Dr. Justin Romberg is the Schlumberger Professor and the Associate Chair for Research in the School of Electrical and Computer Engineering and the Associate Director for the Center for Machine Learning at Georgia Tech.
Dr. Romberg received the B.S.E.E. (1997), M.S. (1999) and Ph.D. (2004) degrees from Rice University in Houston, Texas. From Fall 2003 until Fall 2006, he was a Postdoctoral Scholar in Applied and Computational Mathematics at the California Institute of Technology. He spent the Summer of 2000 as a researcher at Xerox PARC, the Fall of 2003 as a visitor at the Laboratoire Jacques-Louis Lions in Paris, and the Fall of 2004 as a Fellow at UCLA's Institute for Pure and Applied Mathematics. In the Fall of 2006, he joined the Georgia Tech ECE faculty. In 2008 he received an ONR Young Investigator Award, in 2009 he received a PECASE award and a Packard Fellowship, and in 2010 he was named a Rice University Outstanding Young Engineering Alumnus. He is currently on the editorial board for the SIAM Journal on the Mathematics of Data Science, and is a Fellow of the IEEE.
His research interests lie on the intersection of signal processing, machine learning, optimization, and applied probability.
- Ph.D., Electrical and Computer Engineering, Rice University, 2004
- M.S., Electrical and Computer Engineering, Rice University, 1999
- B.S.E.E., Rice University, 1997
Professor Romberg's research focuses on signal processing, machine learning, and data science, particularly in developing theoretical frameworks and algorithms for efficient data acquisition and inference. His work investigates structured signal models, compressed sensing, and computational methods for high-dimensional data analysis. Research efforts are aimed at advancing understanding in data-driven approaches and contribute to fields that require processing of large-scale, complex datasets, with active involvement of graduate and undergraduate students.
Professor Romberg's teaching interests concentrate on signal processing, data analysis, and machine learning at both undergraduate and graduate levels. His instruction emphasizes foundational concepts and practical implementation in these areas, preparing students to address complex problems in engineering and related fields. He actively involves students in hands-on learning experiences that integrate theoretical understanding with computational techniques and encourages collaboration among diverse student groups.
- ONR Young Investigator Award, 2008
- Presidential Early Career Award in Science and Engineering (PECASE), 2009
- Packard Fellowship, 2009
- Rice University Outstanding Young Engineering Alumnus, 2010
- Z. Xu et al., A Multiply‑and‑Accumulate SAR‑ADC‑Based Hybrid Slepian Beamformer, IEEE JSSC, 2026.
- J. Park et al., Real-Time Front-End Adaptation for Energy-Efficient mmWave Radar Sensor, IEEE SENSORS 2025.
- F. Wang, J. Romberg, H. Wang, S. Xu, Power amplifiers and methods of controlling same, US Patent 12,463,594, 2025.
- C. Kaushik, J. Romberg, V. Muthukumar, Approximating high‑dimensional empirical kernel matrices, arXiv:2511.03892, 2025.
- N. Singh et al., A Fast Broadband Beamspace Transformation, arXiv:2512.08887, 2025.