Dr. Xin Li
Carnegie Mellon University
The aggressive scaling of CMOS technology results in large-scale process variations and makes it continually more challenging to create reliable and robust analog and mixed-signal (AMS) integrated circuits. This talk presents several novel methodologies to facilitate large-scale statistical performance modeling for AMS circuits. The objective is to capture the impact of process and environmental variations for today’s nanoscale AMS circuits. In particular, we explore a number of novel statistical techniques (e.g., sparse regression, Bayesian model fusion, etc) to address the modeling challenges posed by high dimensionality and strong nonlinearity. As such, the parametric yield of nanoscale ICs can be predicted both accurately and efficiently. In addition, the proposed modeling techniques are further applied to self-healing of AMS circuits in order to minimize parametric yield loss.
Xin Li received the Ph.D. degree in Electrical and Computer Engineering from Carnegie Mellon University, Pittsburgh, PA in 2005, and the M.S. and B.S. degrees in Electronics Engineering from Fudan University, Shanghai, China in 2001 and 1998, respectively.
He is currently an Assistant Professor in the Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA. In 2005, he co-founded Xigmix Inc. to commercialize his PhD research, and served as the Chief Technical Officer until the company was acquired by Extreme DA in 2007. In 2011, Extreme DA was further acquired by Synopsis (Nasdaq: SNPS). Since 2009, he has been appointed as the Assistant Director for FCRP Focus Research Center for Circuit & System Solutions (C2S2). His research interests include computer-aided design, neural signal processing, and power system analysis and design.
Dr. Xin Li has been an Associated Editor of IEEE Trans. on Computer-Aided Design of Integrated Circuits and Systems (TCAD) since 2012 and an Associated Editor of Journal of Low Power Electronics (JOLPE) since 2011. He served on the Technical Program Committee of Design Automation Conference (DAC) from 2011 to 2012, the Technical Program Committee of International Conference on Computer-Aided Design (ICCAD) from 2008 to 2011, the Technical Program Committee of International Workshop on Timing Issues in the Specification and Synthesis of Digital Systems (TAU) from 2010 to 2012, the Technical Program Committee of International Conference on VLSI Design (VLSI) in 2009, and the IEEE Outstanding Young Author Award Selection Committee in 2006. He received the NSF Faculty Early Career Development Award (CAREER) in 2012, a Best Paper Award from Design Automation Conference (DAC) in 2010 and two IEEE/ACM William J. McCalla ICCAD Best Paper Awards in 2004 and 2011.