[home]   [news]   [pubs]   [resume]   [talks]   [service]
I hold dual academic and industrial appointments as a Senior Lecturer (Associate Professor) at University College London (UCL), and a Principal Scientist at Bell Labs. At UCL I am part of the Digital Health Institute and UCL Interaction Center, while at Bell Labs I am a member of the Internet-of-Things research group.

Before moving to England, I spent four years at Microsoft Research based in Beijing. There I was a Lead Researcher within the Mobile and Sensing Systems group (MASS) led by Feng Zhao. In March 2011, I received a Ph.D. from Dartmouth College under the supervision of Andrew T. Campbell and Tanzeem Choudhury.

My research interests revolving around the systems and modelling challenges that arise when computers collect and reason about people-centric sensor data. At heart, I am an experimentalist who likes to build prototype mobile sensing systems based on well-founded computational models.

Please visit my publications page or google scholar profile to learn more about my work.

I can be reached at: niclane at acm dot org

Mar '16 BodyScan is provisionally accepted at MobiSys! This is part of our new initiative into forms of radio-based sensing for wearables. A sister system (HeadScan) will appear at IPSN in April; pre-print of the HeadScan paper is available here.
Honored to be serving as the PC Chair of HotMobile 2017. I will be working with Elizabeth Belding who will be the General Chair. Stay tuned for more details.
Feb '16 I have accepted a Senior Lecturer (Associate Professor) position at UCL, but will be also maintaining my current role at Bell Labs. At UCL, I will be part of the Digital Health Institute and the UCL Interaction Center.
Pre-prints of two of our recent papers on enabling deep learning for mobile and wearables are now available. "DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices" will appear at IPSN 2016; while "From Smart to Deep: Robust Activity Recognition on Smartwatches using Deep Learning" is to be presented at WristSense 2016.
Jan '16 Two papers provisionally accepted to IPSN '16. The first details unobtrusive monitoring of internal body states (such as, eating and drinking) using a wearable that exploits PHY-level radio transmissions; a first-of-its kind device developed with collaborators at MSU. The second presents DeepX -- a software-based accelerator for deep learning models that enables wearable-class hardware to cope with the deepest forms of this important direction in machine learning.
Oct '15 Initial results of our measurement study examining the system resource overhead of deep learning inference phases on wearables, phones and embedded devices will appear at the IoT-App workshop at SenSys.
Sept '15 DeepEar wins best paper at UbiComp '15! Congrats to all my co-authors.
Aug '15 I am joining the editorial board of ACM SIGMOBILE Mobile Computing and Communications Review, “GetMobile Magazine”; there I will be working with Robin Kravets on a column covering the latest and greatest in mobile computing research.
DeepEar, and our broader work into deep learning for wearable and mobile platforms, is featured in the New Scientist -- 'Eavesdropping app will turn your smartphone into a virtual PA'.