🎓 Education
Huijia Zheng is expected to earn her M.S. in Cognitive Psychology in Context from Vanderbilt University in May 2025, with an outstanding cumulative GPA of 3.875 and recognition through the Scholastic Achievement Scholarship. She holds dual B.S. degrees in Psychology and Cognitive Science (Computation and Cognition Track) from the University of Michigan – Ann Arbor, graduating in December 2022 with a GPA of 3.849. During her undergraduate studies, she also pursued a minor in Computer Science and received distinctions such as University Honors and the James B. Angell Scholar award.
💼 Experience
Huijia Zheng has an impressive research portfolio, currently contributing as a graduate researcher in Vanderbilt University’s Brain Development Lab and Levin Lab. Her work involves investigating white matter tracts in language processing using Diffusion Tensor Imaging (DTI) and exploring attention mechanisms through eye-tracking studies. She has also collaborated with Beijing Normal University’s Luo Lab, where she led multiple research projects involving personality assessment, empathy testing, and cognitive performance evaluation. Additionally, her past research experience includes working in the Multisensory Perception Lab and Contact, Cognition and Change Lab at the University of Michigan, focusing on audiovisual speech perception, neural imaging, and multilingualism. Beyond academia, she gained hands-on industry experience through internships at Shangtang Technology and Beijing National Aquatics Centre, where she worked on AI-driven digital human interaction and cultural venue management.
🏆 Awards and Honors
Huijia Zheng’s academic excellence and research contributions have been recognized through multiple accolades. She has been awarded the Scholastic Achievement Scholarship at Vanderbilt University and has consistently maintained a high academic standing, earning University Honors and the prestigious James B. Angell Scholar distinction during her undergraduate studies. Her contributions to cognitive science research have also led to multiple publications in esteemed journals.
🔬 Research Focus
Huijia’s research primarily revolves around cognitive neuroscience, psycholinguistics, and computational cognitive science. She investigates language processing mechanisms, attention allocation in human perception, and cognitive-behavioral assessments using advanced methodologies such as MRI, EEG, and AI-driven analysis. Her work also extends to personality assessment, empathy evaluation, and multilingual communication studies. By integrating computational tools into psychological research, she aims to advance understanding in human cognition and mental health.
📝 Conclusion
Huijia Zheng is a rising scholar in cognitive psychology, known for her multidisciplinary expertise and strong research contributions. With a keen interest in bridging psychology, neuroscience, and computational methods, she is committed to advancing research in cognitive science and its applications in real-world scenarios. Her work has not only contributed to academic knowledge but also holds potential implications for AI-driven assessments, mental health, and human-computer interaction.
📚 Publications
The role of dorsal and ventral white matter tracts in phonological and semantic processing of language in pre-readers and beginning readers. [Manuscript in preparation]. Peabody College of Education and Human Development, Vanderbilt University.
An investigation of the matching mode of a forced-choice personality test and its faking-resistance mechanism based on eye-movement data. [Manuscript in preparation]. Department of Psychology, Beijing Normal University.
Empathy Through the Lens: Development and Validation of a Video-Based Empathy Test. [Manuscript submitted for publication]. Department of Psychology, Beijing Normal University.
Information-Reduction Ability Assessment in the Context of Complex Problem-Solving. Journal of Intelligence, 13(3), 28. DOI: 10.3390/jintelligence13030028
Understanding emotional influences on sustained attention: a study using virtual reality and neurophysiological monitoring. Frontiers in Human Neuroscience, 18, 1467403. DOI: 10.3389/fnhum.2024.1467403
Depressive Emotion Recognition Based on Behavioral Data. Lecture Notes in Computer Science, 11354. Springer, Cham. DOI: 10.1007/978-3-030-15127-0_26