Perciano is a Scientist in the AI & Learning Systems group and the Computational Biosciences group, at Lawrence Berkeley National Laboratory. She conducts research in the areas of machine learning, image analysis, quantum algorithms and machine learning, probabilistic graphical models, and high-performance computing motivated by the incredible challenges around scientific data generated by computational models, simulations, and experiments. Her research focuses on mathematical foundations for new methods, on the implementation of scalable methods, and on platform-portability. Her goal is to develop powerful, mathematically-grounded, scalable algorithms that meet the requirements needed to analyze current and future scientific datasets acquired in user data facilities. She has built a diverse collaboration network throughout the years in fields such as materials science, chemistry, biosciences, geosciences, among others. She is an ACM, APS, and IEEE member.

Area of Interest

• Artificial Intelligence and Image Processing
• Image Processing
• Knowledge Representation and Machine Learning
• Applied Mathematics
• Applied Statistics
• Functional Materials
• Time-Series Analysis
• Stochastic Analysis and Modelling
• Quantum Information, Computation and Communication

Education

• PhD| University of Sao Paulo, Sao Paulo, Brazil
• MS| Federal University of São Carlos, São Carlos, Brazil
• BS| Federal University of Alagoas, Maceió, Brazil