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Ameya Agaskar
Also published under:A. Agaskar
Affiliation
Amazon Alexa, Seattle, WA, USA
Topic
Modulo Operation,System Throughput,Wireless,Achievable Rate,Adaptive Beamforming,Additive Noise,Analog Domain,Antenna Array,Antenna Array Elements,Array Elements,Automatic Gain Control,Channel Coherence Time,Cloud Radio Access Network,Coherence Time,Compression Scheme,Computational Complexity,Conditional Probability,Covariance Matrix,Delay Difference,Delay Spread,Distortion Levels,Doppler Shift,Doppler Spread,Fading Channel,Flight Test,Ground Station,High Signal-to-noise Ratio,Increase In Computational Complexity,Interval Size,Joint Design,Linear Combination,Low-resolution Analog-to-digital Converters,Massive Multiple-input Multiple-output,Massive Multiple-input Multiple-output Systems,Multiple Antenna Arrays,Multiple Antennas,Multiple Arrays,Mutual Information,Natural Disasters,Optimal Rate,Optimization Problem,Quadrature Amplitude Modulation,Quantization Bits,Quantization Error,Quantum,Rate Of Nodes,Rayleigh Fading Channel,Relay Network,Relay Nodes,Remote Areas,
Biography
Ameya Agaskar received the B.S. degree in engineering physics and the M.Eng. degree in electrical and computer engineering from Cornell University in 2007 and 2008, respectively, and the Ph.D. degree in engineering sciences from Harvard University in 2015. From 2008 to 2020 he was a Staff Member with MIT Lincoln Laboratory, where he worked on adaptive array signal processing for radar and communication applications. Since 2020, he has been working on speech signal processing and machine learning for Amazon Alexa, Cambridge, MA, USA. He received the Best Student Paper award at IEEE GlobalSIP 2014 for his paper on randomized Kaczmarz algorithms.