Agenda

SP Mini symposium

Where am I? An experiment in Indoor Localization

Prof. K.V.S. Hari
Department of ECE, Indian Institute of Science, Bangalore

Abstract: Indoor Localization of people (or objects), where GPS is not available, is an interesting problem with several applications. Several solutions exist, of which, positioning based on WiFi, Video-Tag identification, Ultra Wideband signals and Inertial sensors, are a few examples. In this talk, we consider a scenario where a First-Responder team enters a building after a disaster and the position of each member of the team needs to be known to the control center outside the disaster-affected building. Specifically, we will discuss how an Inertial Navigation System (INS) embedded in a shoe can be designed, to address this problem.

Brief Bio: K.V.S. Hari received the B.E., M.Tech and PhD(1990) degrees from Osmania University, IIT Delhi, University of California at San Diego, respectively. Since 1992, he has been a Faculty Member at the Department of ECE, Indian Institute of Science (IISc), Bangalore, where he is currently a Professor and coordinates the activities of the Statistical Signal Processing Lab in the department. Currently, he is also an Affiliated Professor in the Department of Signal Processing, KTH-Royal Institute of Technology, Stockholm. His current research and development interests include MIMO Wireless Communication, Sparse signal Processing, Indoor Localization and Assistive technologies for the Elderly.

Overview of Signal Processing Seminar

Agenda

Microelectronics Colloquium

Sten Vollebregt, Massimo Mastrangeli, Daniele Cavallo

Tenure track colloquium

Daniele Cavallo (TS group); wideband phased arrays for future wireless communication terminals, Massimo Mastrangeli (ECTM Group); Towards smart organs-on-chip, Sten Vollebregt (ECTM group) Emerging electronic materials: from lab to fab

Signal Processing Seminar

Krishnaprasad Nambur Ramamohan

Signal processing algorithms for acoustic vector sensors

Symposium MRI for Low-Resource Setting

Steven Schiff, Johnes Obungoloch

Sustainable Low-Field MRI Technology for Point of Care Diagnostics in Low-Income Countries

Kick-off meeting of the project "A sustainable MRI system to diagnose hydrocephalus in Uganda"

Signal Processing Seminar

Peter Gerstoft

Machine learning in physical sciences

Machine learning (ML) is booming thanks to efforts promoted by Google. However, ML also has use in physical sciences. I start with a general overview of ML for supervised/unsupervised learning. Then I will focus on my applications of ML in array processing in seismology and ocean acoustics. This will include source localization using neural networks or graph processing. Final example is using ML-based tomography to obtain high-resolution subsurface geophysical structure in Long Beach, CA, from seismic noise recorded on a 5200-element array. This method exploits the dense sampling obtained by ambient noise processing on large arrays by learning a dictionary of local, or small-scale, geophysical features directly from the data.

Signal Processing Seminar

Aydin Rajabzadeh

manufacturing defect detection