Currently, I am part of the Mobile Systems Research Lab at the Department of Computer Science and Technology, University of Cambridge. I am working in the MEDEA project funded by the Wellcome Trust to detect Alzheimer's disease using outdoor mobility and sleep data.
I got my PhD in Sep-2019 from the School of Informatics, University of Edinburgh under Dr. Rik Sarkar in "Machine Learning and Privacy Preserving Algorithms for Spatial and Temporal Sensing" [Thesis]. I was a Research Associate in the Department of Computing, Imperial College London under Dr. Thomas Heinis (till Sep-2020).
My primary research interest is to design analysis and privacy-preserving algorithms using tools from topology, geometry, and statistics to infer abstract knowledge from massive and noisy spatio-temporal sensing data. I am also interested in Federated Learning problems and data management problems related to spatial and temporal data.
We are organizing the first Geometric Mobility Workshop as part of CGWeek-2021.
Human mobility has high diversity and heterogeneity and interventions that focus on protecting the most active individuals and most popular venues can significantly reduce the infection while retaining high levels of social activity.
Proposes private and efficient data structure to answer range queries along paths in a planar graph.
An efficient framework to map trajectories to Euclidean vectors called signatures using differential topology. This enables Euclidean machine learning tools for the trajectories.
Particle filter based perioricity detection for phase driving niosy periodic event streams.
Supports efficient and parallel range queries by partitioning large spatial datasets into computing clusters. Partitioning ensures that the clusters are load balanced in in terms of data and queries. It uses random sampling and learning methods for partitioning.
Using Bluetooth connection automatically detects when a user leaves her workstation and transfers active applications contexts to phone, for example URL and timing of a Youtube video being watched.
An intermediator router with all supported communication hardware and a software layer to convert between protocols. The router handles the control messages for the concerned protocols and encapsulates the data as the protocols require.
Worked on Bluetooth and Bluetooth Low Energy communication solution for Android and Wearable embedded devices.
Design and develop BLE software stack as a part of Intel’s first BLE chip.
Develop Bluetooth stack and hardware specific drivers for Android phones with Intel Bluetooth chip.
Intel Bluetooth drivers in Linux kernel, advanced BLE data link layer in Android open source (available in all Android devices since Android 7).
Develop automation framework to test Intel communication hardware.
Analysis and Privacy Preserving Algorithms of Spatiotemporal sensing
CPI: 9.49 / 10
Master's thesis: Determination of Safe regions in Optimized Dynamically Updatable Programs
CPI: 9.40 / 10
Ranked 9st out of four hundred thousand students in the state in Higher Secondary (10+2) examination, 2005
Awarded Best Student Project of the institute by TCS Ltd. for B.Tech. final year research thesis (1 yr.), 2009
Scored 10/10 in the M.Tech. final year research thesis (1 yr.), 2011
Received Intel India divisional recognition award (awarded quarterly across Intel India) for conceptualizing Intel’s first smart watch, 2014
Demonstrated feasibility of seamless context transfer in Intel India Innovation Summit, 2013
First to demonstrate Object Transfer Service (OTS) in Android platform across all industries, 2014
Represented Intel Corp. in Bluetooth SIG Interoperability test event as a technology expert, 2015
Received both Principal’s Career Development Scholarship and The Global Research Scholarship (£31.5k / year for three years), Sep ’15 (Only student to receive both in that year from School of Informatics)