Effective practices for managing staff performance in higher education: an exploratory study 

Public art as liberatory pedagogy through performance methodologies 

Robustness of gradient methods for data-driven decision making 

Performance management in government: the importance of goal clarity 

TCam: Touch driven communication for virtual moviemaking 

(M)other work: feminist maternal performance art 

Data-driven methods in description-based approaches to audio information processing 

Designing‐in performance: energy simulation feedback for early stage design decision making 

The implementation of data-driven techniques for the synthesis and optimization of colloidal inorganic nanocrystals 

Thermally driven water treatment with membrane distillation: membrane performance, waste heat integration, and cooling analysis 

Towards trustworthy and data-driven social interventions 

Average-case performance analysis and optimization of conditional asynchronous circuits 

The pop show: racial performance and transformation in global arts industries 

Performance evaluation of timestamp-driven databases 

Performance and incentive schemes for peer-to-peer systems 

Performance monitoring and disturbance adaptation for model predictive control 

Transformative occupations: life experiences of performers with disabilities in film and television 

School-wide implementation of the elements of effective classroom instruction: lessons from a high-performing, high-poverty urban school 

High performance web-caching architecture 

Performativity of sites of commemoration and performativity at sites of commemoration 

Data-driven learning for dynamical systems in biology 

Ivory dreams: the music critic as performer 

Optimal applications of social and emotional learning paradigms for improvements in academic performance 

School culture, leadership, professional learning, and teacher practice and beliefs: A case study of schoolwide structures and systems at a high-performing high-poverty school 

AI-driven experimental design for learning of process parameter models for robotic processing applications