The Multimedia Communications and Systems Lab (MCSL) at the University at Buffalo is led by Prof. Nick Mastronarde. We conduct research on resource management in computer systems and wireless networks, with recent emphasis on UAV networks and systems. Although we work on diverse topics, a lot of our research is thematically connected by an underlying mathematical framework (Markov decision processes and reinforcement learning), a common application domain (scheduling and resource management), and an emphasis on energy-efficiency.
We gratefully acknowledge support from the Air Force Research Laboratory,the National Science Foundation, and GE Aviation.
Multiple PhD positions are now available. Candidates are expected to start in the Spring 2023 or Fall 2023 Semester.
Candidates will conduct research related to one or more of the following topics:
- Radio frequency sensing
- Unmanned aerial vehicle (UAV) networking and network simulation
- mmWave communications
- Artificial intelligence and machine learning (AI/ML) for wireless
- Software radio development
Self-motivated candidates with background in Electrical Engineering, Computer Engineering, Computer Science, or closely related disciplines are encouraged to apply. Strong background in wireless communications and networking is required; coding experience (in Python, C, or C++) is also required. Preference will be given to applicants with MS degrees, applied optimization or machine learning background, software radio development experience, experience with ns-3, experience working in Linux, or experience working with open-source UAV software tools (e.g., ArduPilot, QGroundControl, DroneKit).
To apply, please send your CV, transcripts, and publications (if any) to Dr. Nick Mastronarde by email (email@example.com).
Nick Mastronarde is an Associate Professor in the Department of Electrical Engineering at the University at Buffalo. He received his Ph.D. degree in Electrical Engineering at the University of California, Los Angeles (UCLA) in 2011 and his B.S. and M.S. degrees in Electrical Engineering from the University of California, Davis in 2005 (Highest Honors, Department Citation) and 2006, respectively. He has been the recipient of several awards and honors including a first year department fellowship through the Electrical Engineering department at UCLA, the Dissertation Year Fellowship through the Graduate Division at UCLA, the Dimitris N. Chorafas Foundation Award for 2011, and the 2020 SEAS Senior Teacher of the Year Award.
He has spent four summers (2013, 2015, 2016, 2018) as a faculty fellow at the US Air Force Research Laboratory (AFRL) Information Directorate in Rome, NY. In the summer of 2010, he was a graduate intern at IBM Research Watson Lab in the Exploratory Stream Analytics group where he developed learning algorithms for discovering anomalies in massive volumes of streaming data. In the summer of 2007, he was a graduate student intern at Intel Corporation in the Graphics Architecture Team where he developed and patented an algorithm enabling the selective use of fractional and bidirectional video motion estimation in an H.264/AVC encoder.
Prof. Mastronarde's research interests are in the areas of resource allocation and scheduling in wireless networks and systems, UAV networks, 4G/5G networks, dynamic power management, cross-layer design and optimization, Markov decision processes (MDPs), and reinforcement learning.
We are grateful for the support that we have received from the National Science Foundation (NSF), the US Air Force Research Laboratory (AFRL), SOCOM, ARMOR-IIMAK, US Ignite, Schmidt Futures, the Griffis Institute, and the University at Buffalo.
The project website for our recent NSF SWIFT award can be found here: AI-Enabled Spectrum Coexistence between Active Communications and Passive Radio Services: Fundamentals, Testbed and Data
Prof. Nick Mastronarde: firstname.lastname@example.org
Department of Electrical Engineering
226 Davis Hall
University at Buffalo
Buffalo, NY 14260