Ph.D. Students
Yishuang Lin
Jianfeng Song
Hailiang Hu
Chanwei Hu (jointly advised by Prof. Khatri)
Donghao Fang
Prianka Sengupta
Zhenrui Wang (jointly advised by Prof. Shi)
Chunkai Fu
Cristhian Roman Vicharra
M.S. Students
Visiting Scholars
Ning Xu, Wuhan University of Technology, China
Youmeng Li, Tianjin University, China
Xinguo Deng, Fuzhou University, China
Wai-Kei Mak, National Tsinghua University, Taiwan
Visiting Graduate Students
Yujie Wang, Nankai University, China
Guan-Qi Fang, National Taiwan University of Science and Technology, Taiwan
Yu-Hung Huang, National Taiwan University of Science and Technology, Taiwan
Graduated Ph.D. Students
Chin-Ngai Sze (Cliff), 2005, IBM Austin Research Lab
Di Wu, 2006, Cadence
Ganesh Venkataraman, 2007, Magma
Ke Cao, 2007, Marvell
Shiyan Hu, 2008, Michigan Tech University (Faculty)
Rupak Samanta, 2008, Intel
Yifang Liu, 2009, Google
Kyu-Nam Shim, 2012, Intel
Xi Chen, 2013, Qualcomm
Jae-Yeon Won, 2015, Synopsys
Hao He, 2016, Thumbtack
Jiafan Wang, 2017, Synopsys
Chaofan Li, 2018, Synopsys
Justin Sun, 2018, Quicken Loans
He Zhou, 2019, Cadence
Wenbin Xu, 2019, Cadence
Lin Huang, 2019, Cadence
Yanxiang Yang, 2019, Amazon
Lang Feng, 2020, Nanjing University
Hongxin Kong, 2020, Cadence
Nithyashankari Jayasankaran, 2021, Qualcomm
Erick Carvajal Barboza, 2021, University of Costa Rica (Faculty)
Rongjian Liang, 2021, Nvidia
Yaguang Li, 2022, Nvidia
Graduated M.S. Students
Rishi Chaturvedi, 2004, Analog Devices Inc.
Anand Rajaram, 2004, Texas Instrument
Vikram Seth, 2004, Redpine Signals Inc.
Min-Seok Kim, 2006, Samsung Electronics
Qiuyang Li, 2006, Juniper Networks
Sridhar Varadan, 2007
Trenton Henrichson, 2008, AMD
Nimay Shah, 2008, Analog Devices Inc.
Carlos Esquit Hernandez, 2008, University of the Valley of Guatemala
Pratik Shah, 2008, Nvidia
Venkata Rajesh Mekala, 2010, Nvidia
Subodh Prabhu, 2010, Cisco
Tanuj Jindal, 2010, Intel
Amrinder Singh, 2010, Intel
Sundararajan Ramakrishnan, 2010, Intel
Yu Yang, 2011, Synopsys
Yi-Le Huang, 2011, Nvidia
Qiong Zhao, 2012, AMD
Alvin Chang, 2012, Intel
Zheng Xu, 2013, National Instruments
Jung-Tai Tsai, 2013, Xilinx
Farah Rasheed, 2013, JHU Applied Physics Lab
Ruixiao Ni, 2013, Marvell
Shalimar Rasheed, 2014, Nvidia
Gongming Yang, 2014, FactSet
Rohit Kumar, 2014, Nvidia
Chia-Yu Wu, 2015, Altera
Sitong Zhai, 2015
Shivaram Irukula, 2015, Intel
Ang Lu, 2015, Xilinx
Zhuoyang Gao, 2015, Amazon
Yiren Shen, 2016, Amazon
Rohit Gangrade, 2016, Apple
Pu Chen, 2016, Amazon
Nfn Shrija, 2016, Intel
Saumil Gogri, 2019, Cypress Semiconductor
Amrutha Shikaripura Jagadeesh, 2019, Intel
Abhijith Reddy, 2019, Marvell
Vaishnavi Venkatesh, 2019, Micron
Sanjay Rajashekar, 2020, Apple
Sara Jacob, 2020, NXP
For Prospective Students
Roughly speaking, VLSI CAD is to develop software algorithms to assist VLSI circuit designs. This objective itself implies that both Electrical Engineering (EE) and Computer Science (CS) background are requested. Since the ultimate goal is to enable efficient and high performance circuit design, obviously you have to understand VLSI circuit design. As for the CS part, both algorithm design and proficient programming skill are essential because CAD research is somewhat equivalent to algorithm design and the effectiveness of the algorithms need to be verified through software implementations. Sometimes, advanced algorithm designs require knowledge in Applied Math such as linear programming, graph theory and combinatorial optimizations.
Ideally, it is preferred that you have background on all of the aforementioned fields: VLSI design, algorithms and applied math. However, this rarely happens for a junior graduate student. In practice, I wish you to have a solid background on at least one of these fields. As long as you are diligent and intelligent, you will be successful!