- at Harvard
We are non-deterministic, infinite-state automata. Our genes determine our starting states. External influences (inputs) induce transformations (state transitions) and responses (outputs). Our lifelong experience is a continuous time-continuous transition Markov random process. What defines each of us in totality at a particular moment in time is a snapshot of his state, which is a random variable conditioned upon the initial state and all past influences.
Ling-Pei Kung (a.k.a. Ken) obtained his Ph.D from the MIT Media Laboratory, where his dissertation explores the potential applications of reconfigurable computing for media processing and the issues of reconfigurable computing in general.
His professional interests include algorithms, computational structures (control and datapath) and parallel processing, complexity theory, system engineering (SW/HW co-design, SOC), implementation methodologies, and EDA tools in the following application areas: digital signal processing, digital image/video processing, machine vision, digital communication, real-time control, etc.
He has multi-disciplinary formal training (MSEE, MS. Materials Sci. & Eng., BS, Chem. Eng.) in science and engineering. Believing knowledge is only compartmented by human but not in nature, he is fond of drawing analogies, generalizing theories, providing different perspectives, and applying knowledge across different domains.
Prior to obtaining his PhD, he worked in the industry as a VLSI engineer on MPEG hardware, a researcher for DTV systems, and a DSP engineer.
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