Christos Maravelias

Professor

Princeton University

United States

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Christos Maravelias is a Professor at Princeton University in the United States. His research focuses on optimization frameworks for chemical and energy systems, varying from multi-scale variability to membrane network synthesis for metal recovery. He has published extensively on topics including deterministic global optimization, energy transition planning, and the optimization of biofuels network design. His recent work also explores innovative approaches to achieving sustainability through advanced chemical production scheduling and electrification in process industries.

Christos Maravelias

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Articles (30)

Drop-in fuel production from food waste: system level optimization and analysis

Transforming the Process Industries through Electrification: Challenges and Opportunities

A general optimization framework for designing chemical & energy systems subject to multi-scale temporal variability

Membrane network synthesis for metal recovery: An optimization-based framework

Constructing Optimal Piecewise Quadratic Approximations for Enhancing Deterministic Global Optimization

A control-inspired approach for energy transition planning under uncertainty

Code and Data Repository for Constructing Optimal Piecewise Quadratic Approximations for Enhancing Deterministic Global Optimization

Complexity Reduction Methods for Large-Scale Spatially Explicit Biofuels Network Design

Supervised Learning of the Optimal Objective Function Value in Chemical Production Scheduling

Superstructure-based optimization of membrane network systems for multicomponent liquid mixture separation

A General Framework and Optimization Models for Integrated Capacity and Production Planning

Engineered poplar for bioproduction of the triterpene squalene

Optimization methods for plastics management supply chain design

Piecewise linear trees as surrogate models for system design and planning under high-frequency temporal variability

Large-scale spatially explicit analysis of carbon capture at cellulosic biorefineries

Computational enhancements of continuous production scheduling MILPs using tightening constraints

An Explainable Classification Framework for Determining and Understanding the Suitability of Solvent Extraction for Bioproduct Recovery

Accounting for costs in attainable‐region‐based reactor–separation network synthesis: Models, tradeoffs, and insights

Multi-technology separation system synthesis

Linear Programming-Based Preprocessing Algorithm and Tightening Constraints for Multiperiod Blend Scheduling Problems

A Coverage Self-Consistent Microkinetic Model for Vapor-Phase Formic Acid Decomposition over Pd/C Catalysts

Optimization-Based Azeotropic Distillation System Synthesis Using Geometric Insights

On the utility of production scheduling formulations including record keeping variables

Ethanol to diesel: a sustainable alternative for the heavy-duty transportation sector

High yield co-production of isobutanol and ethanol from switchgrass: experiments, and process synthesis and analysis

Supervised Machine Learning for Understanding and Improving the Computational Performance of Chemical Production Scheduling MIP Models

Production scheduling under demand uncertainty in the presence of feedback: Model comparisons, insights, and paradoxes

CProS: A web-based application for chemical production scheduling

On the derivation of graphically inspired feasibility constraints for distillation network synthesis

Variable Bound Tightening and Valid Constraints for Multiperiod Blending

Collaborators (13)

Iiro Harjunkoski

Mehmet Mercangöz

Simon Brædder Lindahl

Manos Mavrikakis

Caleb Geissler

Shawn D. Mansfield

Yuanhui Zhang

Massimiliano Barolo

Zhiyong Ren

Nathan Adelgren

Sabrina Summers

George W. Huber

Boeun Kim

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