Course Topics:
 

• Math Foundations (from scratch)

      Linear Algebra, Data/Signal Processing, Probability and Learning

• GPS, WiFi, Sensor Fusion

      Algorithms: Triangulation, Trilateration, Clustering, SLAM, Kalman filter

       Applications: Outdoor and indoor localization, mapping, IoT

• IMU Sensors, Motion Tracking

      Algorithms: Dead reckoning, PCA, Hidden Markov Models (HMM), Kalman Filters

      Applications: Activity tracking, Gesture recognition, Sports analytics, wearable computing

• Microphone, Speakers

      Algorithms: SVD, Noise Cancellation, Dynamic Time Warping, 3D Binaural Sounds

      Applications: Acoustic Sensing, Voice Assistants, Earphone computing

• Camera, Light

      Algorithms: SIFT/SURF, Wavelets, 3D Point clouds, Structure from motion (SfM)

      Applications: Augmented reality, Visual Communication, Shadow sensing

• Wireless Radios (WiFi, BLE, 5G)

      Algorithms: Beamforming, Time of Flight (ToF), Clock synchronization, FMCW, Doppler

      Applications: Presence detection, Liquid identification, Bio-monitoring, Digital agriculture

• Mobile Sensing, Spatial Diversity

      Algorithms: Synthetic aperture, RF imaging, Particle filter

      Applications: Drones, Autonomous vehicles

• Security and Privacy

      Algorithms: Classification, Non-linearity, Viterbi decoding, MLE, Stochastic gradient descent

      Applications: Fingerprinting, side channel, inference

• Emerging areas: Edge computing, battery-free devices, Earable computing, …

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   Grading Information:
    - Homework, Assignmeents:       20%
    - Paper reviews (~10):                 15%
    - 1 mid-term exam (Apr 15th):     25%
    - Final project:                             40% (you can use platform of your choice, e.g., MATLAB, Python, Java, Android, etc.)
    - Project report (5+ pgs):             Only for 4 credit students