I work on fundamental artificial intelligence and machine learning research problems motivated from important science and engineering applications. Some examples include:
AI-driven Adaptive Experiment Design with applications to engineering and scientific domains
Sequential Decision-making under Uncertainty problems motivated by real-world applications including agriculture and optimization of cyber-physical systems such as smart grid and smart health
Robust Machine learning and Decision-making for high-stakes applications
Machine Learning to improve Electronic Design Automation for designing high-performance, energy-efficient, and reliable hardware for large-scale data analysis applications
Optimized Computer Architectures for Big Data Computing using Emerging Technologies (e.g., Through-Silicon-Via / Monolithic 3D integration, Heterogeneous systems, and Processing-in-Memory cores)
Machine Learning for Sustainable Computing and Computational Sustainability

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