FlowGraph Research gets Honorable Mention at IEEE PacificVis

Computer Science PhD student Jun Ma, Assistant Professor Chaoli Wang, and Professor Ching-Kuang Shene received an Honorable Mention for their paper, “FlowGraph: A Compound Hierarchical Graph for Flow Field Exploration“, at the IEEE Pacific Visualization Symposium (PacificVis), Feb. 26 – Mar. 1, 2013, in Sydney, Australia. In this paper, the authors present a novel graph-based solution for visual analytics of three-dimensional large and complex flow field data sets, enabling occlusion-free observation and comparison of streamlines and their spatial relationships in a controllable fashion.

Exploring interesting flow patterns in the car flow data set. Selecting three L-nodes (one at the next level of the hierarchy) to capture the main flow structure passing through the car.

PacificVis is one of the three leading conferences in the field of visualization. This year, out of 118 submission, 34 were accepted, from which one was awarded the best paper and four received honorable mentions. Chaoli Wang attended the symposium and presented the paper. He also presented another accepted paper “iTree: Exploring Time-Varying Data using Indexable Tree” at the symposium, coauthored with his PhD student Yi Gu.


Best Paper Award

Computer Science Assistant Professor Chaoli Wang, former CS undergraduate student John Reese, former CS MS student Huan Zhang, CS PhD student Jun Tao, and Physics Professor Robert Nemiroff will receive a Best Paper Award for their paper, “iMap: A stable layout for navigating large image collections with embedded search”, at the IS&T/SPIE Conference on Visualization and Data Analysis, February 3-6, 2013, in Burlingame, California. Jun Tao will present the award paper at the conference.

With the booming of digital cameras and image archiving and photo sharing websites, browsing and searching through large online image collections is becoming increasingly popular. This award paper targets the Astronomy Picture of the Day (APOD), a popular online astronomy archive maintained by NASA and Michigan Tech, and presents a solution for image search and clustering based on the evaluation of image similarity using both visual and textual information. To lay out images, the paper introduces iMap, a treemap based representation for visualizing and navigating image search and clustering results. iMap strikes a good balance among simplicity, intuitiveness, and effectiveness by addressing key issues such as stable layout, screen utilization, and in-place interaction.

For their next steps, the authors will further develop techniques for animated transition and graph based image layout, deploy the visualization results on the display wall at the Immersive Visualization Studio (IVS) at the Center for Computer Systems Research (CCSR) for outreach, and eventually release a web based online program to benefit a wider user base.

apod querying example
apod querying

Grad Seminar MS Defense: Xiang Li

Poplar Gene Expression Data Analysis Pipeline

Thursday, December 13  4pm
Fisher 325

MS Defense:  Xiang Li
Advisor: Hairong Wei

Abstract: Analyzing large-scale gene expression data is tedious and time-consuming. To solve this problem, we develop a set of pipeline tools for rapid processing poplar gene expression data. In our pipeline tools, DEG pipeline is designed to identify biologically important genes that are differentially expressed under certain condition in multiple time points. Pathway analysis is designed to evaluate the expression of a set of genes catalyzing biological pathways. Domain pipeline evaluates the output from DEG pipeline. It is designed to figure out the enriched protein domains related to DEGs. GO pipeline also evaluates the output from DEG pipeline and attempts to figure out the enriched GO terms.

Our pipeline tools can analyze both microarray gene data and high-throughput gene data. These two types of data are obtained by two different technologies. A DNA microarray is a collection of microscopic DNA spots attached to a solid surface. High throughput sequencing, also called as the next-generation sequencing, is a new technology to measure gene expression levels by sequencing MicroRNAs (miRNAs), and obtain each miRNA’s copy numbers in cells or tissues.

We also develop an on-line tool for the pipelines to facilitate users to analyze their data. Besides the analyses mentioned above, it can also perform GO hierarchy analysis, i.e. construct GO trees by taking a list of GO terms as input.


CS Department Seminar, Harriet King, Master’s Defense

Understanding “Just Enough” Users

3 – 4 p.m. Friday, November 30, 2012

REKHI 214

Abstract: Among daily computer users who are proficient, some are flexible at accomplishing unfamiliar tasks on their own and others have difficulty. Software designers and evaluators involved with Human Computer Interaction (HCI) should account for any group of proficient daily users that are shown to stumble over unfamiliar tasks. We define “Just Enough” (JE) users as proficient daily computer users with predominantly extrinsic motivation style who know just enough to get what they want/need from the computer. We hypothesize that JE users have difficulty with unfamiliar computer tasks and skill transfer, whereas intrinsically motivated daily users accomplish unfamiliar tasks readily. Intrinsic motivation can be characterized by interest, enjoyment, and choice and extrinsic motivation is externally regulated. In our study we identified users by motivation style and then did ethnographic observations. Our results confirm that JE users do have difficulty accomplishing unfamiliar tasks on their own but had less problems with near skill transfer. In contrast, intrinsically motivated users had no trouble with either unfamiliar tasks or near skill transfer. This supports our assertion that JE users know enough and can transfer that knowledge, but become unproductive when faced with unfamiliar tasks.

Biography: Harriet King is a candidate for an MS degree in computer science. She has three previous degrees: one in art, a masters in education, and a BS in computer science from Michigan Tech. Harriet worked locally as a software engineer for a number of years before coming back for her masters. She recently started her own business, We Help You Use Tech, LLC, which provides tutoring and training to computer users, just like driver’s education for computer gadgets.



Search for Department Chair

Michigan Technological University invites applications and nominations for the position of Chair of the Department of Computer Science to begin in the 2013-2014 academic year. We seek an individual with the vision and leadership skills to elevate the department’s prominence in computer science research, further our strong tradition of educational excellence, and grow our graduate programs. Find out more at this link.


CS Department Seminar, Aly Farahat, PhD Defense

July 16, 2pm

Title: Automated Design of Self-Stabilization

Abstract

Nowadays, we witness an increasing impact of software system failures due to the
growing abundance and steady proliferation of software into our daily activities.
Self-stabilization is a property of a distributed system such that, regardless of the
legitimacy of its current behavior, the system behavior shall eventually become legitimate and shall remain so thereafter. Despite its elegance, self-stabilization is very difficult to
design and verify manually. We pursue two approaches towards the automated design of
self-stabilization. The first approach explores the global state space of distributed
protocols, through a set of heuristics, to automatically add self-stabilization to these
protocols. Towards this end, we develop software tools that implement our heuristics and
obtain existing and new self-stabilizing protocols on various network topologies. The
second approach investigates the global behavior of a distributed protocol by reasoning
about the local state space of just one of its components/processes. In particular, we
provide necessary and sufficient conditions — verifiable in the local state space of every
process — for global deadlock and livelock-freedom of protocols on ring topologies. Local
reasoning potentially circumvents state explosion and partial information in distributed
systems, thereby enabling our assertions about global deadlocks and livelocks to hold for
rings of arbitrary size.

Watch the defense:

Mediasite
Echo 360


CS Department Seminar, Christopher Brown, PhD Candidate

March 30, 2012, 3:00 PM, Room 214 – Rekhi Hall

Title: Generating Automated Usability Tests for User Centered Design

The agile approach to software development gives top priority to satisfying the customer through early and continuous delivery of valuable software. A key component of the agile approach is test driven development (TDD), which involves the continuous maintenance of an automated regression test suite. One area that appears resistant to TDD is usability testing, due to its inherently subjective nature. Without automated usability testing, many HCI intensive applications cannot be developed in a fully agile manner.
This research project will provide automated usability tests that can supplement standard usability testing. It uses generative programming techniques to create test code based on common usability heuristics. Generated code can adapt to varying styles of interface, and can ground subjective decisions in objective criteria. [Video]


CS, Center for Computer Systems Research and ECE Seminar – Brian VanVoorst, Speaker

Title: An Introduction to Point Cloud Understanding
Brian VanVoorst, MTU Alumni & Technical Director of BBN Technologies

Thursday, March 22,2012 – 135 Fisher Hall – 2:00 PM

Abstract: A point cloud is a collection of 3D points from a 3D sensor such as a LIDAR, stereo camera, or a Microsoft Kinect system. These 3D sensors are used in applications of robotics, mapping (such as the Google Street View platforms), and entertainment. At BBN there are multiple projects under way with a common theme of “point cloud understanding.” Point cloud understanding is an area of computer vision research in which algorithms are developed to extract knowledge from point clouds. In this talk an overview of 3D sensors and their point clouds, discuss challenges computer scientists face in processing point clouds, explain some of the key algorithms and data structures, highlight the differences between point cloud understanding and image understanding, and explore opportunities for sensor fusion. I will draw heavily upon the real-world challenges we face in our ongoing research projects. This talk will be accessible to computer scientists and engineers at all levels.

Biography: Brian VanVoorst joined BBN Technologies in 2008 as a Technical Director to help form the BBN Technologies office in Minnesota. He has more than 19 years of experience working on and leading research and development programs. His most recent work is in the area of the automated understanding of LIDAR point clouds. His previous work has been in many areas, including real-time and fault-tolerant systems, mobile ad-hoc networking, parallel processing, and parallel system benchmarking. He also has worked extensively with robotics and was part of a team that was a finalist for the DARPA Urban Challenge. Before coming to BBN, VanVoorst was a researcher at Honeywell Labs for 14 years and spent two years at the NASA Ames Research Center. VanVoorst earned his bachelor’s and master’s degrees in computer science from Michigan Technological University. From 1999–2001 he held a lectureship position at Michigan Tech and taught in the Computer Science Department while continuing to work for Honeywell. He holds one patent with four applications pending and has published more than 20 papers in conference proceedings and journals.


5th Annual BonzAI Brawl Programming Contest

Put your AI to the test and conquer the nine realms! On March 31, 2012 the 5th Annual BonzAI Brawl programming competition will take place in the CS department at Michigan Technological University. The programming will be an all day event, where teams of 1 to 3 contestants will implement an AI player for a game. The contestants will be given the details of the API the day of the competition and must design a winning strategy within the 8 hours allotted. After coding ends, the AIs are pitted against each other, in a tournament (known as the BRAWL). Spectators are welcome to attend and cheer for their favorite AI at the BRAWL. For more information about BonzAI Brawl or to register your team, visit http://wics.students.mtu.edu/bonzai. All teams must register by March 23, 2011.

Sponsored in part by a donation from LaSalleTech, Consistacom, Jackson, and the CS Department.