I am an assistant professor in the Department of CSE at IIT Madras. My research interests are in designing IoT-based/mobile systems that interact with and interpret (sense) the physical world, spanning both algorithm design as well as end-to-end system prototyping.
With advancement in the field of aerial robotics, unmanned aerial vehicles (UAVs) have
gained wide applicability providing an array of "on-demand" services. We explore the
capabilities of UAVs to host wireless networks that are lightweight, flexible, portable and
easy to deploy on demand. This finds great applicability where network infrastructure is
absent/destroyed, sparingly present or additional capacity is required. Such networks, due
to their ubiquitous nature, are really helpful in disaster scenarios that can aid first
responders in an emergency.
With millions of apps in the play-store, their diverse requirements for resources and a
sky-rocketing user-base, guaranteeing good Quality of Experience (QoE) has become a
challenge particularly in resource constrained and highly congested wireless networks. With
a multitude of radios available in newer generation smartphones (WiFi, 3G, 4G, LTE) and
accessibility to multiple cellular ISPs simultaneously (dual SIMs, Google Fi) a key question
we ask is, "Which network is just enough for a good QoE and yet save on the phone's battery,
data cost etc and be fair to other users of the network?".
Harness the versatility of RF-based sensing (RFID,
wideband, millimeter waves) to address challenges in location estimation, smart spaces,
surveillance and RF communications. Such sensing is often aided by autonomous mobile
platforms like robots or drones that makes the process ubiqutious, scalable and time
efficient, often in challenging environments like emergency situations.
Demo Video of the SkyLiTE network. SkyLiTE
is an UAV based LTE network.
Spectrum databases maintain geographic availability of unused RF spectrum or whitespaces.
However, they are often inaccurate leading to inefficient spectrum usage. Hence such
databases need to be intelligently augmented by real spectrum measurements wherever and
whenever necessary. Further, to make spectrum sensing scalable, pervasive and potentially
crowdsourced, we create 'mobile spectrum sensing' devices by interfacing low cost, portable
SDRs to smartphones.
We are broadly interested in designing IoT-based/mobile systems that interact with and interpret (sense) the physical world, spanning both algorithm design as well as system prototyping. Our research focuses on building intelligent sensing platforms, through the use of heterogeneous sensor modalities, to solve real-world problems - e.g., indoor localization, smarthome applications or intelligent human computer interaction interfaces.