Name: Abdullah Maruf
Pronouns: He/Him
Institution: Dartmouth College
Department: Engineering and Earth Science
Biography:
I am a second year graduate student (Masters) working on defect containing iron-oxides using high-throughput computational approach for planetary science implications (i.e. Mars). I have been involved in diverse research projects in the past few years, including experimental research on quantum computing, specifically designing and characterizing 2 qubit Kerr-cat chip. My goal is to continue this line of research, specially quantum error correction with surface codes in the future.
Academic Status: Masters Student
Year in program: 2nd
Research Area/Department: Engineering; Materials Science
Other, specify:
Major/Specialty: I’m an Earth/Materials-Science major working on fundamental understanding of mineral/natural magnets (i.e. spin-orientation and vorticity) using theoretical/computational approach with DFT and ML.
Degrees Earned or in Progress: 2nd year Masters Student
What courses or academic preparation have you completed to prepare for a summer internship experience?
Current (Grad Level): ENG131: Science of Solid States Materials, ASTR: Astrophysics Grad Level: CHEM267: Materials Chemistry, ENGS137: Molecular Design with DFT. Undergrad Level: Quantum Mechanics, Solid State Physics, Statistical Mechanics, Lineal Algebra I, Differential Equation I and II, Statistics I and II, Non-Parametric Statistics, Introduction to R for Data Science, Introduction to Computer Science with C
Have you published any research or worked on research/technical projects? Yes
Where has your research been published or where have you conducted research/technical projects? My most recent works, including summer research at national labs, have yet to be published and are currently being either reviewed at journal or drafted (three articles in pipeline at various stages). Before that, I was heavily involved in physics/engineering research since my freshman year during undergraduate studies at South Dakota State University – which resulted most of the published work so far (mentioned in abridged-CV).
Please describe your research/academic interests:
I have a broad research interest in the field of materials and quantum information science (since they are quite interdisciplinary in nature) utilizing data and machine learning techniques.
Computational and Data Science Areas:
Computational Science Applications, i.e., Bioscience, Cosmology, Chemistry, Environmental Science, Nanotechnology, Climate, etc.; High-Performance Computing; Machine Learning and AI; Quantum Computing and Information Science
Research Synergy:
I am particularly drawn to computational, AI/machine learning, and data sciences research for several reasons. My primary interest lies in the realm of Quantum Information Science (QIS) and Machine Learning (ML) research projects within the Exascale Computing Project (ECP), with a focus on potential applications in the fields of materials physics and chemistry. These technical areas align with my academic background as an Earth/Materials-Science major and my ongoing work in understanding the fundamental properties of mineral and natural magnets. My current research involves employing theoretical and computational approaches, including Density Functional Theory (DFT) and Machine Learning (ML) techniques, to gain insights into the intricacies of spin orientation and vorticity in these materials. This work has allowed me to develop strong computational skills, a deep understanding of materials science, and expertise in applying ML methods to complex scientific problems. My interest in computational, AI/ML, and data sciences research is highly relevant to the work conducted at the DOE labs. Firstly, the interdisciplinary nature of my research aligns well with the DOE’s mission, which often involves tackling complex, multifaceted challenges. Secondly, my expertise in computational techniques can be invaluable for optimizing simulations and data analysis, enhancing the efficiency of experiments, and accelerating the discovery of novel materials with applications in energy and beyond. Moreover, my openness to engaging with a wide range of intriguing problems complements the collaborative environment fostered by DOE labs. I am eager to contribute my skills and gain valuable research experience while working alongside DOE lab staff on projects that can have a substantial impact on advancing science and addressing critical energy and environmental challenges. So I believe my background and interests in computational, AI/ML, and data sciences are well-aligned with the research goals and collaborative spirit of the DOE labs, making me a motivated and valuable candidate for research synergy within this dynamic environment.
Motivation:
My primary goal is to work on interesting problems in the field of physics/chemistry and data-science as a future interdisciplinary career-researcher. And I’ve been trying to follow this path, as a student researcher, over the past few years by taking relevant courses, which genuinely intrigues me, and getting involved in diverse research projects spanning from computational materials science and engineering to backend software development for parallelization and quantum computing. While many of my class or research projects did not “”see the light of day””, but I still tried to be persistent and am grateful that I was able to learn many valuable skills that I wound not have learnt otherwise. For the upcoming summer project with SRP, I intend to utilize my past research experience and learn new skills in programming and data-science/ML with a possible application in QIS or materials science. And I believe, it will not only help me to contribute more effectively but also make me a better researcher overall, irrespective of my future research topics as an aspiring career scientist.
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