Energy Control and Optimization (ECO) Laboratory

Research Areas

Energy Control and Optimization (ECO) Lab is the research lab for multi-scale modeling in the Mechanical Engineering Department at the Stevens Institute of Technology, directed by Dr. Shima Hajimirza. The research goal of the ECO Lab is to find smarter engineering solutions for energy technology demands and multi-scale dynamic systems using computational modeling and applied mathematics.


Shima Hajimirza, PhD

Active Projects

1. Radiation Heat Transfer

We thrive to improve the fundamental understanding of thermal transport especially in the form of radiation heat transfer in different materials, complex media and at multiple scales. Fundamental modeling of nano-scale radiation is of particular interest to the research of ECO Lab, which pertains to many practical applications.

2. Micro-Nano Material Design

Material structures of small sizes can improve response of energy absorbing/converting/transforming systems to physical stimuli such as radiation, heat, pressure, vibration, etc. Studying the physical and chemical properties of these materials using first principle numerical simulations is a focus of the ECO Lab. In particular, nano-size textured materials are of interest in thin film photovoltaic technology. We strive to understand the relationship between photo-electric characteristics of textured semiconductor and dielectric nano-structures and their geometry and composition through state-of-the art theoretical and numerical techniques.

3. Machine Learning for Inverse Design

Many design problems in modern engineering and operations research can be formulated as an inverse problem: Given the target specifications, identify the initial conditions or design parameters that result in the most desired performance. This includes a vast domain of problems in energy systems design, biomedical imaging, inference and diagnostics, remote sensing, optimal control, etc. Newly discovered tools in machine learning and statistics such as Deep Learning, Bayesian and Meta-model Optimization, non-parametric regression techniques, etc. can help improve or expedite the solutions to many such problems by learning from data and past experience. Part of the research at ECO Lab is dedicated to identifying problems in energy technologies, material design and bio-engineering that have not yet benefited from such modern computational approaches.

4. Control and Optimization

Our group is also involved in developing modern control algorithms and optimal policies for dynamic and hybrid energy systems, with a special interest in renewable energy systems and smart grids.


Please visit Dr. Hajimirza’s research webpage for publications.