In recent times, researchers have proposed numerous approaches that allow smartphones to determine user current locations (e.g., home, office, railway station, restaurant, street, supermarket etc.) and their activities (such as sitting, walking, running, bicycling, driving, cutting bread, making coffee, watching television, working at laptop, taking lunch, using water tap, brushing teeth, flushing toilet etc.) in real-time. But, to infer much richer story of context-aware applications, it is necessary to recognize the smartphone surfaces - for example on the sofa, inside the backpack, on the plastic chair, in a drawer or in your pant-pocket. This paper presents SurfaceSense, a two-tier, simple, inexpensive placement-aware technique, that uses smartphone’s embedded accelerometer, gyroscope, magnetometer, microphone and proximity sensor to infer where phone is placed. It does not require any external hardware and provides 91.75% recognition accuracy on 13 different surfaces.