Research
My research is centered at the convergence of Operations Research, quantitative modeling, and climate change decision making. With an experience in probabilistic risk assessment, data analysis, decision sciences, applied machine learning, Life-Cycle Assessment and Techno-Economic Analysis (LCA/TEA), I am interested in understanding the multifaceted challenges posed by climate change and contribute to the development of data-driven decision support tools to both mitigate and adapt critical infrastructure systems to climate risks.
I. Modeling Resilience and Adapting Critical Infrastructure Systems to Climate Change
Keywords - Sea-Level Rise Adaptation Planning , Resilience Indicators, Adaptation Decision models, Impact Assessment, Techno-Economic Analysis (TEA), Wastewater systems.
Methods - Probabilistic Risk Assessment, Mixed-Integer Linear Programming, Spatial Data Analysis, Applied ML, ML-based Optimization, Density-based Spatial Decomposition, Spatial Optimization, Network tracing, Network optimization.
Under this research stream, I am interested in modeling infrastructure systems’ resilience to climate change stressors such as sea-level rise, and developing data-driven decision models to inform adaptation policy making. My Doctorate Research titled ‘’Resilience Assessment & Adaptation Planning of On-Site Wastewater Treatment & Disposal Systems,” was motivated by answering the following research questions:
For infrastructure systems where data on historical performance under disruptions is not available or deficit, how can we quantify the resilience of the system under future events?
For network based infrastructure systems, such as power networks, indicators such as connectivity, redundancy etc. are used to model resilience of systems known as the ”Network Resilience Theory”. For standalone non-network based systems, such as decentralized wastewater management systems, refineries, etc., how can we design indicators that reflect the systems’ resilience under current and future conditions?
In the event of a system failure, how can we quantify the domino effect factor and how would this shape the ability of the system to adapt and recover from disruptions?
How can we develop multi-dimensional resilience measures that are not dependent on allocating subjective weights to represent indicators’ significance and yet are directly associated with and can be reevaluated under various adaptation pathways to determine the optimal adaptation scheme.
With a regional focus on Miami-Dade county, the primary strategy for adapting on-site wastewater systems is by decommissioning those systems at risk and connecting the property to the main sewer line. Given the current and future stressors on the existing sewer network, and the moratorium status of the existing pump stations, what are the alternative adaptation approaches.
Considering various adaptation alternatives including advanced onsite treatment technologies, sewer extension and community-scale wastewater network clusters, what is the optimal (integrated) adaptation portfolio that minimizes the overall adaptation costs while ensuring a post-adaptation resilience threshold is achieved.
II. Sustainability and Circular Transition of Systems
Keywords - From Waste to Resource, Nutrients Recovery, Bio-fertilizers, Biogas from Municipal Waste, Sustainability, LCA/TEA
Methods - Data Collection and analysis, ML, Predictive Modeling, Geospatial Analysis, Techno-Economic Analysis, Global Assessment Modeling.
My current post-doctoral appointment at Northwestern University focuses on studying the circularity in the urban water sector. As a member of Dunn Systems Analysis Group, in the Chemical and Biological Engineering department, I collaborate closely with a diverse team of chemical and environmental engineering experts to study the potential of recovering byproducts at the municipal wastewater treatment facilities such as fertilizers and biogas. This research addresses the following objectives:
From a systems analysis lens, evaluate the cost and environmental feasibility of deploying emerging wastewater treatment technologies for recovering byproducts such as nutrients for use as fertilizers, and biogas for use as a renewable energy source.
Investigate how the quantity and composition - nitrogen (N), phosphorus (P), and suspended solids - of incoming wastewater influence the potential for byproduct recovery across different regions. This exploration is crucial as wastewater compositions and permissible treatment levels vary among regions, thereby impacting the potential for byproduct recovery.
Through analyzing the fertilizers’ products sales and markets in the USA, evaluate the demand and cost-effectiveness of producing fertilizers from Biomass in wastewater treatment facilities.
Develop an integrated assessment model to study the dynamics of the water-energy-food sector in order to balance the demand and supply sides. Demand is modeled by treating a certain amount of wastewater up to regulated treatment thresholds, demand for fertilizers, and demand for energy to power the WW treatment facility. The supply is modeled by the inflow volume of wastewater, as well as its composition of solids, nitrogen and phosphorus (nutrients).
Should the wastewater treatment facility use the recovered biogas in-house or sell it to the grid? what is the cut-off point beyond which more biogas generation is no longer cost or environmentally efficient?