Building multimodal AI systems for financial reasoning, market understanding, and reliable decision support.

Contact Me sden118@aucklanduni.ac.nz

I am a Ph.D. student in Statistics at the University of Auckland, supervised by Associate Professor Ciprian Doru Giurcaneanu. My research focuses on the application of AI in the financial domain, with a particular emphasis on multimodal financial reasoning and stock price prediction.

Prior to my doctoral studies, I earned a Bachelor's degree in Finance from Anhui University in China and a Master of Science from the University of Leeds in Financial Mathematics. I am interested in how language, numerical data, and external evidence can be combined to make financial AI systems more robust and interpretable.

ICAIF 2025 Best Paper Award for FinMR: A Knowledge-Intensive Multimodal Benchmark for Advanced Financial Reasoning.

Research Directions

My work sits at the intersection of artificial intelligence, statistics, and finance. I focus on building benchmarks, reasoning methods, and evaluation frameworks for multimodal financial AI.

Multimodal Financial Reasoning

Designing benchmarks and methods for financial reasoning across text, numerical tables, market signals, and other evidence.

Evidence Acquisition

Studying how AI systems can gather evidence step by step, reflect on errors, and improve reasoning reliability.

AI for Finance

Developing and evaluating artificial intelligence methods for financial reasoning, forecasting, decision support, and other complex financial applications.

Financial Forecasting

Applying machine learning and multimodal information to stock price prediction and market understanding.

Education

  • 2024-now Ph.D. in Statistics
    University of Auckland, New Zealand
  • 2018-2019 Master in Financial Mathematics
    University of Leeds, United Kingdom
  • 2013-2017 BSc in Finance
    Anhui University, China

Visiting

  • 2025.10-2026.06 Visiting Student in CCDS
    Nanyang Technological University, Singapore

News

Highlight ยท Nov 2025

FinMR received the ICAIF 2025 Best Paper Award

Awarded at the 6th ACM International Conference on AI in Finance in Singapore.

  • 2026: CLER: Improving Multimodal Financial Reasoning by Cross-MLLM Error Reflection appears in AAAI as an oral presentation.
  • 2026: Multi-Agent SEA accepted to Information Fusion.
  • 2025.10: Started a visiting student position in CCDS at Nanyang Technological University.
  • 2025: Bridging Cognitive Divide received the BIBM 2025 Best Paper Award.

Selected Publications

Google Scholar
ICAIF 2025 FinMR
Best Paper Award

FinMR: A Knowledge-Intensive Multimodal Benchmark for Advanced Financial Reasoning

S. Deng, H. Peng, J. Xu, R. Mao, C. D. Giurcaneanu, J. Liu.

Proceedings of ACM ICAIF, 168-176, 2025.

AAAI 2026 CLER
Oral Presentation

CLER: Improving Multimodal Financial Reasoning by Cross-MLLM Error Reflection

S. Deng, Z. Wang, R. Mao, C. D. Giurcaneanu, J. Liu.

Proceedings of AAAI, 2026.

WWW 2026 Ethereum

Multi-source Multi-level Multi-token Ethereum Dataset and Benchmark Platform

H. Li, M. Zhang, M. Li, J. Li, Z. Zhang, J. Yang, S. Deng, J. Liu.

Proceedings of the ACM Web Conference, 8517-8520, 2026.

Information Fusion SEA

Multi-Agent SEA: Step-wise Evidence Acquisition for Multimodal Financial Reasoning

S. Deng, Z. Huang, K. Du, R. Mao, J. Liu, C. D. Giurcaneanu, E. Cambria.

Information Fusion, 104550, 2026.

IEEE TAC Diabetes

Personalized Diabetes Care: Discovering Diabetes Mindset Disparities From Metaphorical Cognition

W. Zhao, R. Mao, S. Deng, E. Cambria.

IEEE Transactions on Affective Computing, 2026.

BIBM 2025 Metaphor
Best Paper Award

Bridging Cognitive Divide: Uncovering Cognitive Disparities among Diabetic Patients via Metaphor

W. Zhao, R. Mao, S. Deng, E. Cambria.

IEEE International Conference on Bioinformatics and Biomedicine, 2025.

Awards

  • ICAIF 2025 Best Paper Award for FinMR.
  • BIBM 2025 Best Paper Award for Bridging Cognitive Divide.

Curriculum Vitae

A downloadable PDF version of my curriculum vitae is available here.

Download CV