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Zehua Zeng

             

Bio

I am a Software Research Engineer at Intel, where I build full-stack applications and interactive visualization tools for large-scale semiconductor design and manufacturing. My work spans software engineering, data visualization, machine learning, and scalable data systems, with a focus on transforming complex engineering data into intuitive tools that enable real-time analysis and informed decision-making.

I received my Ph.D. in Computer Science at the University of Maryland, College Park, where I worked with Prof. Leilani Battle in the BAttle-Data Lab and UW Interactive Data Lab. My research focused on visualization recommendation systems, interactive visual analytics, and human-centered data analysis. I also received my M.S. in Computer Science from the University of Maryland and my B.S. in Telecommunication Engineering from Beijing University of Posts and Telecommunications.

I enjoy building software that bridges research and real-world applications, from scalable backend systems and APIs to modern web applications and interactive data experiences. Throughout my career, I’ve developed end-to-end solutions that combine intuitive user interfaces with robust data processing and analytics, helping engineers make faster, more informed decisions.

I’m always interested in discussing full-time, part-time, contract, freelance, and project-based software engineering opportunities. If you think my background could be a good fit, feel free to reach out via LinkedIn or email.

Experience

Software Research Engineer/Scientist, Intel Corporation, Chandler, AZ, USA
Jan 2023 - Present
Graduate Research Assistant, University of Maryland, College Park, MD, USA
May 2016 - Dec 2022
Graduate Teaching Assistant, University of Maryland, College Park, MD, USA
Aug 2015 - Dec 2019
Research and Development Engineering Intern, Baidu, Inc. Beijing, China
Jan 2015 - Jul 2015

Awards

VGTC Visualization Dissertation Award Honorable Mention
2024
Best Short Paper Honorable Mention Award
2023 IEEE VIS
Best Paper Honorable Mention Award
2021 IEEE VIS
Dean’s Fellowship
2020

Publications

Balancing Speed and Accuracy for Robust Analog-Mixed Signal Circuit Design using Closed-Loop Reinforcement Learning with Ensemble Neural Network Surrogates
Zuwei Guo, Jie Fu, Sumukh Bhanushali, Zehua Zeng, Imon Banerjee, Arindam Sanyal
IEEE ISCAS, 2026

A Systematic Review of Visualization Recommendation Systems: Goals, Strategies, Interfaces, and Evaluations
Zehua Zeng, Leilani Battle
Foundations and Trends in Databases, 2024

Too Many Cooks: Exploring How Graphical Perception Studies Influence Visualization Recommendations in Draco
Zehua Zeng, Junran Yang, Dominik Moritz, Jeffrey Heer, Leilani Battle
IEEE VIS, 2023

Draco 2: An Extensible Platform to Model Visualization Design
Junran Yang, Péter Ferenc Gyarmati, Zehua Zeng, Dominik Moritz
IEEE VIS 2023 – Short Papers (Best Paper Honorable Mention)

Using Graphical Perception in Visualization Recommendation
Zehua Zeng, Leilani Battle
ACM Interactions, 2023

A Review and Collation of Graphical Perception Knowledge for Visualization Recommendation
Zehua Zeng, Leilani Battle
CHI, 2023

A Multi-Faceted Approach for Evaluating Visualization Recommendation Algorithms
Zehua Zeng
Ph.D. Dissertation, 2022

An Evaluation-Focused Framework for Visualization Recommendation Algorithms
Zehua Zeng, Phoebe Moh, Fan Du, Jane Hoffswell, Tak Yeon Lee, Sana Malik, Eunyee Koh, Leilani Battle
IEEE VIS, 2021 (Best Paper Honorable Mention)

Supporting Team-First Visual Analytics through Group Activity Representations
Sriram Karthik Badam, Zehua Zeng, Emily Wall, Alex Endert, Niklas Elmqvist
Graphics Interface (GI), 2017

Service