Emily Jia

933 citations
4 papers · 399 indexed · 1 hit paper · h-index 2
Topics
Adversarial Robustness in Machine Learning (2 papers)Explainable Artificial Intelligence (XAI) (2 papers)CCD and CMOS Imaging Sensors (1 paper)
Journals
arXiv (Cornell University)Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Partner nations
United StatesCanadaChina

In The Last Decade

Emily Jia

4 papers receiving 386 citations

Hit Papers

Fooling LIME and SHAP20202026202220242020100200300

Peers

Emily Jia
Comparison fields: 5 of 99
  • Artificial Intelligence 279
  • Health Informatics 45
  • Safety Research 39
  • Computer Networks and Communications 20
  • Computer Vision and Pattern Recognition 20
Replace Sophie Hilgard with:
Sophie Hilgard United States
Dylan Slack United States
Giulia Vilone Ireland
Jörg Schlötterer Germany
Alan Perotti Italy
Ludovik Çoba Italy
Huiqi Deng China
Milad Moradi Austria
Adrien Bibal Belgium
Raha Moraffah United States
Emily Jia relative to Sophie Hilgard United States Sophie Hilgard's profile →
Citations per field
00.5×1.5×
Sophie Hilgard · 1×
Citations per year

Countries citing papers authored by Emily Jia

Since Specialization
Citations

This map shows the geographic impact of Emily Jia's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Emily Jia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emily Jia more than expected).

Fields of papers citing papers by Emily Jia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emily Jia. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Emily Jia. The network helps show where Emily Jia may publish in the future.

Co-authorship network of co-authors of Emily Jia

This figure shows the co-authorship network connecting the top 25 collaborators of Emily Jia. A scholar is included among the top collaborators of Emily Jia based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Emily Jia. Emily Jia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

4 of 4 papers shown
#WorkIndexed citations
1 1
2 1
3
Fooling LIME and SHAPbreakdown →
386
4
How can we fool LIME and SHAP? Adversarial Attacks on Post hoc Explanation Methods.
11

About Emily Jia

Emily Jia is a scholar working on Health Informatics, Computer Graphics and Computer-Aided Design and Biophysics, having authored 4 papers that have together received 399 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (2 papers), Explainable Artificial Intelligence (XAI) (2 papers) and CCD and CMOS Imaging Sensors (1 paper). The work is most often cited by research in Health Informatics (45 citations), Artificial Intelligence (279 citations) and Safety Research (39 citations). Emily Jia has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Sophie Hilgard, Himabindu Lakkaraju, Dylan Slack, Sameer Singh, Baorui Ma, Yu-Shen Liu, Helge Rhodin, Wenyuan Zhang, Junsheng Zhou and Sidney Fels. Their work appears in journals such as arXiv (Cornell University) and Proceedings of the AAAI/ACM Conference on AI Ethics and Society.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Rankless by CCL
2026