Rutgers logo
Department of Chemical and Biochemical Engineering
Rutgers logo
Department of Chemical and Biochemical Engineering
Abstract background of technology, science and cloud computer.3d illustration.Wallpaper of binary code and binary language concept pattern and big data structure.

Computing and Data Science


CBE researchers apply computational methods to problems across all length scales, including quantum mechanical modeling of catalytic reactions, bio-inspired and data-driven materials design, interfacial behavior of nanomaterials, and design and optimization of complex systems. Rutgers provides a rich environment for computational research via cross-disciplinary collaborations and high performance computing resources.


Ioannis (Yannis) Androulakis, Fuat Celik, Gregory Dignon, Meenakshi Dutt, Benjamin Glasser, Ashley Guo, Diane Hildebrandt, Alexander Neimark, Rohit Ramachandran, Silvina Tomassone

Research Topics

·    Multiscale methods
·    Enhanced sampling techniques
·    Computational chemistry
·    Statistical mechanics
·    Discrete element methods
·    Deep learning
·    Machine learning
·    Data-driven methods
·    Systems engineering

Research Clusters

Multiscale Simulation and Modeling

Faculty: Dignon, Dutt, Glasser, Guo, Neimark, Tomassone

We apply molecular modeling and statistical mechanics to develop solutions to problems in energy, drug delivery, and catalysis, as well as other biomedical, environmental, and pharmaceutical applications.

Molecular Design

Faculty: Dignon, Dutt, Guo

The discovery and design of materials is greatly accelerated by information gained from computational studies at the molecular level, along with high-throughput screening techniques, enhanced sampling, deep learning, and data-driven methods. We use these to explore new materials to meet therapeutic, electronic, environmental, and biopharmaceutical needs.

Reaction Engineering

Faculty: Celik, Hildebrandt, Neimark

We study reaction processes at both the molecular and the systems ends of the spectrum, using quantum mechanical modeling and molecular simulation to understand and design efficient catalytic materials, and reactor modeling to define optimal operating conditions for CO2 reduction in reaction systems.

Process Systems Engineering

Faculty: Androulakis, Hildebrandt, Ramachandran

We use computational modeling and simulation tools to design optimal chemical and pharmaceutical process systems for clean and efficient operation, and to elucidate principles underlying complex biological systems.