Zimeng Lyu
Ph.D. Candidate
Ph.D. Candidate in Computer Science specializing in advanced ML, neural architecture search, and real-time adaptation. Delivered $7.3M in power plant cost savings and beat market benchmarks with evolved RNN strategies. Proficient in C++, Python, PyTorch, Docker, Spark, and distributed computing for large-scale AI solutions. Additionally, I serve as an instructor for a master’s-level Software Engineering for Data Science core course, designing four real-world, large-scale data pipeline applications.
Thesis Advisor: Dr. Travis Desell.
Research Areas
Time Series Forecasting
Online and Offline Time Series Forecasting, Stock Return Predictions
Neural Architecture Search
NeuroEvolution, Recurrent Neural Networks
Minimally Supervised Learning
Self Organizing Maps, Topological Projections
Latest News
EvoAPPs Paper Acceptance
WCCI IJCNN acceptance
Applied Soft Computing Journal Paper Accepted
Online Evolutionary Neural Architecture Search for Multivariate Non-Stationary Time Series Forecasting
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