NSF Research Experiences for Undergraduates

NSF-REU in Biochemical, Environmental, and MOlecular Research in Engineering (BEMORE)

Students that join the BEMORE REU Site will gain the interdisciplinary knowledge, skills, and training to address a variety of grand challenges, including antibiotic resistance, sustainable plastic replacements, smart polymers, urban air quality, bio-based sensors, and more. Participants will prepare to address knowledge gaps, develop new technologies, and bring unique perspectives to complex problems at the interface of biochemical and environmental systems. Learn more about NSF-REU BEMORE.
Faculty Mentors: Dr. Lee Blaney (professor of chemical, biochemical and environmental engineering) and Dr. Mark Marten (professor and chair of chemical, biochemical and environmental engineering)
Dates: Summer 2024 (June 3 – August 9, 2024)

NSF-REU in Online Interdisciplinary Big Data Analytics in Science and Engineering

This REU Site program will provide 8-week summer online research experiences to undergraduates on how to utilize modern data science and high-performance computing (HPC) techniques to process and analyze big data in many science and engineering disciplines such as Atmospheric Science, Mechanical Engineering, and Medicine. Learn more about NSF-REU Big Data.
Faculty Mentors: Dr. Matthias K. Gobbert (professor of mathematics) and Dr. Jianwu Wang (associate professor of information systems)
Dates: Summer 2024 (June 10 – August 2, 2024)

NSF-REU in Smart Computing and Communications

The goal of this Research Experiences for Undergraduate (REU) site in Smart Computing and Communications is to increase technical awareness, intellectual curiosity, creativity, and critical thinking of undergraduate students in smart computing and communications. This project will contribute to the preparation of a diverse workforce of scientist trained in the multi-disciplinary area, which promises to impact most every sector of society such as healthcare, natural disasters, energy, transportation, agriculture, finance, manufacturing, and national defense. Learn more about NSF-REU Smart Computing.
Faculty Mentors: Dr. Nirmalya Roy (professor of information systems) and Dr. Anupam Joshi (professor of computer science and electrical engineering and acting dean, COEIT)
Dates: Summer 2024 (June 3 – August 9, 2024)

NSF-REU in Big Data and Machine Learning Techniques for Atmospheric Remote Sensing (Team 1)

Many satellites generate very large volumes of observational data. For instance, NASA satellite Terra was launched in 1999 and has been in mission for over 20 years. Its MODIS instrument generates about 100 GB of level 2 Cloud Product data every day, which accumulates over 700 TB in total. Distributed and scalable machine/deep learning algorithms are needed to train over large scale datasets. In this project, we will extend our preliminary work to utilize larger volumes of training datasets by designing algorithms that are scalable on multiple computing nodes, especially GPU nodes and study how prediction accuracy could be further improved. Learn more about NSF-REU Big Data.
Faculty Mentors: Dr. Jianwu Wang (associate professor of information systems) and Dr. Matthias K. Gobbert (professor of mathematics)
Dates: Summer 2023 (June 5 – July 28, 2023)

NSF-REU in Biochemical, Environmental, and MOlecular Research in Engineering (BEMORE)

Students that join the BEMORE REU Site will gain the interdisciplinary knowledge, skills, and training to address a variety of grand challenges, including antibiotic resistance, sustainable plastic replacements, smart polymers, urban air quality, bio-based sensors, and more. Participants will prepare to address knowledge gaps, develop new technologies, and bring unique perspectives to complex problems at the interface of biochemical and environmental systems. Learn more about NSF-REU BEMORE.
Faculty Mentors: Dr. Lee Blaney (professor of chemical, biochemical and environmental engineering) and Dr. Mark Marten (professor and chair of chemical, biochemical and environmental engineering)
Dates: Summer 2023 (May 31 – August 10, 2023)

NSF-REU in Smart Computing and Communications

The REU research projects will be conducted in three interrelated thrust areas of smart computing and communications: (i) security and privacy protection, (ii) novel applications, and (iii) sensing and adaptive networking. Proposed projects will include a mix of theory and hands-on work and will leverage enabling paradigms (e.g., cloud computing, Internet-of-Things, high-speed wireless) to design, model, and implement novel techniques and solutions for smart computing and communication applications, encompassing algorithms for artificial intelligence, data mining, machine learning, edge analytics, signal processing, and big data. Some projects will also include building functional prototypes for demonstration. Learn more about NSF-REU Smart Computing.
Faculty Mentors: Dr. Nirmalya Roy (professor of information systems) and Dr. Anupam Joshi (professor and chair of computer science and electrical engineering)
Dates: Summer 2023 (June 5 – August 12, 2023)

NSF-REU in Big Data and Machine Learning Techniques for Atmospheric Remote Sensing (Team 1)

Many satellites generate very large volumes of observational data. For instance, NASA satellite Terra was launched in 1999 and has been in mission for over 20 years. Its MODIS instrument generates about 100 GB of level 2 Cloud Product data every day, which accumulates over 700 TB in total. Distributed and scalable machine/deep learning algorithms are needed to train over large scale datasets. In this project, we will extend our preliminary work to utilize larger volumes of training datasets by designing algorithms that are scalable on multiple computing nodes, especially GPU nodes and study how prediction accuracy could be further improved. Learn more about this research opportunity.

Faculty Mentors: Dr. Jianwu Wang (associate professor of information systems) and Dr. Matthias K. Gobbert (professor of mathematics)
Dates: Summer 2022 (June 6 – July 29, 2022)