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Ben Stetler
Researcher at NYU Langone Health
Professional Background
Ben Stetler is a dedicated and skilled research associate who has been making significant contributions in the field of neuroimaging at NYU Langone Health over the past two years. His professional journey is characterized by a strong foundation in mathematics and a passion for data science and machine learning. At NYU Langone, Ben principally focuses on developing and testing innovative data analysis pipelines tailored to the diverse neuroimaging datasets that the lab collects, demonstrating his ability to translate complex data into actionable insights. Alongside his analysis work, Ben plays a crucial role in maintaining the lab's computational resources, ensuring that fellow researchers have the tools they need to succeed in their projects. This dual focus not only reflects his technical expertise but also highlights his commitment to collaborative research and education.
Before joining NYU Langone, Ben established himself as a proficient database software engineer, where he specialized in developing high-performance databases for big data applications utilizing the powerful kdb+ database. His background in database engineering complements his research work, providing him with a unique lens through which he approaches data analysis tasks.
Beyond his current role, Ben's experience extends to various positions that have equipped him with a breadth of knowledge and skills. His past roles include being a data scientist at First Derivatives and a software engineer at Kx Systems, both of which honed his ability to manage and analyze large data sets efficiently. Furthermore, Ben has worked as a science analyst at Infor, as well as serving as an academic tutor and student lecturer at Harvard University. These diverse experiences underline his well-rounded expertise in mathematics and data analysis, making him a valuable asset in any research or technological environment.
Education and Achievements
Ben's academic background is impressive and reflects his commitment to advancing his knowledge in mathematics. He obtained his Master of Arts (M.A.) in Mathematics from Harvard University, one of the leading institutions in the world, known for its rigorous academic standards and distinguished faculty. Prior to that, Ben completed his Bachelor of Arts (B.A.) in Mathematics at Stanford University, which speaks to his foundational skills and early interest in the field. His education has equipped him with a strong theoretical understanding of mathematical concepts, probability, and statistics, all of which are essential areas in both data science and neuroimaging research.
In addition to his formal education, Ben has actively engaged in research activities that have furthered his expertise. He participated in the Research Experience for Undergraduates program at Cornell University and was involved in the Summer Research for Undergraduates at Stanford University. These research opportunities allowed him to apply his academic knowledge practically and develop his skills in a collaborative research setting.
Throughout his professional career, Ben has been recognized for his contributions both as a researcher and educator, illustrating his ability to communicate complex concepts effectively. His previous roles as a science analyst, academic tutor, and student lecturer showcase his dedication to empowering others in their learning journeys, reflecting a commitment to education that is a significant part of his career.
Skills and Interests
Ben's technical skills are complemented by his keen interest in emerging technologies and methodologies in data science. Currently, he is exploring machine learning techniques utilizing popular Python packages such as TensorFlow and scikit-learn. This endeavor demonstrates his commitment to staying at the forefront of data science and incorporating state-of-the-art tools into his workflows.
Moreover, Ben's prior experience with data analysis packages in R adds versatility to his skill set. His extensive background in mathematical probability and statistics elevates his ability to perform complex analyses and build predictive models that can unlock valuable insights for various applications.
As Ben continues to develop his skill set in machine learning, he remains focused on the intersection of data science and neuroscience, striving to leverage data analytics to deepen our understanding of the brain and its functions. This dual interest not only showcases his intellectual curiosity but also positions him as a pioneer in exploring novel approaches to neuroimaging data interpretation.
Achievements
- Developed and tested data analysis pipelines for diverse neuroimaging data at NYU Langone Health.
- Maintained and optimized computational resources for research efficiency in a neuroimaging lab environment.
- Played significant roles in high-performance database development and management during his time as a database software engineer.
- Actively participated in research collaborations, contributing to the advancement of data analysis methodologies in academic settings.
- Engaged in educational roles that emphasize teaching complex mathematical concepts to peers and students.
Interests
- Machine Learning: Exploring TensorFlow and scikit-learn in Python for innovative data analysis methods.
- Data Science: Passionate about applying statistical methods and algorithms to extract insights from data.
- Neuroimaging: Dedicated to utilizing computational techniques for improved understanding of brain function and structure.
Location
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