Haojian Jin

My research lies at the intersection of human-computer interaction, privacy, and mobile systems, focusing primarily on two contrasting but complementary questions:

  • Privacy: How can we make it easier for users, developers, and auditors to protect data privacy?
  • Sensing: How can we build sensor-based systems to improve our lives?

My research moves the field forward using a dual approach, inspired by the ancient Yin-Yang principle. When designing a new sensing system, I treat privacy as a first-class citizen. I often start with the best privacy practice and develop novel solutions to overcome other challenges. Meanwhile, my sensing research helps me understand the strengths and weaknesses of various privacy-intrusive technologies, allowing me to design privacy protections that balance the interests of users, developers, and auditors.

						I am on the academic job market. 
						[Curriculum Vitae] [Research Statement]  [Teaching Statement]  [DEI Statement]
					
Bio.

I am a final-year Ph.D. student in the Human-Computer Interaction Institute at Carnegie Mellon University, advised by Jason Hong and Swarun Kumar. I also collaborate closely with Yuvraj Agarwal over the years. Before coming to CMU, I had been a research engineer at Yahoo Research for 3 years. At Yahoo, I developed key algorithms in visual search, cryptography, speech recognition and large-scale data mining. I also have run a startup and interned at Microsoft Research Asia, Bosch Research and Chinese Academy of Science before I started my Ph.D..

I received the UbiComp Gaetano Borriello Outstanding Student Award in 2020, which is given to one graduate student per year who has made outstanding research andservice contributions to the field of ubiquitous computing. My research has also been recognized by Research Highlights at Communications of the ACM and GetMobile, and best paper awards at Ubicomp and ACM Computing Reviews.

Featured projects

across human-computer interaction, privacy, and mobile systems.

Lean Privacy Review Lean Privacy Review A fast and cheap method to conduct "Front Page Test" systematically for Data Ethics.

[TOCHI'21] [Video] [Try it]
Modular Privacy Flows (Thesis research) MPF IDE A software pattern that can minimize data collection and offer transparency and control.

[Paper under review]
Software-Defined Cooking A closed-loop system that can sense and control heating at a fine-grained resolution.

[MobiCom'19] [Video]
[Communications of the ACM article]