• I am a PhD candidate with 8 years of research experience in Chemical Engineering and Biological Sciences. Highly skilled in bio-data analysis, developing multi-physics & surrogate models, and designing experiments for their validation. Published over 8+ scientific articles in top-tier journals.• My expertise encompasses a broad range of modeling frameworks for physical systems, including but not limited to Finite Element Modeling (FEM), coarse-grained Molecular Dynamics (MD) simulations, Partial Differential Equations (PDE) modeling of signaling networks, Active Vertex Models of biophysics, numerical models such as Level Set for modeling multiphase flows, as well as surrogate or data-driven modeling approaches.• My familiarity with computer vision and its applications in the field of Systems Bio-engineering is demonstrated through a machine learning-based tool called MAPPER, which automates the analysis of adult fruit fly wings. By combining this tool with bioinformatics analysis, I was able to identify 5 therapeutic targets within a loss-of-function GPCR screening dataset, resulting in 2 publications as first author in peer-reviewed journals.• In addition, I possess a robust domain knowledge of process optimization using machine learning. I developed a Bayesian Optimization framework, employing Gaussian Process Regression models, to estimate parameters for computationally expensive biophysics models of development. This work culminated in the award of a $48,000 pilot grant from Northwestern University's NSF-Simons Center for Quantitative Biology.• As a highly proficient programmer, I am well-versed in multiple programming languages and both commercial and open-source tools for data visualization and machine learning. I have employed these techniques in major scientific projects throughout my career.• I am highly collaborative and skilled in working in a multidisciplinary setting. For instance, I led a team of 10+ individuals in a cross-collaborative project to develop a multiscale mechano-chemical model of epithelial morphogenesis, which resulted in 2 manuscripts being published in peer-reviewed journals.• I've designed a novel simulation to investigate microchannel Taylor flow, showcasing my expertise in microfluidics and computational fluid dynamics. Furthermore, I've engineered a cost-effective microfluidic platform, reducing initial investment costs by 98.5%, and published related work in 3 prestigious peer-reviewed journals.