Penalized portfolio optimization 

Optimizing penalized and constrained loss functions with applications to large-scale internet media selection 

Optimization strategies for robustness and fairness 

Engineering design optimization 

Artificial Decision Intelligence: integrating deep learning and combinatorial optimization 

Robust feature selection with penalized regression in imbalanced high dimensional data 

Iterative path integral stochastic optimal control: theory and applications to motor control 

Analysis, design, and optimization of large-scale networks of dynamical systems 

Difference-of-convex learning: optimization with non-convex sparsity functions 

Statistical analysis of high-throughput genomic data 

Scalable optimization for trustworthy AI: robust and fair machine learning 

I. Asynchronous optimization over weakly coupled renewal systems 

Landscape analysis and algorithms for large scale non-convex optimization 

Modern nonconvex optimization: parametric extensions and stochastic programming 

Regularized structural equation modeling 

Imposing classical symmetries on quantum operators with applications to optimization 

Differentially private and fair optimization for machine learning: tight error bounds and efficient algorithms 

Environmentally responsive buildings: multi-objective optimization workflow for daylight and thermal quality 

The next generation of power-system operations: modeling and optimization innovations to mitigate renewable uncertainty 

Novel theoretical characterization and optimization of experimental efficiency for diffusion MRI 

Dynamic routing and rate control in stochastic network optimization: from theory to practice 

Novel optimization tools for structured signals recovery: channels estimation and compressible signal recovery 

Learning objective functions for autonomous motion generation 

Model based design of porous and patterned surfaces for passive turbulence control 

Incorporating prior knowledge into regularized regression