(4dz) Machine Learning for Systematic Material Design and Process Development in Vapor and Liquid-Based Crystallization

I am a Postdoctoral Fellow at the School of Chemical and Biomolecular Engineering at Georgia Institute of Technology. My postdoctoral research under the supervision of Drs. Andreas Bommarius, Ronald Rousseau, and Martha Grover focuses on process design and development for continuous manufacturing of pharmaceuticals and is supported by U.S. Food and Drug Administration. I obtained my Ph.D. in Chemical Engineering in 2019 from the University of Maryland, College Park under the supervision of Dr. Raymond Adomaitis. My Ph.D. research was focused on vapor-based synthesis of nanomaterials and thin-films for space-related applications and was supported by U.S. National Science Foundation and NASA Goddard Space Flight Center. I was also a Future Faculty Fellow at the same institution.

Research Interests

1- Systematic design of the next generation of functional nanomaterials for emerging applications by vapor-based deposition

Functional nanomaterials have a variety of applications from electronics to health and catalysis. Among different synthesis methods vapor phase processing techniques stand out since they offer a highly controlled setting for producing crystalline nanostructures and thin-films. In fact, in theory, chemical vapor-based processes can be designed such that only one layer of atoms is deposited at each process step, providing a tool to manipulate the chemistry and thickness of a deposited structure down to atomic scale. Indeed, this technology is already matured in the form of the Atomic Layer Deposition (ALD) process for producing dozens of binary compounds, with metal-oxides more than any other group. However, further developments necessary for producing complex, non-binary nanostructures for emerging applications such as spacecraft optics, self-cleaning surfaces, antimicrobial coatings, nanocatalysts, and protective layers, in high-throughput and robust processes, are challenged by two factors: (i) Despite experimental advancements in producing specific materials (e.g., aluminum oxide thin-film for sub-10 nm transistors), our fundamental knowledge about film nucleation and growth processes remains limited. This becomes a serious issue when synthesis of more complex structures with non-binary chemistries is needed. (ii) Thanks to the ALD’s ability in nanoscale manipulations, the available design space for producing even a simple ternary system such as indium tin oxide (ITO) is vast, impossible to explore by purely experimental approaches. My research program focuses on using a combination of experiment and theory to use the large amount of data available on binary ALD processes to systematically approach the discovery and optimization of complex non-binary nanostructures with superior properties.

2- Development of data-driven tools for pharmaceuticals crystallization process modeling, monitoring, and control

Liquid phase crystallization is a critical step in large-scale manufacturing of most synthetic small molecule drugs serving two primary purposes of chemical purification and establishment of drug’s physical attributes such as dissolution rate and stability. Robust process design and development and subsequent monitoring for pharmaceuticals crystallization face challenges including lack of accurate integrating process models that incorporate different physical phenomena involved and Process Analytical Technology models that can translate the captured data by the modern probes to usable information for monitoring and control purposes. My research focuses on developing data-driven approaches to build robust models for fast, accurate, and reliable translation of the acquired data from crystallization processes. These include developing a variety of image analysis algorithms based on traditional and modern computer vision techniques. These tools then can be used to build hybrid process models for particular batch and continuous crystallization systems, facilitating process optimization, and control.

Teaching Interests

I am interested in teaching core chemical engineering courses in both graduate and undergraduate levels. I also would be happy to design new electives in line with my research. My teaching philosophy is based on (1) ensuring students’ preparedness for both research and industrial careers, (2) providing the best learning experience for students from different Socio-economic and cultural backgrounds, and (3) strong emphasis on outside of class and online learning and material development. Committed to our social responsibility, my lab will be active in reaching out to the local community by participating in science festivals, mentoring local high school students, and hosting interns from local schools in our lab.