Affiliation
Signal Processing Systems Group
Faculty of Electrical Engineering, Mathematics, and Computer Science
Delft University of Technology
Building 36, Mekelweg 4,
2628 CD Delft, Netherlands
Office: 17.040
Email: G.Joseph@tudelft.nl
Postdoctoral Researcher, Department of Electrical Engineering and Computer Science, Syracuse University, NY, USA(2019-'21)
PhD, Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore, India (2014-'19)
Masters of Engineering, Signal Processing, Indian Institute of Science, Bangalore, India (2012-'14)
Bachelor of Technology, Electronics and Communication Eng., National Institute of Technology, Calicut, India (2007-'11)
Geethu Joseph received the B. Tech. degree in electronics and communication engineering from the National Institute of Technology, Calicut, India, in 2011, and the M. E. degree in signal processing and the Ph.D. degree in electrical communication engineering (ECE) from the Indian Institute of Science (IISc), Bangalore, in 2014 and 2019, respectively. She was a postdoctoral fellow with the department of electrical engineering and computer science at Syracuse University, NY, USA, from 2019 to 2021. She is currently a tenured assistant professor in the signal processing systems group at the Delft University of Technology, Delft, Netherlands.
Dr. Joseph was awarded the 2022 IEEE SPS best PhD dissertation award and the 2020 SPCOM best doctoral dissertation award. She is also a recipient of the Prof. I. S. N. Murthy Medal in 2014 for being the best M. E. (signal processing) student in the ECE dept., IISc, and the Seshagiri Kaikini Medal for the best Ph.D. thesis of the ECE dept. at IISc for the year 2019-'20
Dr. Joseph holds 50+ peer-reviewed publications in the fields of signal processing, communications, and control theory. She is an associate editor of the IEEE Sensors Journal and an active reviewer for major journals and conferences in signal processing, communications, and control theory. Her research interests include statistical signal processing, network control, and machine learning.