【活动推广】ConnectEd公益讲座：听美国名校教授聊聊找教职那些事—

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ConnectEd at UCI & UCLA

美国名校教授Panel系列分享会

——工程/计算机专场

活动介绍

Introduction

在读博士、考虑申请博士的人，经常担心的一个问题就是：毕业后何去何从？听说找教职竞争激烈，到底怎么样才能在美国R1大学找到一份终身教职？

为了帮助正在准备申请博士，尤其是美国全奖博士的以及博士在读正在找tenure track教职的同学们提供学术和职业发展支持，ConnectEd at UCI & UCLA特地邀请到了三位美国名校的助理教授们，来给大家分享他们在美国读博以及找教职的经验！

本次教授系列座谈会是由UCI AGS官方赞助的公益性学术分享活动

。一共五个分会场：

社科类（已于3/27成功举办），生物工程医学类（已于4/13成功举办），工程/计算机类，商科类，人文类。

本次为大家带来的就是工程/计算机类的专场，专业涉及：计算机科学、计算机工程、环境工程、结构工程、力学和材料等。

活动主办方：ConnectEd at UCI & UCLA

嘉宾介绍

Meet our Panelists

Sitao Huang (黄思陶), Ph.D.

UCI 电气工程和计算机科学系助理教授

个人主页：

https://sitaohuang.com/

科研方向：FPGA and GPU based hardware acceleration, high-level synthesis (HLS), programming language and compilation flow for hardware accelerators, heterogeneous computing.

简介：Sitao Huang is an assistant professor in the Department of Electrical Engineering and Computer Science at the University of California, Irvine. He received his Ph.D. degree and M.S. degree in Electrical and Computer Engineering from University of Illinois at Urbana-Champaign in 2021 and 2017 respectively. He received his B.Eng. degree in Electronics Engineering at Tsinghua University in 2014. He is a recipient of 2019 Sundaram Seshu International Student Fellowship and 2018 Rambus Computer Engineering Fellowship. His research won several awards, including the Best Paper Award at IDEAL 2021, Best Paper Nomination at ASP-DAC 2021, the Student Innovation Award at the 2018 IEEE HPEC Graph Challenge, and the first place at DAC 2019 System Design Contest.

Ziqi Wang, Ph.D.

UC伯克利结构工程、力学和材料系助理教授

个人主页：

https://ce.berkeley.edu/people/faculty/ziqiwang

科研方向：(i) computational uncertainty quantiﬁcation methods for rare event simulation; (ii) reliability of civil engineering structures subjected to seismic hazards.

简介：Dr. Ziqi Wang is an Assistant Professor in Structural Risk and Reliability for Multi-Hazards at the University of California, Berkeley. His main research interest lies in Structural Reliability, Random Vibration and Uncertainty Quantiﬁcation for Civil Engineering. He is also interested in the application of stochastic dynamics and probabilistic methods to a broader ﬁeld of science.

Yufei Ding (丁雨霏), Ph.D.

UCSB 计算机科学系&电气与计算机工程系助理教授

个人主页：

https://sites.cs.ucsb.edu/~yufeiding/

科研方向：domain-specific language design, architecture and compiler optimization, and hardware acceleration; building high-performance, energy-efficient, and high-fidelity programming frameworks for emerging technologies such as quantum computing, machine learning, and deep learning

简介：Yufei Ding joined the Department of Computer Science (with a joint appointment in the Department of Electrical & Computer Engineering), University of California at Santa Barbara as an Assistant Professor in Nov 2017. She received her Ph.D. in Computer Science from North Carolina State University, and B.S. and M.S. in Physics from University of Science and Technology of China and the College of William and Mary, respectively. She is a recipient of NSF CAREER Award (2020), IEEE Computer Society TCHPC Early Career Researchers Award for Excellence in High Performance Computing (2019), NCSU Computer Science Outstanding Dissertation Award (2018), NCSU Computer Science Outstanding Research Award (2016), and Distinguished Paper Award at OOPLSA (2020).

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