Eight faculty members in the Texas A&M University College of Engineering received Faculty Early Career Development (CAREER) Awards from the National Science Foundation (NSF) for their 2021 funding cycle.
The NSF CAREER program offers support to early career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization. Activities pursued by early career faculty are expected to build a firm foundation for a lifetime of leadership in integrating education and research.
Each year, the NSF presents an estimated 500 CAREER awards totaling around $250 million to early career faculty at U.S. institutions of higher learning, museums, observatories, research labs, professional societies and similar organizations associated with research or educational activities.
This year’s College of Engineering recipients include:
Dr. Sara Abedi
Assistant Professor and Stephen A. Holditch Faculty Fellow
Harold Vance Department of Petroleum Engineering
Abedi's research project “ An Integrated Experimental-Theoretical Framework for Understanding the Multiscale Mechanical Response of Rock-Reactive Brine Interactions” will study the impact of reactive brine interactions on the properties of rocks at multiple length scales using advanced experimental and modeling techniques.
Her project will acknowledge the multiscale and nonhomogenous aspect of rock-fluid interactions and aims at gaining a fundamental insight of the coupling between the chemical, microstructural and mechanical processes involved. Abedi, an affiliated faculty member in the Zachry Department of Civil and Environmental Engineering, tailored her research for a broad application that aligned with the civil, mechanical and manufacturing innovation area within the National Science Foundation, particularly for advancing infrastructure resilience and sustainability.
Read more about Dr. Abedi's research
Dr. Dion S. Antao
Assistant Professor
J. Mike Walker ’66 Department of Mechanical Engineering
The goal of Antao’s project “ Ultrafast Localized Plasmas in Dense Fluids: From Fundamental Phase-Change Phenomena and Diagnostics to Efficient Heat and Mass Transport” is to integrate research and education around the use of ultrafast (20-100 nanoseconds) and fast (0.1-10 microseconds) pulsed plasma discharges in liquids and vapors to probe, manipulate or tune and enhance heat and mass transfer processes during liquid-vapor phase change encountered in boiling and desalination processes.
"Phase-change heat transfer processes are at the center of most aspects of our lives," he said. "We propose to develop theory and tools to understand the fundamentals of these phase-change phenomena better, and then manipulate, tune and enhance such processes to optimize thermal and mass transport in various energy conversion and water treatment technology."
Read more about Dr. Antao's research
Dr. Theodora Chaspari
Assistant Professor
Department of Computer Science and Engineering
Chaspari’s goal for her project “ Enabling Trustworthy Speech Technologies for Mental Health Care: From Speech Anonymization to Fair Human-centered Machine Intelligence” is to design reliable machine learning, notably for speech-based diagnosis and monitoring of mental health, for addressing three pillars of trustworthiness: explainability, privacy preservation and fair decision making. Trustworthiness is critical for both patients and clinicians: patients must be treated fairly and without the risk of reidentification, while clinical decision making needs to rely on explainable and unbiased machine learning.
"If we can specifically predict the degradations in their tone, then we should be able to intervene and prevent a relapse of the symptoms from occurring," said Chaspari. "We are developing AI that is not only reliable in terms of precise monitoring but also more human-centered and friendly."
Read more about Dr. Chaspari's research
Dr. Dileep Kalathil
Assistant Professor
Department of Electrical and Computer Engineering
There are three critical issues that significantly impede the success of reinforcement learning (RL) in real-world engineering systems: lack of resiliency, data efficiency and scalability. Kalathil’s CAREER project “ Towards a Principled Framework for Resilient, Data Efficient and Scalable Reinforcement Learning for Control” develops a principled approach for the RL-based design of control algorithms for large-scale real-world engineering systems by overcoming the fundamental challenges of resiliency, data efficiency and scalability. The main application domain of interest is electricity systems, which guides the problem formulation and solution approaches, and lends credence to the algorithms using real-world examples.
“This is an area of machine learning that is not very well addressed,” Kalathil said. “And that is what reinforcement learning is about. Reinforcement learning is essentially machine learning for making active decisions.”
Read more about Dr. Kalathil's research
Dr. Vinayak Krishnamurthy
Assistant Professor
J. Mike Walker ’66 Department of Mechanical Engineering
Krishnamurthy’s project “ Partitive Solid Geometry for Computer-Aided Design: Principles, Algorithms, Workflows & Applications” will establish the foundations of a new geometric modeling framework – partitive solid geometry – for the design of complex two- and three-dimensional geometric patterns. Modeling complex patterns, such as cellular structures, is intrinsic to several areas of national interest, including consumer products, protective gear for sports and the military, and curved miniaturized electronics. This research will introduce space-filling shapes as the underlying novel shape representation for partitive solid geometry, which will enable forward design workflows for the creation of complex shapes and structures for generative and procedural design.
"The award will allow me to continue my efforts on building a solid foundation for my long-term goal — to create the next generation of design tools that augment the designers' cognitive ability for creative problem-solving,” he said. “What this research hopes to accomplish in the long term is to give the control back to the designer by making complex geometric modeling available to all — real time and intuitive to interact with, useful for serious engineering design and usable for recreational learning."
Read more about Dr. Krishnamurthy's research
Dr. Chao Ma
Assistant Professor
Department of Engineering Technology and Industrial Distribution
Advanced ceramic materials play a vital role in numerous applications with strict requirements or under harsh conditions, such as those in the biomedical, aerospace, chemical, and energy industries. Traditional manufacturing methods for ceramic parts have severe geometric constraints, long production time and high cost. Binder jet additive manufacturing can overcome these drawbacks. However, it is currently unable to produce dense ceramic parts, significantly limiting its applications.
Ma’s project “ Powder Preparation and Compaction for Ceramic Binder Jet Additive Manufacturing” aims to increase understanding of how powder granule characteristics (density, structure and strength) and powder compaction affect resulting part density. In addition, this CAREER plan includes a series of educational activities to strengthen and diversify the advanced manufacturing workforce, impacting K-12 teachers and students, undergraduate and graduate students, and professionals in the industry.
Read more about Dr. Ma's research
Dr. Xingyong Song
Assistant Professor
Department of Engineering Technology and Industrial Distribution
Through his project “ Control of a Long and Curved String for Deep Underground Exploration” Song will contribute new fundamental knowledge related to modeling and control of a large-scale system with a long, curved, string-like geometry. This will lead to advances in deep underground directional drilling systems impacting national strategic areas including energy, the environment and outer space exploration.
In energy, it will enable automated directional drilling for enhanced geothermal energy systems and unconventional natural gas production. In environmental research, the project will address a critical technical barrier to accessing ancient ice cores in the South Pole, to evaluate large-scale climate patterns and predict future climate changes such as the evolution of global warming. In outer space exploration, it will build the fundamental foundation to control a drilling robot to reach potential signs of microbial life and water resources on Mars, to fulfill the ultimate mission of the Mars exploration.
Read more about Dr. Song's research
Dr. Maryam Zahabi
Assistant Professor
Wm Michael Barnes ’64 Department of Industrial and Systems Engineering
Zahabi’s project “ Adaptive Driver Assistance Systems and Personalized Training for Law Enforcement Officers (ADAPT-LEO)” will model officers' driving workload and performance in high-demand situations, then use those models to develop in-vehicle technology and training solutions that adapt to officers' workloads to reduce the risk of crash-related harm in police operations. The models, methods and tools developed may also benefit other driving and training domains.
“Previous examinations on adaptive training are generally a proof of concept without implementation in actual training settings, which might have been due to the limitations of off-the-shelf training media. We will fill this gap by developing an adaptive driving simulation-based training system,” Zahabi said. “This CAREER research seeks to fill this knowledge gap by establishing novice law enforcement officers’ performance models that can accurately represent their cognitive, perceptual and motor demands while driving.”