human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "BikeNet: A mobile sensing system for cyclist experience mapping"
  Abstract: We present BikeNet, a mobile sensing system for mapping the cyclist experience. Built leveraging the MetroSense architecture to provide insight into the real-world challenges of people-centric sensing, BikeNet uses a number of sensors embedded into a cyclist's bicycle to gather quantitative data about the cyclist's rides. BikeNet uses a dual-mode operation for data collection, using opportunistically encountered wireless access points in a delay-tolerant fashion by default, and leveraging the cellular data channel of the cyclist's mobile phone for real-time communication as required. BikeNet also provides a Web-based portal for each cyclist to access various representations of her data, and to allow for the sharing of cycling-related data (for example, favorite cycling routes) within cycling interest groups, and data of more general interest (for example, pollution data) with the broader community. We present: a description and prototype implementation of the system architecture based on customized Moteiv Tmote Invent motes and sensor-enabled Nokia N80 mobile phones; an evaluation of sensing and inference that quantifies cyclist performance and the cyclist environment; a report on networking performance in an environment characterized by bicycle mobility and human unpredictability; and a description of BikeNet system user interfaces.

Connected through hyperedge HE-1 (induced by source paper "Sensing meets mobile social networks: the design, implementation and evaluation of the CenceMe application"):
  with members:
    - "People-centric urban sensing"
    - "Energy-Efficient Continuous Activity Recognition on Mobile Phones: An Activity-Adaptive Approach"
    - "From taxi GPS traces to social and community dynamics: A survey"
    - "An event-driven energy efficient framework for wearable health-monitoring system"
    - "SensOrchestra: Collaborative Sensing for Symbolic Location Recognition"
    - "IMPROVING RESIDENTIAL ENERGY CONSUMPTION AT LARGE USING PERSUASIVE SYSTEMS"

Connected through hyperedge HE-2 (induced by source paper "People-centric urban sensing"):
  with members:
    - "Sensing meets mobile social networks: the design, implementation and evaluation of the CenceMe application"
    - "A wireless sensor network For structural monitoring"

Connected through hyperedge HE-3 (induced by source paper "SPS: A Novel Semantics-Aware Scheme for Location Privacy in People-Centric Sensing Network"):
  with members:
    (none)

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science