Aditi Verma

Aditi Verma

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I am interested in how nuclear technologies specifically and complex technologies broadly—and their institutional infrastructures—can be designed in more creative, and participatory ways that are epistemically inclusive of both lay and expert perspectives. To this end, my work focuses on developing a more fundamental understanding of the early stages of the design process to improve design practice and pedagogy, and also improve the tools with which designers of complex systems work. I am particularly interested in developing novel approaches for gathering both qualitative and quantitative data generated throughout the design processes of complex systems and using this data to improve design outcomes. In my work, I focus on three main research questions:

  1. How can a fundamental understanding of design be used to improve design practice, design tools, and engineering pedagogy?
  2. How can design processes be made more open and participatory such that epistemic plurality and inclusivity are achieved as part of the design process?
  3. How can insights from design research be applied to the designs of policies and institutions for the governance — both innovation and regulation — of nuclear technologies?

The picture depicts the Sociotechnical Readiness Level which is a framework which critiques and reimagines the traditional Technology Readiness Level Framework. As part of the new SRL framework, we are developing new metrics and indicators to measure both social and technical aspects of a technology's readiness throughout its design and development processImage: The Sociotechnical Readiness Level, which is a framework which critiques and reimagines the traditional Technology Readiness Level Framework. As part of the new SRL framework, we are developing new metrics and indicators to measure both social and technical aspects of a technology’s readiness throughout its design and development process.

What are some of your most interesting projects?

Two new projects I am most excited about are (1) developing a sociotechnical readiness level framework for the assessment of novel technologies and (2) diagnosing the causes of cost overruns in the early stages of technology design.
In the first project, we are critiquing and reimagining the traditional Technology Readiness Level framework to capture both societal and engineering aspects of a technology’s readiness and integrate them into a single framework. As part of this work, we will develop metrics and indicators for assessing a technology’s readiness across the nine levels of sociotechnical readiness.
In the second project, we are studying how decisions made in the early stages of design impact overall system cost. This work is especially crucial in a nuclear energy context because recent nuclear plant construction projects have been severely impacted by cost overruns as well as project delays. It is vitally important to diagnose the causes of these cost overruns and address them in the early stages of the design if nuclear reactors are to play a significant role in our low-carbon energy systems.

How did you end up where you are today?

I was drawn to the field of nuclear engineering because of the enormous potential nuclear technologies have for solving one of the grandest challenges of our time: access to reliable, clean, and abundant energy.

What is the most significant scientific contribution you would like to make?

I hope to develop a deeper and more fundamental understanding of the design processes of complex systems that leads to more creative, robust, societally, and environmentally beneficial design outcomes.

What makes you excited about your data science and AI research?

There is an enormous opportunity to use data science and AI to study the early stages of the design processes of complex systems and develop new tools to stimulate a broader exploration of the design space and to ensure better design outcomes.

What are 1-3 interesting facts about yourself?

I love learning new languages. Depending on how you count, I speak (with varying levels of ability) six (or seven).


Research Highlights

Ken Resnicow

Ken Resnicow

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Dr. Resnicow studies tailored behavior change interventions, natural language processing of clinical encounters, analyses of large datasets related to obesity and other chronic diseases, novel designs such as SMART, MOST, and reinforcement learning, and applied complex systems and chaos theory in behavior change.

 


Accomplishments and Awards

Bogdan I. Epureanu

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• Computational dynamics focused on nonlinear dynamics and finite elements (e.g., a new approach for forecasting bifurcations/tipping points in aeroelastic and ecological systems, new finite element methods for thin walled beams that leads to novel reduced order models).
• Modeling nonlinear phenomena and mechano-chemical processes in molecular motor dynamics, such as motor proteins, toward early detection of neurodegenerative diseases.
• Computational methods for robotics, manufacturing, modeling multi-body dynamics, developed methods for identifying limit cycle oscillations in large-dimensional (fluid) systems.
• Turbomachinery and aeroelasticity providing a better understanding of fundamental complex fluid dynamics and cutting-edge models for predicting, identifying and characterizing the response of blisks and flade systems through integrated experimental & computational approaches.
• Structural health monitoring & sensing providing increased sensibility / capabilities by the discovery, characterization and exploitation of sensitivity vector fields, smart system interrogation through nonlinear feedback excitation, nonlinear minimal rank perturbation and system augmentation, pattern recognition for attractors, damage detection using bifurcation morphing.


Accomplishments and Awards