Jiali Liu

Jiali Liu

Ph.D. Candidate in Human-Computer Interaction
jiali.Liu@telecom-paris.fr
Diva Group
LTCI, Télécom Paris, IP Paris
46 Rue Barraut, 75013, Paris, France

Research

I'm currently doing my Ph.D in the DIVA Group, under the supervision of Prof. James R. EAGAN, at Télécom Paris, IP Paris. My research focuses on understanding how people make sense of data in their real analytic practices, with the goal to design beeter analytic tools and environments that can suit their contextual needs.

More generally, I am interested in human-computer interaction (HCI), sensemaking, information visualization, end-user programming, and tool design. Before my Ph.D., I obtained my engineering degree at Télécom Paris, majoy in Human-Computer Interaction and 3D graphics.

Publication

Understanding the Role of Alternatives in Data Analysis Practices.

Jiali Liu, Nadia Boukhelifa, and James Eagan,

IEEE Transactions on Visualization and Computer Graphics, IEEE (2019)

PDF IEEE Video

Understanding Alternatives in Data Analysis Activities.

Jiali Liu, Nadia Boukhelifa, and James Eagan,

Extended Abstracts of the 2019 CHI Conference, 2019. (workshop)

PDF HAL

Making Sense of Data Workers' Sense Making Practices.

Jiali Liu, Nadia Boukhelifa, and James Eagan,

Extended Abstracts of the 2018 CHI Conference, 2018. (workshop)

PDF HAL

Teaching

News

Oct. 20-25th, 2019
I will be presenting my vast paper on alternatives at VIS 2019 conference in Vancouver, Canada.
July 1-4th, 2019
I atteneded the RJC Young Researchers in Human-Computer Interaction Meeting, in Toulouse, France.
Aug. 27-31th, 2018
I participanted in the 4th ACM SIGCHI Summer School on Computational Interaction, at University of Cambridge, UK.
Apr. 21-26th, 2018
I atteneded the CHI 2018 conference in Montreal, Canada.

/* background image -- Florence Nightingale's 'Cox Comb' or 'Rose' diagrams, which helped save lives during the Crimean War and continued to spark revolutions in health care and hygiene in hospitals worldwide.

This is a great reminder for the value and power of data visualizations. */