Computer Engineering graduate student Alexander Nelson received an honorable mention for the National Science Foundation (NSF) Graduate fellowship. Alex’s research is focused on developing innovative cyber-physical systems that can dramatically improve a person’s standard of living in an impactful way. His current and past projects have involved emergency communications, assistive devices and home automation.

His prior research in assistive devices has gained acceptance to the 2013 IEEE Sensors Conference and 2013 Real Time Systems Symposium and contributed to a Microsoft Software Engineering Innovation Foundation award. His current research gained acceptance to a Works-in-Progress session at the 2013 Real Time Systems Symposium. His research co-mentors are Professors Nilanjan Banerjee and Ryan Robucci.

The NSF honorable mention designation is considered a significant national academic achievement and provides access to cyberinfrastructure resources through NSF’s Extreme Science and Engineering Discovery Environment (XSEDE) computing infrastruture. XSEDE is the most advanced, powerful, and robust collection of integrated advanced digital resources and services in the world. It is a single virtual system that scientists can use to interactively share computing resources, data, and expertise.

Computer Engineering graduate student Alexander Nelson received an honorable mention for the National Science Foundation (NSF) Graduate fellowship. Alex’s research is focused on developing innovative cyber-physical systems that can dramatically improve a person’s standard of living in an impactful way. His current and past projects have involved emergency communications, assistive devices and home automation.

His prior research in assistive devices has gained acceptance to the 2013 IEEE Sensors Conference and 2013 Real Time Systems Symposium and contributed to a Microsoft Software Engineering Innovation Foundation award. His current research gained acceptance to a Works-in-Progress session at the 2013 Real Time Systems Symposium. His research co-mentors are Professors Nilanjan Banerjee and Ryan Robucci.

The NSF honorable mention designation is considered a significant national academic achievement and provides access to cyberinfrastructure resources through NSF’s Extreme Science and Engineering Discovery Environment (XSEDE) computing infrastruture. XSEDE is the most advanced, powerful, and robust collection of integrated advanced digital resources and services in the world. It is a single virtual system that scientists can use to interactively share computing resources, data, and expertise.

NSF REU 2014

Research Experiences for Undergraduates
in Green Building Environments at UMBC

May 28 – August 15, 2014

New emerging “smart plugs” embed a micro-controller and low-power communication device that allows you to monitor the power consumption of individual devices (e.g., microwave, coffee machine, laptop) plugged into power sockets, and communicate such power consumption information over a wireless network to a central monitoring station. Such devices could lead to substantial savings of energy & money by enabling Internet-based monitoring & real-time control of the behavior of individual appliances. This project will use real-life microcontroller kits (ACME Plugs from Moteware) & real-life building measurement data to explore whether such measurement-based monitoring can be used to

• Develop Smart Circuit Breaker — i.e., to lessen the burden of the user of plugging each and every appliance/device in the building with a smart plug; we will investigate connecting multiple devices together with an individual smart plug/smart circuit breaker and design a smart circuit breaker using energy metering chip (ADE7753), AC/DC power supply, Microcontroller with radio (TI MSP430F16 and Cypress Powerline Communications (PLC) modem) and solid state AC relay (Sharp S216SE1) etc.
• Profile individual devices — i.e., use NILM (non-intrusive load monitoring) data analytics algorithm on the time-series of power consumption traces to infer the type of plugged-in device (e.g., distinguish between a laptop & a coffeemaker), thereby building a dynamic catalog of the types & number of devices connected by a consumer.
• Predict the power consumption of individual rooms — i.e., using the past history of the power consumption of individual devices to create predictive inferences of the usage patterns for individual devices (e.g., learn that the individual switches on a dehumidifier for ~3 hrs every Thu).
• Receive $4,500 stipend, free on-campus housing
• Access to university resources, Travel support to UMBC, Unique research experience

Please send your CV (include any relevant experience) and unofficial transcript to Dr. Nirmalya Roy at Sorry, you need javascript to view this email address. .

NSF REU 2014

Research Experiences for Undergraduates
in Green Building Environments at UMBC

May 28 – August 15, 2014

New emerging “smart plugs” embed a micro-controller and low-power communication device that allows you to monitor the power consumption of individual devices (e.g., microwave, coffee machine, laptop) plugged into power sockets, and communicate such power consumption information over a wireless network to a central monitoring station. Such devices could lead to substantial savings of energy & money by enabling Internet-based monitoring & real-time control of the behavior of individual appliances. This project will use real-life microcontroller kits (ACME Plugs from Moteware) & real-life building measurement data to explore whether such measurement-based monitoring can be used to

• Develop Smart Circuit Breaker — i.e., to lessen the burden of the user of plugging each and every appliance/device in the building with a smart plug; we will investigate connecting multiple devices together with an individual smart plug/smart circuit breaker and design a smart circuit breaker using energy metering chip (ADE7753), AC/DC power supply, Microcontroller with radio (TI MSP430F16 and Cypress Powerline Communications (PLC) modem) and solid state AC relay (Sharp S216SE1) etc.
• Profile individual devices — i.e., use NILM (non-intrusive load monitoring) data analytics algorithm on the time-series of power consumption traces to infer the type of plugged-in device (e.g., distinguish between a laptop & a coffeemaker), thereby building a dynamic catalog of the types & number of devices connected by a consumer.
• Predict the power consumption of individual rooms — i.e., using the past history of the power consumption of individual devices to create predictive inferences of the usage patterns for individual devices (e.g., learn that the individual switches on a dehumidifier for ~3 hrs every Thu).
• Receive $4,500 stipend, free on-campus housing
• Access to university resources, Travel support to UMBC, Unique research experience

Please send your CV (include any relevant experience) and unofficial transcript to Dr. Nirmalya Roy at Sorry, you need javascript to view this email address. .

NSF REU 2014

Research Experiences for Undergraduates
in Green Building Environments at UMBC

May 28 – August 15, 2014

New emerging “smart plugs” embed a micro-controller and low-power communication device that allows you to monitor the power consumption of individual devices (e.g., microwave, coffee machine, laptop) plugged into power sockets, and communicate such power consumption information over a wireless network to a central monitoring station. Such devices could lead to substantial savings of energy & money by enabling Internet-based monitoring & real-time control of the behavior of individual appliances. This project will use real-life microcontroller kits (ACME Plugs from Moteware) & real-life building measurement data to explore whether such measurement-based monitoring can be used to

• Develop Smart Circuit Breaker — i.e., to lessen the burden of the user of plugging each and every appliance/device in the building with a smart plug; we will investigate connecting multiple devices together with an individual smart plug/smart circuit breaker and design a smart circuit breaker using energy metering chip (ADE7753), AC/DC power supply, Microcontroller with radio (TI MSP430F16 and Cypress Powerline Communications (PLC) modem) and solid state AC relay (Sharp S216SE1) etc.
• Profile individual devices — i.e., use NILM (non-intrusive load monitoring) data analytics algorithm on the time-series of power consumption traces to infer the type of plugged-in device (e.g., distinguish between a laptop & a coffeemaker), thereby building a dynamic catalog of the types & number of devices connected by a consumer.
• Predict the power consumption of individual rooms — i.e., using the past history of the power consumption of individual devices to create predictive inferences of the usage patterns for individual devices (e.g., learn that the individual switches on a dehumidifier for ~3 hrs every Thu).
• Receive $4,500 stipend, free on-campus housing
• Access to university resources, Travel support to UMBC, Unique research experience

Please send your CV (include any relevant experience) and unofficial transcript to Dr. Nirmalya Roy at Sorry, you need javascript to view this email address. .

NSF REU 2014

Research Experiences for Undergraduates
in Green Building Environments at UMBC

May 28 – August 15, 2014

New emerging “smart plugs” embed a micro-controller and low-power communication device that allows you to monitor the power consumption of individual devices (e.g., microwave, coffee machine, laptop) plugged into power sockets, and communicate such power consumption information over a wireless network to a central monitoring station. Such devices could lead to substantial savings of energy & money by enabling Internet-based monitoring & real-time control of the behavior of individual appliances. This project will use real-life microcontroller kits (ACME Plugs from Moteware) & real-life building measurement data to explore whether such measurement-based monitoring can be used to

• Develop Smart Circuit Breaker — i.e., to lessen the burden of the user of plugging each and every appliance/device in the building with a smart plug; we will investigate connecting multiple devices together with an individual smart plug/smart circuit breaker and design a smart circuit breaker using energy metering chip (ADE7753), AC/DC power supply, Microcontroller with radio (TI MSP430F16 and Cypress Powerline Communications (PLC) modem) and solid state AC relay (Sharp S216SE1) etc.
• Profile individual devices — i.e., use NILM (non-intrusive load monitoring) data analytics algorithm on the time-series of power consumption traces to infer the type of plugged-in device (e.g., distinguish between a laptop & a coffeemaker), thereby building a dynamic catalog of the types & number of devices connected by a consumer.
• Predict the power consumption of individual rooms — i.e., using the past history of the power consumption of individual devices to create predictive inferences of the usage patterns for individual devices (e.g., learn that the individual switches on a dehumidifier for ~3 hrs every Thu).
• Receive $4,500 stipend, free on-campus housing
• Access to university resources, Travel support to UMBC, Unique research experience

Please send your CV (include any relevant experience) and unofficial transcript to Dr. Nirmalya Roy at Sorry, you need javascript to view this email address. .

NSF REU 2014

Research Experiences for Undergraduates
in Green Building Environments at UMBC

May 28 – August 15, 2014

New emerging “smart plugs” embed a micro-controller and low-power communication device that allows you to monitor the power consumption of individual devices (e.g., microwave, coffee machine, laptop) plugged into power sockets, and communicate such power consumption information over a wireless network to a central monitoring station. Such devices could lead to substantial savings of energy & money by enabling Internet-based monitoring & real-time control of the behavior of individual appliances. This project will use real-life microcontroller kits (ACME Plugs from Moteware) & real-life building measurement data to explore whether such measurement-based monitoring can be used to

• Develop Smart Circuit Breaker — i.e., to lessen the burden of the user of plugging each and every appliance/device in the building with a smart plug; we will investigate connecting multiple devices together with an individual smart plug/smart circuit breaker and design a smart circuit breaker using energy metering chip (ADE7753), AC/DC power supply, Microcontroller with radio (TI MSP430F16 and Cypress Powerline Communications (PLC) modem) and solid state AC relay (Sharp S216SE1) etc.
• Profile individual devices — i.e., use NILM (non-intrusive load monitoring) data analytics algorithm on the time-series of power consumption traces to infer the type of plugged-in device (e.g., distinguish between a laptop & a coffeemaker), thereby building a dynamic catalog of the types & number of devices connected by a consumer.
• Predict the power consumption of individual rooms — i.e., using the past history of the power consumption of individual devices to create predictive inferences of the usage patterns for individual devices (e.g., learn that the individual switches on a dehumidifier for ~3 hrs every Thu).
• Receive $4,500 stipend, free on-campus housing
• Access to university resources, Travel support to UMBC, Unique research experience

Please send your CV (include any relevant experience) and unofficial transcript to Dr. Nirmalya Roy at Sorry, you need javascript to view this email address. .

Center for Hybrid Multicore Productivity Research
Distinguished Computational Science Lecture Series

Image Registration for Multisource Remote Sensing

Dr. Jacqueline Le Moigne
NASA Goddard Space Flight Center
Software Engineering Division – Code 580

3:00pm Thursday, 3 April 2014, ITE 456, UMBC

Satellite remote sensing systems provide large amounts of global coverage and repetitive measurements representing simultaneous or multi-temporal observations of the same features by different sensors; for example over the last 40 years, Landsat satellites have been acquiring more than three million images representing about one petabyte of data. Furthermore, most sensors are carried on separate platforms, resulting in a tremendous amount of data that must be combined. In meeting some of the Earth System Science objectives, the combination of all these data at various resolutions — spatial, radiometric and temporal — will facilitate a better understanding of Earth and space science phenomena, and image registration enables the first step towards this integration.

In this talk, we will describe the image registration challenge in the context of Earth and space remote sensing. Then, we will review a subset of the methods that are being utilized to tackle this challenge, and finally we will describe some of our work that utilizes multiscale representations, in particular wavelets and over-complete representations, as well as more recent work dealing with the registration of Martian data based on crater extraction and matching.

Dr. Le Moigne is the Assistant Chief for Technology in the Software Engineering Division at NASA Goddard, and was Goddard Center Associate for ESTO/Advanced Information Systems Technology Program, from 2009 to 2012. Dr. Le Moigne received a B.S. and a M.S. in Mathematics, and a Ph.D. in Computer Science from the University Pierre and Marie Curie, France. While her Ph.D. thesis dealt with biomedical imagery, her post-doctoral work at the UMD Computer Vision Lab focused on the development of a visual navigation system for the first DARPA Autonomous Land Vehicle project. At NASA Goddard since 1990, Dr. Le Moigne has performed extensive work in the processing and the analysis of remote sensing data. Her work particularly focuses on image registration, utilizing multiscale representations as well as high-performance and on-board processing. More recent work dealt with creating web-based access to benchmark data for Image Processing education and research (imageseer.nasa.gov). Currently, Dr. Le Moigne is the PI of a Goddard Internal project focused on Distributed Spacecraft Missions. She has published over 120 publications, including 23 journal papers, holds one patent, and has co-edited a book on “Image Registration for Remote Sensing” published by Cambridge University Press in 2011. She is a NASA Goddard Senior Fellow, an IEEE Senior Member and an ABET Program Evaluator. She was a NATO Science for Peace and Security Committee Panel Member from 2008 to 2011. In 2012, she received the NASA Exceptional Service Medal and the Goddard Information Science and Technology Award.

Center for Hybrid Multicore Productivity Research
Distinguished Computational Science Lecture Series

Image Registration for Multisource Remote Sensing

Dr. Jacqueline Le Moigne
NASA Goddard Space Flight Center
Software Engineering Division – Code 580

3:00pm Thursday, 3 April 2014, ITE 456, UMBC

Satellite remote sensing systems provide large amounts of global coverage and repetitive measurements representing simultaneous or multi-temporal observations of the same features by different sensors; for example over the last 40 years, Landsat satellites have been acquiring more than three million images representing about one petabyte of data. Furthermore, most sensors are carried on separate platforms, resulting in a tremendous amount of data that must be combined. In meeting some of the Earth System Science objectives, the combination of all these data at various resolutions — spatial, radiometric and temporal — will facilitate a better understanding of Earth and space science phenomena, and image registration enables the first step towards this integration.

In this talk, we will describe the image registration challenge in the context of Earth and space remote sensing. Then, we will review a subset of the methods that are being utilized to tackle this challenge, and finally we will describe some of our work that utilizes multiscale representations, in particular wavelets and over-complete representations, as well as more recent work dealing with the registration of Martian data based on crater extraction and matching.

Dr. Le Moigne is the Assistant Chief for Technology in the Software Engineering Division at NASA Goddard, and was Goddard Center Associate for ESTO/Advanced Information Systems Technology Program, from 2009 to 2012. Dr. Le Moigne received a B.S. and a M.S. in Mathematics, and a Ph.D. in Computer Science from the University Pierre and Marie Curie, France. While her Ph.D. thesis dealt with biomedical imagery, her post-doctoral work at the UMD Computer Vision Lab focused on the development of a visual navigation system for the first DARPA Autonomous Land Vehicle project. At NASA Goddard since 1990, Dr. Le Moigne has performed extensive work in the processing and the analysis of remote sensing data. Her work particularly focuses on image registration, utilizing multiscale representations as well as high-performance and on-board processing. More recent work dealt with creating web-based access to benchmark data for Image Processing education and research (imageseer.nasa.gov). Currently, Dr. Le Moigne is the PI of a Goddard Internal project focused on Distributed Spacecraft Missions. She has published over 120 publications, including 23 journal papers, holds one patent, and has co-edited a book on “Image Registration for Remote Sensing” published by Cambridge University Press in 2011. She is a NASA Goddard Senior Fellow, an IEEE Senior Member and an ABET Program Evaluator. She was a NATO Science for Peace and Security Committee Panel Member from 2008 to 2011. In 2012, she received the NASA Exceptional Service Medal and the Goddard Information Science and Technology Award.

This coming weekend, the UMBC chess team will play for the President’s Cup in the Final Four of College Chess. UMBC will compete with chess teams from Webster University, the University of Illinois at Urbana Champaign, and Texas Tech University.

The match has been held each year since 2001 between the top four US schools from the Pan American Intercollegiate Team Chess Championship and the winner is considered the top chess team among U.S. colleges and universities.  UMBC has placed first at the Final Four a record six times.

CSEE Professor Alan Sherman, who is the director of the UMBC chess program, will accompany the team to the match, which will be held at the New York Athletic Club in New York City on Friday through Sunday, April 4-6, 2014. Games will be broadcast live on Monroi.

The UMBC team will consist of:

• Board 1: GM Niclas “The Dark Knight” Huschenbeth (USCF rating 2610)
• Board 2: GM Akshayraj “The Indian Knight” Kore (2519)
• Board 3: M Levan “The Georgian Gangster” Bregadze (2469)
• Board 4: IM and WGM Nazi “The Black Widow” Paikidze (2378)
• Alternate: WGM Sabina “Sunshine” Foisor (2315)