Microsoft Research employees are being recognized among the 53 computing professionals named 2016 Fellows of the Association for Computing Machinery (ACM). The award gives credit to exceptional contributions to the computing industry and is been running since 1993.
“As nearly 100,000 computing professionals are members of our association, to be selected to join the top one percent is truly an honor,” explains ACM President Vicki L. Hanson.
“Fellows are chosen by their peers and hail from leading universities, corporations and research labs throughout the world. Their inspiration, insights and dedication bring immeasurable benefits that improve lives and help drive the global economy.”
Among the fellows selected from Microsoft Research are:
- Ricardo Bianchini: For contributions to power, energy and thermal management of servers and datacenters
- Rustan M. Leino: For contributions to making program verification accessible and practical
- Abigail Sellen: For contributions to human-computer interaction and the design of human-centered technology
- Sudipta Sengupta: For contributions to cloud networking, storage, and data management
- Ravi Kannan: For contributions to the field of theoretical computer science
- Venkata N. Padmanabhan: For research contributions and professional leadership in networked and mobile computing systems
- Ganesan Ramalingam: For contributions to static program analysis
Microsoft Research Projects
The seven Microsoft Research employees have driven development for the company. For example, K. Rustan M. Leino is the Principal Researcher in the Research in Software Engineering (RiSE) group. His most recent papers have covered refinement of programming language.
Microsoft Research is a hugely important division for the company. Microsoft is leading development in such breakthroughs as immersion in VR through haptic feedback and touch and rotation input for mobile devices.
Other interesting Research breakthroughs in 2016 include improvements in computer learning for video to language. This advancement was achieved using MSR-VTT and LSTM-E.