Univeristy of York, UK
Mailing Address: CSE 029
Department of Computer Science
University of York
Heslington, York, UK
Other Current Positions:
Chair (2017- Present)
ACM-W UK Professional Chapter
Stay Connected: Twitter
ACM-W UK mentoring scheme, Royal Holloway, University of London, 2018.
Organiser and program chair
PhD Thesis Examiner
PhD Thesis Examiner, NIT Bhopal, India Jan 2015
Reviewer for Journals
Reviewer for Conferences and workshops
Dr Yadav is currently a Lecturer (=Assistant Professor) in Computer Science Department at the University of York, UK and a visiting research fellow at Computer Lab, Cambridge University. Before joining York, she was a research fellow at Computer Laboratory, Cambridge University and was part of the System Research Group, worked on Databox Project. Before joining this group she worked as a research associate in Faculty of Economics at Cambridge University and London e-science Center and Social Computing Group (with Prof. John Darlington) and AESE Group (with Prof. Julie McCann) in Computing Department at Imperial College London. She worked on TSB funded OpenShare, FP7 funded Cyberlab, and NERC funded FUSE project at AESE group; a visiting researcher at US Army Research Labs, Adelphi, Maryland, US from Aug, 2011 to Jan, 2012 and also worked on ITA (International Technology Alliance) led by IBM Research from September, 2007 to Jan, 2012 as a Supplement Researcher.
She defended her PhD thesis at Distributed System and Network Group, Computing Department, Imperial College London in November, 2011. At Imperial College, she worked with Professor Julie A. McCann. Her PhD was funded by UKIERI (UK-India Education and Research Initiative) fellowship.
The PhD work was focused on Design of Wireless communication stack for Event-driven applications, especially for low-power embedded systems. It is an interdisciplinary research area involves background knowledge of embedded system design, communication systems, and software engineering.
In brief, her research interests include IoT and Wireless Networks, Machine Leaning (TinyML/UltraML), Citizen Science, Complex and Dynamical Systems.