Liu He（Helium）

Liu He（Helium）

Master @ University of Science and Technology of China

About me

My name is Liu He (何浏).

Following the completion of my master’s degree, I am currently taking a research-focused gap year while continuing my research with Prof. Jiahong Yuan at the University of Science and Technology of China (USTC). I have also been collaborating closely with Dr. Yuanchao Li at the University of Cambridge.

Prior to this, I received my Master’s degree from USTC in June 2025, advised by Prof. Jiahong Yuan (Linguistics/CS) and Prof. Mengxiao Zhu (Computational Social Science). I hold a B.E. in Materials Science & Engineering from the Harbin Institute of Technology (HIT). I gained valuable industry experience as an intern on Baidu’s ERNIE Bot team, focusing on large language models.

My research leverages cross-disciplinary insights from Computational Social Science, Speech & Language Processing, and Explainable AI to tackle complex questions surrounding social phenomena and human behavior.

Research Interests

Computational Social Science: I investigate how different communication modalities (text, audio, video) shape distinct public health narratives and sentiment patterns on social media, using the HPV vaccine as a key case study.

Speech and Language for Clinical Informatics: I develop and apply computational methods to analyze speech patterns, aiming to identify linguistic biomarkers for the early detection of neurodegenerative diseases like Alzheimer’s.

Explainable AI: I apply Explainable AI (XAI) methods to uncover and address performance gaps in clinical diagnostic models, aiming to build more robust, fair, and trustworthy systems for healthcare.

Selected Awards

National Third Prize, The 5th Communication Data Mining Competition 2023

Excellent Academic Scholarship, Graduate School, USTC 2023

Professional Activities

Program Committee Member/Reviewer, ICWSM26

Volunteer, International Communication Association (ICA) Regional Hub at Hefei, China

Publications

Here is my Google Scholar Page.

* denotes equal contribution

2025

  • Zhu, M.*, He, L*., Zhao, H., Su, R., Zhang, L., & Hu, B. (2025). Same Vaccine, Different Voices: A Cross-Modality Analysis of HPV Vaccine Discourse on Social Media. Proceedings of the International AAAI Conference on Web and Social Media, 19(1), 2317-2333. https://doi.org/10.1609/icwsm.v19i1.35936 Link Homepage Poster Slides

    This paper, which forms the core of my Master’s thesis supervised by Prof. Mengxiao Zhu, was accepted as an Oral Presentation (Lightning Talk) in the January 2025 submission cycle as a conditional accept. The review process was unusually rigorous, involving five reviewers and one Senior Program Committee (SPC) member, to whom I submitted a 49-page response addressing all concerns. The SPC meta-review praised the “super strong” review process and how the paper was made “much stronger,” concluding it was “a clear accept.” (Jan 2025 accept rate: 18/187 ≈ 9.8%.)

  • Liu, Y.-L., Li, Y., Feng, R., He, L., Chen, J.-X., Wang, Y.-M., Chen, Y.-A., Peng, Y.-H., Yuan, J.-H., Ling, Z.-H. (2025) Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech. Proc. Interspeech 2025, 544-548. https://doi.org/10.21437/Interspeech.2025-1564

  • Liu He, Yuanchao Li, Rui Feng, XinRan Han, Yin-Long Liu, Yuwei Yang, Zude Zhu and Jiahong Yuan. Exploring Gender Bias in Alzheimer’s Disease Detection: Insights from Mandarin and Greek Speech Perception. The 2025 National Conference on Man-Machine Speech Communication (NCMMSC) (Oral) arXiv Slides

  • Liu He, Rui Feng, XinRan Han, Yin-Long Liu, and Jiahong Yuan. 2025.Beyond Mimicry: Auditing Human Bias to Build Fairer AI for Alzheimer’s Assessment. In Companion Proceedings of the 27th International Conference on Multimodal Interaction (ICMI Companion ’25), October 13–17, 2025, Canberra, ACT, Australia. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3747327.3764903

Preprints & Under Review

  • He, L., Li, Y., Liu, Y.-L., Feng, R., Wang, Y., Chen, J., Wang, Y., & Yuan, J. (2025). Disentangling Acoustic Cues in Alzheimer’s Pathology and Perception: The Roles of Language and Gender. Submitted to ICASSP 2026 (under review).

Projects

Language Biomarkers of Alzheimer’s Disease, from Sociolinguistic, Patholinguistic, and Artificial Intelligence Perspectives. National Social Science Fund Project (23AYY012)

Advisors: Dr. Jiahong Yuan (PI)(Professor, USTC), Dr. Yizhe Wang (Postdoc, USTC), Dr. Yuanchao Li (PHD, The University of Edinburgh), Dr. Yiya Chen (Professor, Leiden University, who co-advised this project during her tenure as a Visiting Professor at USTC (Fall 2024))

This foundational research is dedicated to establishing the core methodology and creating a high-quality speech corpus for studying language biomarkers of Alzheimer’s Disease in Mandarin speakers. The goal is to build a resource analogous to the English DementiaBank, serving as a bedrock for future clinical and computational research.

Collected Data System

  • Experimental Design: Co-developed a comprehensive suite of eight speech tasks grounded in patholinguistics to precisely elicit and capture the linguistic variations of Mandarin speakers with cognitive decline.
  • Infrastructure Development: Built and deployed a robust, web-based data collection platform, establishing a standardized tool for high-quality remote data acquisition.
  • Sociolinguistic Analysis: Investigated how sociolinguistic factors influence the perception of speech from individuals with Alzheimer’s Disease.
  • Collaborated as part of a research team in the ICASSP 2025 Dementia Detection Challenge

  • Explainable AI for Cross-Lingual AD Biomarker Analysis

  • Liu, Y.-L., Li, Y., Feng, R., He, L., Chen, J.-X., Wang, Y.-M., Chen, Y.-A., Peng, Y.-H., Yuan, J.-H., Ling, Z.-H. (2025) Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech. Proc. Interspeech 2025, 544-548. https://doi.org/10.21437/Interspeech.2025-1564

  • Liu He, Yuanchao Li, Rui Feng, XinRan Han, Yin-Long Liu, Yuwei Yang, Zude Zhu and Jiahong Yuan. Exploring Gender Bias in Alzheimer’s Disease Detection: Insights from Mandarin and Greek Speech Perception. The 2025 National Conference on Man-Machine Speech Communication (NCMMSC)(Oral) arXiv Slides

  • Liu He, Rui Feng, XinRan Han, Yin-Long Liu, and Jiahong Yuan. 2025.Beyond Mimicry: Auditing Human Bias to Build Fairer AI for Alzheimer’s Assessment. In Companion Proceedings of the 27th International Conference on Multimodal Interaction (ICMI Companion ’25), October 13–17, 2025, Canberra, ACT, Australia. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3747327.3764903

Preprints & Under Review

  • He, L., Li, Y., Liu, Y.-L., Feng, R., Wang, Y., Chen, J., Wang, Y., & Yuan, J. (2025). Disentangling Acoustic Cues in Alzheimer’s Pathology and Perception: The Roles of Language and Gender. Submitted to ICASSP 2026 (under review).

AI-Powered Cognitive Impairment Screening via Speech and Language Analysis. Applied Research & System Development

In collaboration with iFlytek, BUPT Digital Intelligence (Beidian Shuzhi), and Beijing Tiantan Hospital (Ranked #1 in Neurology in China)

An ongoing research project to develop a novel, non-invasive screening tool for cognitive health, aiming for dual outcomes of academic publication and commercial application. The project leverages a unique, large-scale dataset from ~4,000 individuals, featuring multimodal data including speech, text, performance on linguistic tasks, and lifestyle habits. The primary objective is to build and validate AI models to classify various types of cognitive decline (e.g., Cognitive Decline with Alzheimer’s - CDA, Non-Alzheimer’s - CDN, and Vascular - CDV).

Multimodal Communication of HPV Vaccine on Social Media

Advisors: Dr. Mengxiao Zhu(Professor, USTC) , Dr. Cuihua Shen(Professor, UC Davis), Dr. Zhengdong Mao(Professor, School of Information Science and Technology, USTC)

This was a large-scale research project that performed a cross-modality analysis of HPV vaccine discourse on social media. The study involved collecting and analyzing over 1.5TB of data, including texts, audios, and videos from major platforms like Weibo, Douyin, and Bilibili, spanning a decade from 2010 to 2023. The goal was to understand how the same vaccine was discussed differently across various media formats.

  • Zhu, M.*, He, L*., Zhao, H., Su, R., Zhang, L., & Hu, B. (2025). Same Vaccine, Different Voices: A Cross-Modality Analysis of HPV Vaccine Discourse on Social Media. Proceedings of the International AAAI Conference on Web and Social Media, 19(1), 2317-2333. https://doi.org/10.1609/icwsm.v19i1.35936 Link Homepage Poster Slides

    This paper, which forms the core of my Master’s thesis supervised by Prof. Mengxiao Zhu, was accepted as an Oral Presentation (Lightning Talk) in the January 2025 submission cycle as a conditional accept. The review process was unusually rigorous, involving five reviewers and one Senior Program Committee (SPC) member, to whom I submitted a 49-page response addressing all concerns. The SPC meta-review praised the “super strong” review process and how the paper was made “much stronger,” concluding it was “a clear accept.” (Jan 2025 accept rate: 18/187 ≈ 9.8%.)

* denotes equal contribution

Misinformation Spreading on Social Media

Advisors: Dr. Yongdong Zhang(Professor, School of Information Science and Technology, USTC) (PI) and Dr. Mengxiao Zhu(co-PI)

  • Analyzed 110,000 Weibo posts using LDA topic model
  • Analyzed large-scale social media user behavioral data
  • Composed research reports of over 30,000 words

Industry & Technical Experience

Data Science Intern, ERNIE Bot, Baidu | Autumn 2023

Joined Baidu’s ERNIE Bot team during the early wave of China’s LLM development, working on model evaluation, fine-tuning, and dialogue optimization for ERNIE 3.5 and 4.0.

Model Evaluation & Improvement

  • Developed comprehensive evaluation frameworks based on real user feedback
  • Created benchmark datasets and assessment criteria for measuring model quality
  • Conducted both automated metrics and human evaluations
  • Fine-tuned models using supervised learning to improve performance

AI Agent Development

  • Built domain-specific AI agents using Few-Shot Supervised Fine-Tuning (SFT)
  • Covered diverse scenarios: character roleplay, gaming assistants, workplace productivity tools, and educational tutors
  • Contributed to productionizing AI agents for real-world deployment

Dialogue System Engineering

  • Designed query prediction and recommendation systems for multi-turn conversations
  • Implemented token compression techniques for efficient processing
  • Integrated user behavior analysis with co-occurrence mechanisms
  • Improved user engagement through context-aware query suggestions

This experience deepened my understanding of production AI systems and directly informs my current research applying LLMs to social science and clinical applications.

ChatPaper (RAG-based Academic Tool) Mar. 2023 – Jul. 2023

Founding Team Member | 100,000+ users

  • One of the earliest RAG tool, focused on academic efficiency, 100k users at the time.

USTC360 (Non-Profit Career Platform) March 2022 – Present

Co-founder | 2,000+ members

  • Co-founded a non-profit platform connecting over 2,000 USTC students and alumni, facilitating career development by bridging the gap between academia and industry.

  • Developed a Python web scraper to automatically aggregate job opportunities, providing a core technical solution for the community’s information-sharing needs.

Teaching & Mentorship

Beyond my own research, I am passionate about teaching and mentorship. I find deep satisfaction in helping students connect complex theories to real-world applications and find their own academic paths.

Teaching Assistantship

  • Teaching Assistant, Speech Analysis, University of Science and Technology of China, Fall 2024.
  • Teaching Assistant, Health Communication, University of Science and Technology of China, Fall 2022.

Community & Peer Mentorship

Co-founder & Peer Mentor, USTC360 (2022–Present)

  • Co-founded this volunteer-run, non-profit platform and personally maintained its core operations (including weekly JD posting) for over two years, growing the community to 2,000+ members.
  • Offered informal 1-on-1 guidance to many students, helping them discover their underlying passions and navigate the pivot from traditional science (e.g., Physics, Chemistry) into AI and related internship opportunities.

A Note on Peer Mentorship

  • The Context: I believe deeply in sharing my own cross-disciplinary journey from Engineering to Computational Social Science with students who are standing at a similar crossroads.

  • The Action: I met Buyu Deng (SGY ‘23) on the tennis court during his first week at USTC. I encouraged him to explore his passion for modeling beyond his traditional physics track. Drawing on my own research, I introduced him to computational and AI-driven approaches for scientific question, helping him see how data-driven methods could deepen our understanding of natural systems. Together, we identified the Geophysics major as a strong fit for his interests, and I connected him with a computational research group much earlier than is typical, which he then contacted and joined on his own initiative.

  • The Outcome: He made the switch and has absolutely thrived. I’ve been thrilled to see him not only become a top-ranked undergraduate researcher, but also earn many Scholarships and now aim for top-tier PhD programs and summer research.

Miscellaneous

I go by Helium because it sounds like my Chinese name 何浏 (Hé Liú). During my undergraduate studies, I took many chemistry and physics courses and became very familiar with helium.

Outside of research, I enjoy playing tennis 🎾 and swimming 🏊. I’ve been doing both regularly for the past three years.

I really enjoy indie music, and lately my favorite album is Illinois by Sufjan Stevens.