Modern Approaches to Crystallization and Particle Engineering

Chemical engineering Ph.D. focused on organic semiconductors/electronics, and adsorption governed separations. Marko's skill set spans synthetic organic chemistry, theoretical applied mathematics (partial differential equations) involving heat, mass, and momentum transfer, organic semiconductor photophysics, and water purification. Currently working on chemical process development at Bristol Myers Squibb. Marko received his Ph.D. in Chemical Engineering from Princeton University, and Bachelors in Chemical Engineering from the University of Illinois Urbana-Champaign.

Fernando Arrais Romero Dias Lima is a chemical engineer and researcher whose work centers on the modeling, monitoring, and control of crystallization processes, with a strong emphasis on combining process systems engineering and machine learning. He holds two PhD degrees, one in Chemical Engineering from the Norwegian University of Science and Technology (NTNU) and another in Engineering of Chemical and Biochemical Processes from the Federal University of Rio de Janeiro (UFRJ). His research focuses on improving crystallization processes through model-based and data-driven approaches, including soft sensing, symbolic regression, neural networks, universal differential equations, and advanced control strategies. His research has addressed both the fundamental and applied sides of crystallization, spanning mechanistic and empirical modeling, uncertainty-aware prediction, nonlinear model predictive control, reinforcement learning, and experimental closed-loop control of batch systems such as paracetamol crystallization. He has also developed monitoring tools using spectroscopic and particle measurement data to support real-time control and optimization. Across his publications and research appointments, Fernando has built a profile focused on trustworthy and interpretable intelligent methods for crystallization engineering, aiming to bridge rigorous process understanding with modern machine learning tools for industrially relevant applications.