Advanced Activity Recognition
Lama's research is focused on creating contextually aware experiences that understand users through sensing and sense making and act on that context to help with many aspects of their lives. Lama has 16 years of experience in the areas of computer architecture, context-aware computing, multi-modal adaptive interfaces, embedded systems, wireless technologies and sensor networks. Previous work at Intel involved researching and developing the next generation of self-organizing sensor network nodes (Intel Mote Platforms). Lama has pioneered deployments of these technologies in health applications as well as various commercial and industrial settings.
Using the CrowdSignals Data
Lama will use the CrowdSignals data to develop and test new, more robust models for human activity recognition. These models can be used to predict and support users' tasks and activities.
"I am really excited about CrowdSignals.io because it solves one of the major bottlenecks for algorithmic innovation in context awareness: the lack of sufficient labeled sensor data. This could become the community’s gold standard for benchmarking algorithms and creating new ones."
- Lama Nachman, Senior Principal Engineer
Director of Anticipatory Computing
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