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Ashwin Shekar
Graduate Research Assistant
Professional Background
Ashwin Shekar is a highly accomplished computational scientist with over five years of experience in executing data-driven solutions across both academic and industrial landscapes. His extensive career has equipped him with a rich background in identifying and uncovering underlying structures within complex scientific data sets. With a strong foundation in classical machine learning techniques transitioning into advanced deep learning methodologies, Ashwin has honed his skills in various areas crucial to data-driven modeling, forecasting, dimensionality reduction, feature extraction, and process control.
Among his many academic contributions, Ashwin has been active in sharing his insights and findings through 9 conference presentations and has authored or co-authored 5 influential papers in top-tier peer-reviewed journals, including the prestigious Physical Review Letters. His work not only emphasizes his deep understanding of both theoretical and applied aspects of computational science but also showcases his dedication to advancing the field.
Ashwin's analytical skills were further demonstrated during his internship as a Data Science Intern at Eli Lilly and Company, where he successfully applied his knowledge to enhance data-driven process designs within the pharmaceutical sector. This hands-on experience complements his solid educational background, making him a well-rounded expert in his field.
Education and Achievements
Ashwin began his academic journey with a Bachelor's degree in Chemical Engineering from the renowned Birla Institute of Technology and Science, Pilani - Goa Campus, where he graduated with an impressive score of 9.3 out of 10. His strong performance laid the groundwork for his pursuit of advanced studies.
He then progressed to the University of Wisconsin-Madison to pursue a Doctor of Philosophy degree in Chemical Engineering. Throughout his doctoral studies, he served as a Graduate Research Assistant, where he applied his computational skills to investigate complex engineering problems, further solidifying his status as a thought leader in the field of computational science.
Moreover, his scholarly endeavors have led to notable academic recognition, given that his research articles have impacted the scientific community and bolstered his portfolio as a diligent researcher. Ashwin's commitment to knowledge dissemination and research excellence represents a significant aspect of his career.
Key Achievements
- Conference Contributions: With 9 conference talks delivered, Ashwin has proven his ability to communicate complex ideas effectively to his peers, fostering discussions and knowledge exchange on data-driven methodologies in computational science.
- Publication Record: His publication record, which includes 5 first and second author papers in top-notch journals such as Physical Review Letters, highlights his critical thinking and ability to contribute original research that enriches the scientific community.
- Industry Experience: His tenure as a Data Science Intern at Eli Lilly involved collaborating on data-driven process design. This role not only underscored his versatility but also showcased his ability to bridge theoretical knowledge with practical applications in the pharmaceutical industry.
- Diverse Research Background: Ashwin has cultivated a diverse research portfolio, which includes work as a Research Scholar at the Indian Institute of Science, and internships at Unilever and within his undergraduate institute, where he was an Undergraduate Student Researcher. Each position enriched his understanding of computational science from various perspectives.
In conclusion, Ashwin Shekar is a dedicated computational scientist whose comprehensive expertise spans machine learning, data science, and chemical engineering. With impressive educational credentials and a strong record of publications and presentations, he stands out as an expert at the intersection of academia and industry. His achievements reflect his commitment to advancing science through data-driven methodologies, making him a sought-after professional in the field.