degrees, both in Electrical Engineering and Computer Science, from Massachusetts Institute of Technology (MIT). She was a Research Scientist at the MIT Media Lab before joining the faculty at Purdue's School of Electrical and Computer Engineering in 1998. She has held a McDonnell Visiting Fellowship at Oxford University, a Visiting Associate Professorship in the Department of Computer Science at Stanford University, a Guest Researcher position in the Institute of Life Science and Technology at Shanghai Jiao Tong University, and a Visiting Researcher position at Microsoft Research Asia. She currently serves as the Editor-in-Chief of the World Haptics Conference Editorial Board.