TA for Assembly Language unit (Tianjin University)
Assisted in the programming experiments.
Yalong Yang is a PhD Candidate at Caulfield School of Information Technology, Monash University, VIC, Australia. He is working at IALab: Immersive Analytics Lab under the supervision of A/Prof. Tim Dwyer, Prof. Kim Marriott, A/Prof Bernhard Jenny and Dr Caron (Haohui) Chen. He was previsouly supervised by Dr. Sarah Goodwin.
His research topic is Visualising Spatial Flow Data. More details available at:
Yalong's Visualisation Gallery
He was supervised by Prof. Kang Zhang, from University of Texas at Dallas and Dr. Quang Vinh Nguyen, from MARCS, University of Western Sydney in a visualization project during his master study.
Abstract: This paper explores different ways to render world-wide geographic maps in virtual reality (VR). We compare: (a) a 3D exocentric globe, where the user’s viewpoint is outside the globe; (b) a flat map (rendered to a plane in VR); (c) an egocentric 3D globe, with the viewpoint inside the globe; and (d) a curved map, created by projecting the map onto a section of a sphere which curves around the user. In all four visualisations the geographic centre can be smoothly adjusted with a standard handheld VR controller and the user, through a head-tracked headset, can physically move around the visualisation. For distance comparison exocentric globe is more accurate than egocentric globe and flat map. For area comparison more time is required with exocentric and egocentric globes than with flat and curved maps. For direction estimation, the exocentric globe is more accurate and faster than the other visual presentations. Our study participants had a weak preference for the exocentric globe. Generally the curved map had benefits over the flat map. In almost all cases the egocentric globe was found to be the least effective visualisation. Overall, our results provide support for the use of exocentric globes for geographic visualisation in mixed-reality.
Abstract: Showing flows of people and resources between multiple geographic locations is a challenging visualisation problem. We conducted two quantitative user studies to evaluate different visual representations for such dense many-to-many flows. In our first study we compared a bundled node-link flow map representation and OD Maps with a new visualisation we call MapTrix. Like OD Maps, MapTrix overcomes the clutter associated with a traditional flow map while providing geographic embedding that is missing in standard OD matrix representations. We found that OD Maps and MapTrix had similar performance while bundled node-link flow map representations did not scale at all well. Our second study compared participant performance with OD Maps and MapTrix on larger data sets. Again performance was remarkably similar.
Abstract: The movement of tongue plays an important role in pronunciation. Visualizing the movement of tongue can improve speech intelligibility and also helps learning a second language. However, hardly any research has been investigated for this topic. In this paper, a framework to synthesize continuous ultrasound tongue movement video from speech is presented. Two different mapping methods are introduced as the most important parts of the framework. The objective evaluation and subjective opinions show that the Gaussian Mixture Model (GMM) based method has a better result for synthesizing static image and Vector Quantization (VQ) based method produces more stable continuous video. Meanwhile, the participants of evaluation state that the results of both methods are visual-understandable.
Abstract: Treemaps are well-known for visualizing hierarchical data. Most related approaches have been focused on layout algorithms and paid little attention to other display properties and interactions. Furthermore, the structural information in conventional Treemaps is too implicit for viewers to perceive. This paper presents Cabinet Tree, an approach that: i) draws branches explicitly to show relational structures, ii) adapts a space-optimized layout for leaves and maximizes the space utilization, iii) uses coloring and labeling strategies to clearly reveal patterns and contrast different attributes intuitively. We also apply the continuous node selection and detail window techniques to support user interaction with different levels of the hierarchies. Our quantitative evaluations demonstrate that Cabinet Tree achieves good scalability for increased resolutions and big datasets.
Abstract: Enclosure partitioning approaches, such as Treemaps, have proved their effectiveness in visualizing large hierarchical structures within a compact and limited display area. Most of the Treemaps techniques do not use node-links to show the structural relations. This paper presents a new tree visualization approach known as Drawer-Tree that can be used to present the structure, organization and interrelation of big data. By utilizing the display space with traditional node-link visualization, we have developed a novel method for visualizing tree structures with high scalability. The name "drawer" is a metaphor that helps people understand the visualization.
From Mar 2015
Caulfield School of Information Technology, Monash University, VIC, Australia.
Sep 2012 ~ Jan 2015
School of Computer Software, Tianjin University, Tianjin, China.
Sep 2008 ~ Jun 2012
School of Computer Software, Tianjin University, Tianjin, China.
June 2016 ~ July 2016
Details and an interative demo are available at: Yalong's Visualisation Gallery.
Sep 2012 ~ Jan 2015; in Tianjin Key Lab of Cognitive Computing and Application; supervised by Prof. Jianrong Wang (web page in Chinese) and Prof. Jianguo Wei (project details available in our publications)
Part of the National Natural Science Foundation of China (No.61304250 and No.61175016)
We used a ultrasound transducer to get real time images of the vocal tract (mainly the tongue), and to recognize (or synthesize) the sound of the speech with the images.
We aim to improve aids for the speech-handicapped, communication privacy and speech recognition rate in noisy environment.
Related techniques: Speech recognition; Machine Learning; Image Processing; HMM ( Hidden Markov Model); GMM (Gaussian Mixture Model); K-means.
Apr 2013 ~ Nov 2013; cooperated with the Samsung and the Olympus Company; Patent pending
We used image processing technology to measure the size of chips automatically.
The result is in an accuracy of 5um.
Related techniques: Image Processing; Machine Vision; OpenCV; Windows Form programming; C# programming; Software privacy protection and software deployment.
Sep 2010 ~ Jun 2012; supervised by Prof. Jianrong Wang (web page in Chinese)
Team members: Yaolong Haung; Chao Ma; Haobo Ma; Yang Yu; Jun Song and Chang Gao.
The 3rd Prize for China Robot Contest (RoboCup China Open) in 2011.
Team Description Paper (TDP) for 2011; 2012
Related techniques: Robotics; Biped Walking; Prologo; linux; C++ and python.
2010 ~ 2012
Team members: Haobo Ma; Yang Yu.
By using a micro computer as a router which receives commands from mobile devices and sends them to the home appliances.
Invited to the National Students' Innovation Council, 2012
Won the 1st prize of Students' Innovation Contest in SCS(School of Computer Software), Tianjin University
Reported by the medias (web page in Chinese)
Related techniques: Mobile platform development; functional protocol design and presentation and hardware development.
2010 ~ 2012
Team members: Haobo Ma; Yang Yu.
By using the accelerate sensor on mobile phone to simulate the joystick.
By using the bluetooth to communicate with the normal PC
Won The 2nd Prize of National Undergraduate Electronic Design Contest 2010 Embedded System Design Invitational Contest (Intel Cup).
Related techniques: Mobile platform development; windows driver development (by Haobo Ma).
Assisted in the programming experiments.
Assisted in designing experiment exercises and helped students with the IBM JAZZ Software Develop Management by writing tutorials.
Assisted in the programming experiments.
Jan 2018
Apr 2017
Dec 2016
Aug 2016
Oct 2014
May 2014
Apr 2013
Dec 2011
74 scholarships in whole China this year, including undergraduates, post-graduates
Aug 2011
RoboCup is an international robotics competition founded in 1997. The aim is to promote robotics and AI research, by offering a publicly appealing, but formidable challenge. Our team take part in the Simulation 3D competition this year, and I am the team leader.
Apr 2011
Dec 2010
Dec 2010
Mar 2009 -- July 2013
Chairman from Jul 2012 to Sep 2013
Assisted in Organizing the 14th Computing in the 21st Century Conference hosted by Microsoft in Tianjin, Oct 2012
Attended the Summer Camp of Microsoft Research Asia, Aug 2012
Organized 3 programming contests in Tianjin University
From Mar 2015
Volunteering orientation for new students (July 2015)