Building efficient, responsive and usable devices and services
We explore a broad range of topics within mobile computing, covering:
- New kinds of devices, including wearable and embedded.
- Sensors in mobile, wearable, and embedded devices, and sensor networks.
- Systems and architectures to maximize the efficiency of mobile devices, including power, CPU, and bandwidth.
Applications of mobile computing to create technologies that augment our personal and professional digital lives to enhance individual and collaborative pursuit.
- Applying expertise in machine learning, visualization, mobile computing, sensors, and devices, and quantitative and qualitative evaluation techniques to improve the state of the art in physiological computing, health care, home technologies, computer-assisted creativity, and entertainment.
- Kyungmin Lee, David Chu, Eduardo Cuervo, Johannes Kopf, Yury Degtyarev, Sergey Grizan, Alec Wolman, and Jason Flinn, Outatime: Using Speculation to Enable Low-Latency Continuous Interaction for Mobile Cloud Gaming, in MobiSys 2015, ACM – Association for Computing Machinery, 3 June 2015.
- Thomas Ball, Sebastian Burckhardt, Jonathan de Halleux, Michał Moskal, Jonathan Protzenko, and Nikolai Tillmann, Beyond Open Source: The TouchDevelop Cloud-based Integrated Development Environment, in In Proceedings of 2nd ACM International Conference on Mobile Software Engineering and Systems (MOBILESoft), ACM – Association for Computing Machinery, May 2015.
- Earlence Fernandes, Oriana Riva, and Suman Nath, My OS ought to know me better: In-app behavioural analytics as an OS service, Workshop on Hot Topics in Operating Systems (HotOS), May 2015.
- Yujia Li, Kaisheng Yao, and Geoffrey Zweig, FEEDBACK-BASED HANDWRITING RECOGNITION FROM INERTIAL SENSOR DATA FOR WEARABLE DEVICES, April 2015.
- Dimitrios Lymberopoulos, Jie Liu, Xue Yang, Romit Roy Choudhury, Vlado Handziski, Souvik Sen, Filip Lemic, Jasper Buesch, Zhiping Jiang, Han Zou, Hao Jiang, Chi Zhang, Ashwin Ashok, Chenren Xu, Patrick Lazik, Niranjini Rajagopal, Anthony Rowe, Avik Ghose, Nasim Ahmed, Zhuoling Xiao, Hongkai Wen, Traian E. Abrudan, Andrew Markham, Thomas Schmid, Daniel Lee, Martin Klepal, Christian Beder, Maciej Nikodem, Szymon Szymczak, Pawel Hoffmann, Leo Selavo, Domenico Giustiniano, Vincent Lenders, Maurizio Rea, Andreas Marcaletti, Christos Laoudias, Demetrios Zeinalipour-Yazti, Yu-Kuen Tsai, Arne Bestmann, Ronne Reimann, Liqun Li, Chunshui Zhao, Stephan Adler, Simon Schmitt, Vincenzo Dentamaro, Domenico Colucci, Pasquale Ambrosini, Andre Ferraz, Lucas Martins, Pedro Bello, Alan Alvino, Vladica Sark, Gerald Pirkl, and Peter Hevesi, A Realistic Evaluation and Comparison of Indoor Location Technologies: Experiences and Lessons Learned, in The 14th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN '15), ACM – Association for Computing Machinery, April 2015.
- Human Experience and Design
- Mobile and Sensing Systems Group
- Ubiquitous Computing
- Wireless and Networking
- SemanticPaint: Interactive 3D Labeling and Learning at your Fingertips
- Open Source Software from Microsoft for Academics
- HoloLens for Research
- Project Premonition
- How do people share digital and physical things in the home?
- MSR Ethics Review Framework
- Data Science at Microsoft
- Robust Distributed System Nucleus (rDSN)