CS Senior Katelyn Manzo CLAS Outstanding Graduating Student

Katelyn (Katie) Manzo has been a member of the Geosensor Networks lab since August 2015, when she participated in a summer course in programming Arduinos. After doing exceptionally well in the required first year CS courses, she still was on the verge of dropping the major due to the mostly abstract content and question if it would be a right fight. Arduinos, on the other hand, were practical, hands on, and  fun. She understood all concepts in lightening speed, and made the perfect ‘hershey kisses’ right off the bat when sautering  the radio boards. A natural!


Katie practice soldering

She started to work as a MLA (Maine Learning Assistant) for COS250 in Fall 2016, and started with Dr. Nittel in the summer of 2016 as an undergraduate research assistant. She helped develop the course material for COS120: Computing that Matters, especially the Arduino and Database section, and made several instructional videos for the course.

In Fall 2016, she was a founding member of the ACM-W student group at UMaine, and became the group’s Vice President. The group has been very active organizing events for women in computing at UMaine and reached out to high school and middle school students. In 2017, Katie became the ACM-W president, and organized weekly meeting, programming meets and parties on top of her regular course load.

Since Spring 2016, Katie has participated in a project with Dr. Nittel, her advisor and mentor, and Dr. Sharon Klein, an Economics professor for Sustainable Energy. She familiarized herself with a recently developed website that collects data about US Community Renewable Energy Projects (www.communityenergyus.net). Supported via a Margaret Chase Smith Public Affairs Scholarship Katie added a social media component to the original website. The social media component includes user profiles and user discussion forums with regard to user-specific questions around community renewable energy. She has presented her research and work at the Center for Undergraduate Research’s Student Research Symposium in April 2018.

Katie is one of two women left in her graduating class; this is why she feels strongly about supporting women in computing, and the exposure of computing to middle school and high school girls are very important to her. This is also something that she hopes to carry through to the workplace when she graduates.

Katie topped it all of with being the College of Liberal Arts and Sciences Outstanding Graduating Student in 2018.  Congratulations, Katie! Very well done, we are very proud of you!

Here is an interview with Katie.


Katie Manzo CLAS Outstanding Graduating Senior, 2018

Katie with family

Katie with John and Family


Katie carrying the CLAS flag at Commencement


Katie and other CS students at Commencement

J.C. Whittier successfully defends PhD thesis

On April 27 2018, J.C. Whittier successfully defended his Phd thesis titled “Towards an efficient, scalable stream query operator framework for computing continuous fields”. His work has focused on developing a stream operator framework for spatio-temporal inverse distance weighting interpolation of massive sensor data streams. The stream query operator framework achieves a through-out of 100K tuples/sec, on a state of the art workstation. Furthermore, he developed a second stream operator framework that efficiently evaluates value predicates over continuous fields in real-time. Congratulation, J.C.!


4 graduate assistantships available (Fall 2018)

We have 4 graduate teaching assistantships available starting Fall 2018. If you are interested in getting a  PhD in real-time GIS, real-time sensor data streaming, geosensor networks, and social sensing, please apply!


The University of Maine, School of Computing and Information Science is seeking students interested in pursuing advanced degrees in spatial informatics and/or computer science. The school offers MS degrees in Spatial Information Science and Engineering, Spatial Informatics, Information Systems and Computer Science as well as PhDs in Computer Science and Spatial Information Science and Engineering.

Funding for several general graduate research assistantships and teaching assistantships is available from the School starting in September 2018.

Faculty research interests cover a range of topics in geographic information science, data science, and computer science that include: human computer interaction, real-time sensor data streaming, geosensor networks, ontologies and semantic modeling, spatial databases, information policy, spatial and temporal reasoning, and context modeling, among others. The school seeks students with research interests that align with the above research topics. Funding is available through graduate teaching and research assistantships.

Interested applicants should have prior experience or an undergraduate degree in computer science, geographic information science or a closely related degree. On line applications can be accessed through the University of Maine Graduate School at the link https://umaine.edu/graduate/apply/

Interested candidates may contact Kate Beard for further information. Rolling applications are being accepted for Fall 2018 enrollment.

The University of Maine is an Affirmative Action/Equal Opportunity Employer and the University especially encourages applications from women and minorities.

“Real-Time Earthquake Monitoring with Spatio-Temporal Fields” paper published at “Spatiotemporal Computing” Symposium 2017

Today, J.C. Whittier and Iranga Subasinghe are presenting a paper titled Real-Time Earthquake Monitoring with Spatio-Temporal Fields at the Second International Symposium on “Spatiotemporal Computing“, taking place Aug 7-9 2017 at Harvard, MA.

Our objective was to bring together 3 components: a) realistic, publicly available, real-time sensor data streams, b) an open source data stream engine and c) the field data type model (Liang2016) to implement a realistic real-time analysis application using the field model, and explore its implementation using a open source data stream engine. We chose the  Southern California Integrated GPS Network (SCIGN), which provides real-time GPS streams along Southern California fault lines, and the Apache Spark environment (including Spark, Kafka and MongoDB) for implementation.  The live demo can be found at http://shakeviz.geosensornetworks.net.

The paper can be accessed here: ISSTC-2017-whittier_nittel.

Note: a few weeks after finishing our prototype, the SCIGN socket making the live stream available seems to have failed, and is currently under revision. The data currently shown in the demo is data that we archived; the demo loops over this data (April-May 2017 data).  Once the socket streams the data again, we will reconnect to the live data.

Screen Shot 2017-08-07 at 2.13.48 PM

US Community Energy Projects Database and Website

Over the last year, we have been involved in a project to develop a US Community Energy Projects Database and Website, in collaboration with Dr. Sharon Klein, Economics Department, University of Maine. Dr. Klein collected the initial data set, and Katrina Stinson, a CS undergraduate, built the database and website. We soft- launched this spring.

The US Community Energy Projects website is a centralized location for sharing information about community energy projects across the United States. It began as a compilation of publicly available information on renewable energy projects (solar, wind, biomass, geothermal, hydropower) with a “group” or “community” element. Now that the website and associated database are publicly available, the group hopes people with direct knowledge of projects will add/correct information to keep the database growing and current. CWRU renewable energy projects are listed.

Please feel free to share!



Python programming summer camp for Maine high school students

Today, we started teaching a gender-balanced group of 20 Maine high school students the beginnings of Python programming with little whale robots. Good fun!


Katrina Stinson presents capstone project on Visual Analytics for US Community Green Energy Projects

I had the pleasure of advising Katrina Stinson, in collaboration with Dr. Klein (Economics), for her senior capstone project over the last 2 semesters. This project entailed building a website with a database backend holding over 5000 community energy projects in the US that can now be accessed, queried and analyzed through the website. Users can register accounts and add new projects. Her capstone specifically focused on adding visual analytics to the community energy project data (statistics page).

The website can be found at http://communityenergyus.net.

Katrina also graduates as best Senior of her class (and she did the program in 3 instead of the usual 4-5 years).

Congratulations, Katrina!


COS120 – Computing that Matters

This spring, we taught a class with new experimental methods of teaching programming to non-CS majors. The class started with a Scratch module, then 4 weeks of Python, and after that a choice of Arduinos and Databases, GIS, robots, drones or virtual reality.

Katie Manzo, my CLA (computing learning assistant), and I oversaw the Arduino and Database group. Everyone received an Arduino starter kit, and worked their way through different circuit tutorials. We integrated sensor streaming from Arduino boards sensors to Python programs and SQL databases.

The group had 2 final projects: building a zeotrope regulated by a soft potentiometer, and a live streaming sensor station visualizing live data.
Here are some snapshots from the class.

The class material (for self study) is available at this link.


J.C. Whittier successfully defends dissertation proposal

Today, J.C. Whittier successfully defended his dissertation proposal “Towards an efficient, scalable stream operator framework for computing continuous fields”, and advanced to Ph.D. candidacy.

Congratulations, J.C.!


SIE556 Real-time Sensor Data Streams Final Projects (2016)

This semester, the students again came up with a great selection of final projects, applying their new knowledge of real-time sensor data streams processing with mysql, python stream queries and Cloudera’s Spark and some Arduino programming to a project of their interest.

There are several general thematic groups in the class:

Group 1: Using Arduinos and temperature and humidity data to monitor environmental conditions in real-time

Jon Cole built a Unity-based 3D Visualization of live and historic buoy data in the Gulf of Maine.

Check out the interactive demo here. Code here.

Devon Stetson built a sensor data stream analysis system deploying a temperature data in his dorm room.

Welles Tisdale extended his undergraduate capstone project of building an automated greenhouse using Arduinos with live sensor data analysis, alerts and long-term monitoring.

Group 2: Real-time smartphone sensor data analysis to detect parking and departing events at UMaine in real-time.

Avery Dunn and Anthony Stetson’s current capstone project of real-time smartphone sensor data analysis to detect parking and departing events at UMaine in real-time

Group 3: Real-time Speeding Alerts using Arduinos and a GPS unit.

Kaitelyn Haase has just started to learn programming at the beginning of this semester as a graduate student in the MSIS program, and so it is even more impressive that she managed to soldered an Arduino “sandwich” with a shield and an GPS unit, program the Arduino to compute the current speed in real-time and sound a audio alert when the speed was over the speed limit of 70Mi/H. She also analyzed and visualized the collected information.

Group 4: Interactive Visualization of Argo Drifter Data.

Brad Sheperd built a python-based graphic user interface to stream process netCDF encoded stream data from the Argo drifters that cover the oceans world-wide. The visualization allows to interactively spatially subset the data and select different parameters.

Group 5: Transforming Sensor Data into Sounds using SuperCollider

Rod O’Connor combined a set of light sensors on an Arduino with python stream based processing the incoming data and sending it to SuperCollider to ‘animate’ the sensor readings as sound (very cool!).

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