Enyue (Annie) Lu
REU Site: EXERCISE - Explore Emerging Computing in Science and Engineering
PI, Funded by NSF (CNS-2149591), $414,979, February 2022-January 2025
The REU site: EXERCISE project will continue to promote “parallel thinking,” an important computational thinking skill. The PI, together with a group of faculty mentors from diverse backgrounds, will encourage student researchers to explore parallel computing through parallel algorithms, concurrent software, and multi-core architectures. They will tackle data and compute intensive problems in the selected science and engineering application areas such as public health and global epidemics, sustainable aquaculture farming, human activity recognition, topological data analysis, and computational fluid dynamics.
Transforming Shellfish Farming with Smart Technology and Management Practices for Sustainable Production
PI (subcontract), Funded by USDA, collaborating with UMD and UMES, (Total $10M, SU portion: $164,230), Sep. 2020-Aug. 2025
Current practices used in shellfish farming lack the basic technological advancement found in today’s digital automated world. This project seeks to synthesize recent advances in the fields of sensing and imaging, artificial intelligence, robotics, agricultural automation, computer vision, and high performance computing to bring about a major boost in production of shellfish. Along with improving the efficiency of aquaculture industries, increasing technological advancements can be beneficial to wide fish populations and continuing effort to increase the health of Chesapeake Bay.
REU Site: EXERCISE - Explore Emerging Computing in Science and Engineering
PI, Funded by NSF (CNS-1757017), $369,995, February 2018-January 2022
The REU Site will focus on parallel computing for solving big data problems. The proposed student summer research will cover the following three major areas: data mining for quickly finding relatively simple patterns in massive amounts of loosely structured data, machine learning for building mathematical models that represent structure and statistical trends in data with good predictive properties, and hardware architectures for designing inter-core interconnection network on a microchip with improved performance for data traffic.
Project Website: http://faculty.salisbury.edu/~ealu/REU/REU.html
REU Site: EXERCISE - Explore Emerging Computing in Science and Engineering
PI, Funded by NSF (CNS-1460900), $359,984, February 2015-January 2019
The REU Site will focus on four aspects of parallel computing, namely, algorithms, software, architecture and applications. Students will work with faculty mentors in completing cutting-edge research projects to tackle data and compute intensive applications that emphasize the above four aspects. Students will be exposed to emerging paradigms in parallel computing such as MapReduce and GPU computing, and will have opportunities to explore concurrent software and multiprocessor architectures, and design efficient parallel algorithms, and to tackle data and compute intensive problems in networks and security, image and signal processing, and geographic information systems.
Project Website: http://faculty.salisbury.edu/~ealu/REU/REU.html
REU Site: EXERCISE - Explore Emerging Computing in Science and Engineering
PI, Funded by NSF (CCF-1156509), $306,408, April 2012-March 2016
The NSF REU Site: EXERCISE is an interdisciplinary project that explores emerging paradigms in parallel computing with data and compute-intensive applications in the fields of science and engineering. Students will apply emerging parallel computing models including GPU computing with NVIDIA CUDA and MapReduce computing on Amazon EC2 to tackle data and compute-intensive problems such as network pattern detection and medical image reconstruction.
Project Website: http://faculty.salisbury.edu/~ealu/REU/REU.html
Simulated Learning
Faculty mentor, Funded by NSF Bridges for SUCCESS Program, May 2011-Aug 2011
Virtual Simulations provide several advantages such as allowing students to practice with less stress and risk than if they were performing the actual process. Students are also able to practice at any time as opposed to scheduled clinical hours, saving both time and money. In this project, we’ve created a health care environment with an artificial intelligence that allows students to practice making health care decisions. This project was accomplished through creating a mobile application in conjunction with a virtual world.
Faculty collaborators:
o Dr. Tina Brown Reid, Department of Nursing, Salisbury University
Students:
o Andrew Boyd
o Dan Dunning
o Omar Ejaz
Video:
Posters:
| Virtual Training | Mobile Application |
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Mid-Atlantic Institute for Space and Technology (MIST)
Faculty mentor, Funded by NASA, Aug 2006-May 2008
"Development of a Customized GUI for STK": lead the GUI team at Salisbury University to provide the Mission Planning Laboratory with customized graphical user interface for enhanced visualization of missions launched from the Wallops Flight Facility.
Faculty collaborations:
Dr. Mara Chen, Department of Geography and Geosciences, Salisbury University
Dr. Jeffrey Emmert, MIST Mission Planning Lab & Physics Department, Salisbury University
Students:
- Paul Halvorsen
- Tu Hoang
Software tools: Satellite Tool Kit (STK), Flexsim Simulation
Related links:
Presentations:
- Paul Halvorsen and Tu Hoang, “A Customized GUI for Mission Panning Lab at Salisbury University: Design and Implementation”, presented in the 22nd National Conference on Undergraduate Research, April, 2008
“Mission Planning Laboratory at Salisbury University: Using Computer Programming and Geographic Information Science for Space Mission”, presented in the 7th Annual Student Research Conference, Salisbury University, April 27, 2007
Faculty Associate, "Wireless Spacecraft Bus"
Participate in a smart sensor web design. Establish a mote laboratory to provide research and education opportunities on wireless sensor networks for students and faculties at Salisbury University.
Faculty collaborations:
Dr. Min Song, Electrical and Computer Engineering Department, Old Dominion University
Dr. Robert Ash, Department of Aerospace Engineering, Old Dominion University
Hardware facilities: MIB510, MTS310, MICAz
Software tools: Crossbow mote-view
Related links:
Workshops:
ODU-SU MIST Wireless Communications Workshops, April 22, 2008
ODU-SU MIST Wireless Workshop Day, May 10, 2007
