• Modelled the ferroelectric switching behavior of Hafnia-zirconium using electronic structure codes for application in next-gen. logic and memory microelectronics.• Simulated the surface Piezoelectric effect in Si surfaces• Conducted a summer internship program composed of guest lectures and a hands-on computational project• Organized the postdoc career fair as chair of the lab-industry network connection (LINC) committee

• Utilized quantum mechanical methods to simulate atomic material systems. Leveraged python for workflow scripting, algorithm development and software development in the space of atomistic modeling.• Developed an active learning algorithm which utilized a Gaussian Process machine-learning model to predict material stability, thereby enabling the high-throughput generation of catalyst crystal structures for fuel cell applications.• Constructed a high-throughput workflow on HPC clusters to generate a sizable dataset of adsorption energetics. Developed physically inspired features and tested various machine learning methods (Gaussian process, linear regression, Support Vector Regression, etc.).• Communicated research findings to a broader audience by presenting at academic conferences and at regular meetings with supervisors and colleagues

Twice served as a graduate teaching assistant for the Chemical Engineering undergraduate laboratory course, CHEMENG 185 B• Guided undergraduate teams in planning, executing, and interpreting a student-driven research project with the overarching goal of developing skills associated with successful scientists and researchers• Oversaw weekly research meetings with students to discuss results and plan future experiments• Worked with students in the laboratory space to setup experimental protocols and carry out research

Assisted in the fabrication and characterization of GaAs and GaAs alloy based photo-voltaic devices, through molecular beam epitaxy (MBE). Theoretical modelling of band gap energies in intrinsic materials and quantum well heterostructures was performed to elucidate experimental results. Parametric analysis of theoretical efficiency elucidated optimal device parameters to guide future experimentation.

• Investigated cellulose solubility in mixtures of the ionic liquid ([EMIm][DEP]) and organiccosolvents for biomass conversion (biofuel) applications• Preferential solvation mechanisms, cellulose solubility thermodynamics, mixture rheology, andbiomass conversion kinetics were explored with a variety of experimental techniques

Developed affordable front contact electrode materials for silicon solar cells. Responsibilities included fabricating photo-voltaic devices using clean-room facilities. Devices were optically and electrically characterized to find device performance.