UMass Lowell Computer Science doctoral candidates Yinjie Chen and Zhongli Liu won the best paper award at the 8th International Conference on Wireless Algorithms, Systems, and Applications (WASA 2013). 

Chen and Liu are the first author and second author respectively. They are advised by Prof. Xinwen Fu, associate professor of Computer Science at UMass Lowell.

WASA is an international conference on algorithms, systems, and applications of wireless networks. It is a forum for theoreticians, system and application designers, protocol developers and practitioners. 

Topics of interest include effective and efficient state-of-the-art algorithm design and analysis, reliable and secure system development and implementation, experimental study and testbed validation, and new application exploration in wireless networks.

In their paper, Chen and Liu used a single device moving along a route for accurate and efficient localization without the help of any positioning infrastructure or trained signal strength map. They developed a Received Signal Strength (RSS) sampling process, and derived a mathematical model to determine the RSS sampling rate given the target’s distance and its packet transmission rate.

They designed and implemented BotLoc, which is a programmable and self-coordinated robot armed with a wireless sniffer for forensic localization. A video of BotLoc is at http://youtu.be/FsWLrH8Nj50.

The research is sponsored by NSF. Fu’s group develops fundamental empirical and theoretical frameworks for forensic wireless localization via moving sniffers. 

As a separate note, Prof. Xinwen Fu is also winner of Best Paper Award at Communication and Information Systems Security Symposium, IEEE ICC 2013, a flagship conference on communications of IEEE. 

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(L-R): Prof. Xinwen Fu, Yinjie Chen and Zhongli Liu.
On May 3, 2013, 38 students from this semester’s interdisciplinary Sound Thinking course demonstrated their final projects. The course was led by Prof. Jesse Heines (Computer Science) and Prof. Alex Ruthmann (Music).  

Heines noted that this year's class was the largest to date, and that “we’re now at the limit that our classroom can accommodate.”

This year, Ruthmann introduced MaKey MaKey boards to the course, allowing students to create instruments out of Play-Doh, bananas, and other whimsical substances. A MaKey MaKey board was used in the guitar shirt (see photo below).

Other teams really pushed their creativity by mixing electronic and instrumental music.

Students also used the Ichi Board for bridging between the physical and computational worlds. One student team created a piece for trumpet, Ichi Board, and drum machine; another created an guitar+Ichi Board duet.

The faculty team behind the Sound Thinking course also includes Prof. Gena Greher (Music). As part of an NSF-funded dissemination, the team will be conducting their third 2-day workshop for university faculty later this month at the UMass Lowell Inn and Conference Center.

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Guitar Shirt created by students Adam Hostetler and Alyssa Hamann

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Trumpet, Ichi Board, and Drum Machine piece performed by students Jake Galloway, Kelly Macancela, and Jeremy Fauvel

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Guitar and Ichi Board duet performed by students Scott Boiko and Eric Getchell
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UMass Lowell Computer Science professor Holly Yanco was one of twenty Massachusetts leaders honored as “Women to Watch” for 2013 at an event held at the Boston Westin Waterfront on May 9, 2013.

The award was given by the Mass High Tech Council and the Boston Business Journal in their 10th ceremony. As part of the event, $3,200 was raised for the Science Club for Girls.

In her remarks accepting the award, Yanco urged Massachusetts to adopt K–12 standards for computer science education, and make sure that all children in the state have the opportunity to learn computer science.

See more information about the event at the Boston Business Journal.


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Prof. Holly Yanco addresses the crowd of more than 300 while accepting the Mass High Tech award.


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UMass Lowell turned out a big group to support Holly in receiving the award!  From L-R: Fred Martin, Teresa Hamelin, Renae Lias Claffey, Holly Yanco, Julie Chen, Nancy Saucier, and Adam Norton.

January 2013 CS Newsletter published

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Please retrieve your copy of the UML Computer Science Department Newletter, published January 2013!

A PDF link is here, or click on the image below.

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In October 2012, Computer Science Ph.D student Yinjie Chen, his adviser Prof. Xinwen Fu (Associate Chair & Associate Professor, Computer Science), and Nancy Saucier (Associate Director, New Venture Development) successfully completed the NSF Innovation Corps program (I-Corps) at University of Michigan, Ann Arbor. 

NSF I-Corps is newly formed program to “prepare scientists and engineers to extend their focus beyond the laboratory and broadens the impact of select, NSF-funded, basic-research projects.”

The UMass Lowell team was one of 24 teams accepted into the UMich Ann Arbor cohort, the third cohort of this program. NSF program managers selected 147 teams for phone interviews, and chose 24 teams for this cohort. 

Prof. Fu's team is the first into the NSF I-Corps program from UMass Lowell. 

At the Ann Arbor workshop, experienced entrepreneurs introduced participants to the business canvas model. Running a startup is different from running mature business, and start-ups must address nine specific aspects of doing business: 

  1. Customer segments: which customers to pursue;
  2. Value proposition: what a startup can provide to the customers—what is customers’ burning pain and the startup’s edge to cure it;
  3. Customer relationships: how to let customers know the products;
  4. Channels: how to distribute products to customers;
  5. Key resources: what we need to make the products;
  6. Key activities: how to make the product;
  7. Key partners to work with;
  8. Cost structure: projecting monthly expenditures against expected revenue;
  9. Revenue streams: ways to make money. 
After the workshop, teams participated in weekly online meetings to share their progress.

Prof. Fu explained, “Our company will hold the intellectual property of using a single wireless detector to locate a target mobile phone. We confirmed that potential customers include law enforcement who can use their localization tools to locate criminals abusing WiFi networks, outdoor enthusiasts who can locate each other while outdoors, and military personnel who can detect IEDs (improvised explosive devices) by sensing the cellular signals used to detonate IEDs.  

“We went through the rewarding journey of this program, and we're now positioned to found a startup company!”

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(L-R) Nancy Saucier, Yinjie Chen and Xinwen Fu at final presentation of University of Michigan Ann Arbor NSF I-Corp cohort 3 workshop.

From the Chair, Prof. Jie (Jed) Wang:

“I am delighted to welcome three new faculty members to join the department. They are Dr. Anne Mulhern (Lecturer), Dr. Anna Rumshisky (Assistant Professor), and Dr. Kate Saenko (Assistant Professor).
Dr. Mulhern will be primarily teaching lower-level undergraduate core courses.
Dr. Rumshisky is an expert in natural language processing and Dr. Saenko is an expert in computer vision. These two areas have many important applications and funding opportunities from federal funding agencies and industries.
All three bring much needed new talents to the department that will benefit our students and help increase our visibility.”
Here is a brief introduction to our new faculty:

Dr. Mulhern received her doctorate from the University of Wisconsin-Madison in 2010. Her principal interests are logic and languages. She finds the Curry-Howard isomorphism, which describes a fundamental relationship between logics and programming language type-systems a fascinating subject.

She has been teaching various computer science topics since her first semester at the University of Wisconsin when she was one of a large squad of Teaching Assistants for the introductory programming class which had an enrollment of more than a thousand students. Pleasantly surprised to find herself both good at and interested in teaching she has continued to teach at regular intervals ever since.

Dr. Anna Rumshisky's primary area of research is natural language processing, with applications in clinical informatics, computational lexical semantics, and text processing for digital humanities and social science.

Her work focuses on the development of data-informed unsupervised learning methods as well as on leveraging existing resources and information-harvesting techniques.

Dr. Rumshisky received her Ph.D. in Computer Science from Brandeis University in 2009. She received postdoctoral training at MIT CSAIL. She has received undergraduate training at Moscow State University.

Dr. Kate Saenko received a BSc in Computer Science from the University of British Columbia, Canada in 2000 and a PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in 2009.

Between 2009 and 2012 she was a postdoctoral researcher appointed jointly at UC Berkeley and Harvard.

Kate's interests are in developing machine learning methods for computer vision applications, including object recognition, transfer learning and adaptation, color models and joint semantics of images and language. 

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(L-R) Profs. Mulhern, Rumshisky, and Saenko.

Five students from the Institute for Visualization and Perception Research (IVPR) at UMass Lowell were accepted into the Google Summer of Code program this summer.

Google Summer of Code (GSoC) is an international program that awards stipends to software developers to write code for open-source software projects. GSoC pairs students with mentors who are experienced in real-world software development. At the end of the summer, source code created during the program is released as open-source.

Each student worked to improve Weave, the free open-source data visualization and analysis platform that was developed by the IVPR and released in 2011:

  • Sanjay Anbalagan (doctoral student): Extending the Open-source Weave Analysis and Visualization Platform for the Biological Community. Sanjay designed a process that accesses multiple publicly available gene expression data sets, imports that data into Weave and uses Weave analysis features to examine, visualize and compare gene expression profiles.
  • Andrew Dufilie (doctoral student): Asynchronous Rendering to Support Large Data Sets in Weave. Andy improved Weave performance by developing a threading system for its single-threaded ActionScript code base. This means the interface remains highly responsive even when visualizing large data sets of 300,000 records or more.
  • John Fallon (senior): Collaboration in Visualization. John created, implemented and tested the first version of collaboration in the Weave environment, allowing multiple users to work together, simultaneously and remotely, when creating visualizations and performing data analysis in Weave.
  • Heather Granz (doctoral student): An Accessibility Module for Visualizations Using Weave, an Open- source Visualization Platform. Heather developed and tested a Weave-to-JAWS interface that provides descriptions of Weave visualizations in text format. This work is a first step in a larger, more ambitious project that will eventually allow Weave to generate natural language text descriptions of interactive visualizations that are compatible with the JAWS screen-reading system.
  • Sebastin Kolman (doctoral student): InfoMaps: A Tool for Personal Information Management and Analysis. Sebastin implemented InfoMaps, a visualization tool for personal information management, in the Weave environment and extended its support for document visualization and analysis including local file systems.
All five students felt they had benefited from the Google program.

According to senior John Fallon, “It was a positive experience -- getting to contribute to an open-source project, working with experienced programmers and having a professor as a mentor the whole way through”.

Doctoral student, Andy Dufilie, the Weave project engineer, noted, “The major architectural changes I made produced unexpected consequences, requiring much more work than originally planned. The takeaway is to always expect the unexpected when estimating development time.”

The Institute for Visualization and Perception Research at UMass Lowell is led by Prof. Georges Grinstein.

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(L-R) 2012 Google Summer of Code alumni Sanjay Anbalagan, Sebastin Kolman, Andy Dufilie, Heather Granz and John Fallon. Their work expanded and improved Weave, the open-source data visualization and analysis platform.
On September 6, 2012, Harshavardhan (Harsh) Achrekar, a computer science graduate student, under the guidance of Dr. Benyuan Liu, successfully defended his Ph.D. thesis titled “Online Social Network Flu Tracker – a Novel Sensory Approach to Predict Flu Trends.” He is currently employed with the Community Analytics division of eClinicalWorks®, a market leader in ambulatory clinical systems.

Achrekar’s PhD research involved online social network (OSN) analysis, with a focus on predicting flu trends and information extraction from messages posted on OSN's. He was utilizing information posted on online social networks such as Twitter and Facebook to help improve the prediction of influenza levels within US population and was tracking of its spread.

He spend three years developing and perfecting an in-house framework called the Social Network-Enabled Flu Trends (SNEFT). The software that uses continuous data-collection mechanism to monitor flu-related messages, extract relevant user demographic and location information, classify messages in real time, and predict the current influenza levels.

Starting 2009, Achrekar tapped into Twitter and Facebook and extracted tens of millions of influenza-related user posts till date, to provide an almost-instantaneous snapshot of current epidemic conditions and building comprehensive mathematical models that improves the estimate of nationwide flu activity.

Achrekar's approach can significantly enhance public health preparedness against influenza and other large-scale pandemics.

For this research, Achrekar was supported with a $200,000 grant from the National Institutes of Health under a Small Business Innovation Research Award.

His results have been presented in various scientific publications:

  • His paper “Twitter improves Seasonal Influenza Prediction" at the fifth annual International Conference on Health Informatics, Portugal, February 2012, received the Best Student Paper Award. This is a prestigious and competitive conference with a 9% full-paper acceptance ratio.
  • His paper titled “Predicting Flu Trends using Twitter Data” at the International Workshop on Cyber-Physical Networking Systems (CPNS) 2011, in conjunction with IEEE INFOCOM 2011, held in Shanghai, China, April 10–15, 2011, is considered to be a foundational research for flu tracking with OSN data and has received many citations.
  • The paper titled “A Spatio-Temporal Approach to the Discovery of Online Social Trends” at the fifth Annual International Conference on Combinatorial Optimization and Applications (COCOA), Zhangjiajie, China in August 2011 provides insights into using online social network data to discover trends in other domains. 
  • Also “Vision: Towards Real Time Epidemic Vigilance through Online Social Networks” was his first ACM Workshop paper at Mobile Cloud Computing & Services: Social Networks and Beyond (MCS), in conjunction with ACM MobiSys, San Francisco, California, June 2010, that explains the SNEFT architecture for flu tracking and pandemic outburst detection using online social network data.

Dr. Achrekar’s committee included Cindy Chen (Computer Science), Georges Grinstein (Computer Science), Yan Luo (Electrical and Computer Engineering), and Jie Wang (Computer Science).

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Harshavardhan (Harsh) Achrekar at his doctoral defense on September 6, 2012.
Dr. Marjan Trutschl, a graduate of UMass Lowell’s Computer Science doctoral program, was recently named the Abe Sadoff Distinguished Chair in Bioinformatics at Louisiana State University in Shreveport (LSUS).

Prior to joining LSUS, Dr. Trutschl (MS 1997, ScD 2002) and his wife, Dr. Urska Cvek, also a UML graduate (MBA 2007, ScD 2004), worked as research assistants at the Institute for Visualization and Perception Research under the mentorship of Professor Georges Grinstein.

During that time, Grinstein, Trutschl, Cvek, and other group members co-founded Anvil, Inc., a bioinformatics data mining and visualization software firm.

In 2002, Drs. Trutschl and Cvek accepted faculty positions in the Computer Science Department at LSUS.  Dr. Trutschl also became Visiting Assistant Professor of Bioinformatics and Computational Biology at Louisiana State University Health Sciences Center in Shreveport.  In 2003, they co-founded the Laboratory for Advanced Biomedical Informatics at LSUS and, in 2006, were named its co-directors.

Dr. Trutschl is now Associate Professor of Computer Science, co-director of the Laboratory for Advanced Biomedical Informatics at LSUS and Director of the Biomedical Informatics Core at the Center for Molecular and Tumor Virology at LSUHSC-S.  

He has received several awards including Outstanding Research Award (LSUS, 2005), Circle of Excellence Award (LSUS, 2009) and Distinguished Researcher Award (NCRR/IDEA Louisiana Biomedical Research Network, 2010).

His research focuses on data visualization, biomedical informatics, neural networks, data mining and cluster and distributed computing and is funded by NIH, NSF, Department of Defense, several pharmaceutical companies and other organizations.

Drs. Trutschl and Cvek will co-chair the MediViz Symposium at the International Conference on Information Visualization in France this summer.

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Dr. Marjan Trutschl
Computer Science Department doctoral student Beibei Yang presented a research paper co-authored with Prof. Jesse Heines, Domain-Specific Semantic Relatedness from Wikipedia: Can a Course be Transferred?, at the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT) 2012 conference. The event was held June 3–8, 2012 in Montréal (Québec), Canada.

The conference covered a broad spectrum of disciplines working towards enabling intelligent systems to interact with humans using natural language, and towards enhancing human-human communication through services such as speech recognition, automatic translation, information retrieval, text summarization, and information extraction.

Yang and Heines analyzed the problem of transferring credits across undergraduate institutional. About 1/3 of all college students in the U.S. transfer between institutions. In their work, Yang and Heines proposed a Wikipedia-based domain-specific semantic relatedness measure that analyzes course descriptions to suggest whether a course can be transferred from one institution to another.

They showed that the proposed work received a high correlation of 0.85 when compared to human judgment on computer science courses. And it only took less than 1 minute to compare one pair of courses on a standard laptop system.

Their poster at the conference attracted many researchers from universities and organizations including CMU, Stanford, University of Edinburgh, Google, IBM research, and Nuance.

Yang also received a travel grant of $500 from the conference.

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Ph.D. student Beibei Yang at the NAACL-HLT 2012 student research workshop. (Courtesy Andy Dufilie)

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