About Me
I am a PhD student in Computer Science at Rensselaer Polytechnic Institute advised by Professor Jianxi Gao. I earned my B.S. in Computer Science and Mathematics from the University of Toronto, where I had the privilege of being mentored by Professor Ishtiaque Ahmed.
My research focuses on the modeling and inference of complex systems, spanning both networked dynamical systems and large language models (LLMs). I develop mathematical and computational frameworks, drawing on dynamical systems, probabilistic modeling, and optimization, to address problems such as system parameter estimation, neural network training dynamics, and the theoretical understanding of LLM behaviors like in-context learning.
Publications and pre-prints
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EMO: Epigraph Based Multilevel Optimization For Enhancing Chain Of Thought Reasoning Capabilities
Songtao Lu, Yanna Ding, Lior Horesh, Jianxi Gao, Malik Magdon-Ismail
Accepted by IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2025 -
Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation
Yanna Ding, Zijie Huang, Xiao Shou, Yihang Guo, Yizhou Sun, Jianxi Gao
Accepted by AAAI Conference on Artificial Intelligence (AAAI) 2025
[PDF] -
Less is More: Efficient Weight “Farcasting” with 1-Layer Neural Network
Xiao Shou, Debarun Bhattacharjya, Yanna Ding, Chen Zhao, Rui Li, Jianxi Gao Accepted by International Conference on Database Systems for Advanced Applications (DASFAA) 2025 -
Inferring from Logits: Exploring Best Practices for Decoding-Free Generative Candidate Selection
Mingyu Derek Ma, Yanna Ding, Zijie Huang, Jianxi Gao, Yizhou Sun, Wei Wang
Accepted by the 4th Efficient Natural Language and Speech Processing workshop (NeurIPS ENLSP) 2024 [PDE] -
Predicting Time Series of Networked Dynamical Systems without Knowing Topology
Yanna Ding, Zijie Huang, Malik Magdon-Ismail, Jianxi Gao
Preprint
[PDF] -
Efficient parameter inference in networked dynamical systems via steady states: A surrogate objective function approach integrating mean-field and nonlinear least squares
Yanna Ding, Jianxi Gao, Malik Magdon-Ismail
Published in Phys. Rev. E 109, 034301 (2024)
[PDF] [DOI] -
Learning Network Dynamics from Noisy Steady States
Yanna Ding, Jianxi Gao, Malik Magdon-Ismail
Published in IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) 2023
[DOI]
Earlier Projects
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University of Toronto Supervisor: Prof. Priyank Chandra Summer 2020
During research analysis, such as categorizing social media posts, different researchers often have to label a shared dataset. It is essential to determine inter-coder reliability in order to make the research results more convincing in this case. This project implements a standalone application to calculate different inter-rater reliability metrics (e.g., Scott’s Pi).
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COVID-19 Related Stigma On Social Media
University of Toronto Supervisor: Prof. Syed Ishtiaque Ahmed Summer 2020 - Present
The COVID-19 pandemic has led to increased stigma, prejudice, and hate against people of East Asian descent living in North America and around the world. In particular, those individuals perceived to be from China or to a Chinese-heritage are frequently targeted on social media platforms such as Twitter, Facebook, and Instagram. This project studies the stigma, fear, and misinformation on social media related to COVID-19. It aims to increase public awareness of the harm and impact of stigma and reduce the spread of stigma. During the project, I collected and maintained a dataset of 650+ million tweets, including 220k potentially stigmatizing tweets with geo-location data; visualized and analyzed various statistical metrics on the previous data, including distribution of sentiment (labeled by the BERT model) around the globe.
Awards
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2020, Mitacs Research Training Award, University of Toronto
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2020, Department of Computer Science Undergraduate Research Award, University of Toronto
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2020, The Chancellor’s Scholarship – St. Hilda’s , University of Toronto