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Yijiang Pang

Yijiang Pang

PhD Student

Talent
Ann ArborMember since September 12, 2026
Hyperparameter optimizationSequence modelingZeroth-order optimizationOptunaGit
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Hyperparameter optimizationSequence modelingZeroth-order optimizationOptunaGit

Experience

Visiting Research Student at University of Michigan, ILLIDAN Lab (2024-01 – Present)

  • Clinical ML. Led two first-author clinical AI studies developing a cross-cohort surrogate-biomarker framework that harmonized shared clinical variables across NACC and I-CONECT and linked conversational language with multi-modality biomarkers.
  • Built the end-to-end modeling pipeline, including data preprocessing and harmonization, training and evaluating established machine-learning models, and Optuna-based hyperparameter optimization.
  • Statistical validation through feature-importance, correlation, and sensitivity analyses.
  • Foundations of LLMs and sequence modeling.

Developing

Fourier-based sequence-modeling blocks as computationally efficient alternatives to attention for long-context and irregularly timed sequences, with a focus on multiscale temporal dependence, causal modeling, and scalable architectures; benchmarking the designs on synthetic sequences and EHR next-event prediction.

Graduate Research Assistant at Michigan State University (2021-01 – Present)

  • Adam theory. Established the first convergence guarantees for plain vector-formulated Adam under heavy-tailed stochastic noise through a generalized discounted-to-nonconvex conversion and discounted-regret analysis.
  • Zeroth-order optimization. Proposed forward-pass-only methods for deep-model optimization; proved optimal query complexity and achieved substantial improvements across diverse vision and language tasks.
  • Clinical ML. Led the full lifecycle of a first-author longitudinal study predicting progression from normal cognition to mild cognitive impairment/Alzheimer's disease, including raw-data preprocessing, cohort construction, feature selection, model development, and rigorous evaluation; Mentored and technically led an undergraduate researcher through three projects on subject harmonization, distributed batch-effect correction, and bilingual speech-based cognitive assessment, resulting in publications at PSB, KDD, and Interspeech.

Education

Ph.D. in Computer Science – Michigan State University (2021-01 – 2027-05)

M.T. in Technology – Kent State University (2019-01 – 2021-12)

B.E. in Mechatronics – University of Electronic Science and Technology of China (2009-01 – 2013-12)

Skills

PhD Student

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