Renju Liu (刘人驹)

I am a computer science Ph.D. candidate at UCLA. I am currently working with Prof. Mani Srivastava at Networked and Embedded System Lab (NESL).

Prior joining NESL, I was proudly and luckily working with Prof. Felix Xiaozhu Lin at Crossroads Systems Exploration Lab (XSEL) at Purdue.

My research interest widely lies on System, Security, Deep Reinforcement Learning (DRL) Infrastructures and Applications.

Google Scholar
Curriculum Vitae: Send me an email!


RemedIoT: Remedial Actions for Internet-of-Things Conflicts
Renju Liu, Ziqi Wang, Luis Garcia, Mani Srivastava
Proceedings of the 6th Conference on Systems for Built Environments (BuildSys), 2019

VirtSense: Virtualize Sensing through ARM TrustZone on Internet-of-Things
Renju Liu, Mani Srivastava
Proceedings of the 3rd Workshop on System Software for Trusted Execution (SysTex), 2018

VirtSense: Virtualize Sensing through ARM TrustZone on Internet-of-Things (Poster)
Renju Liu, Luis Garcia, Mani Srivastava
Conix Annual Review, 2018

PROTC: Protecting Drone's Peripherals through ARM TrustZone
Renju Liu, Mani Srivastava
in Proc. of the 3rd Workshop on Micro Aerial Vehicle Networks, Systems, and Applications (DroNet), 2017

MyoBuddy: Detecting Barbell Weight Using Electromyogram Sensors
Renju Liu, Bo-Jhang Ho, Hsiao-Yun Tseng, and Mani Srivastava,
in Proc. of the 1st Workshop on Digital Biomarkers 2017

Understanding the Characteristics of Android Wear OS
Renju Liu, Felix Xiaozhu Lin
in Proc. ACM Conf. Mobile Systems, Applications and Services(MobiSys), 2016

Anatomizing System Activities on Interactive Wearable Devices
Renju Liu, Lintong Jiang, Ningzhe Jiang and Felix Xiaozhu Lin,
in Proc. ACM Asia-Pacific Workshop on Systems (APSys), 2015

Highlighted Projects

1. Securely train the drone to recognize unsafe behaviors through deep reinforcement learning / deep Q-network.
2. Modify deep reinforcement learning and deep learning infrastructure to speed up training process.
3. Modify or capture Android Apps sensitive information without root previlege by eavesdropping Binder messages.
4. Investigating OS design bottlenecks for wearable computing devices.

Relevant Research and Industry experience

Graduate Student Research for Prof. Mani Srivastava (Fall 2016 - cur)
UCLA, CS Department, Los Angeles, CA

Use deep reinforcement learning to solve unmanned vehicle safety issues.

Software Engineering Intern in Detection Infrastructure (June 2017 - Sept 2017)
Facebook Inc, Menlo Park, CA

Build internal security rules management tools.

Graduate Research Assistant for Prof. Felix Lin (Aug 2014 - May 2016)
Purdue University, ECE Department, West Lafayette, IN

Investigate wearable OS design bottlenecks.


(Nov 2018) Passed Ph.D. Oral Exam! Advanced to candidacy!

(Oct 2018) Will be interning at Pinterest again in summer 2019!

(Feb 2018) Will be interning at Pinterest in summer 2018!

(May 2017) Passed Ph.D. Qualifying Exam

(Sept 2016) Continued as a Ph.D. student at UCLA

(Aug 2014) Started as a Ph.D. student at Purdue


Coming soon!


I'm chinese. 1000000000% chinese. In my spare time, I enjoy cooking, lion dancing, hiking, going out with friends, drinking, playing magic tricks, and sleeping.
Writing research paper on beach is probably the most enjoyable research life one can ever have, and fortunately, you can do it in LA!

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