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Peter Meilstrup
Perceptual scientist, software engineer
Peter Meilstrup is a distinguished data scientist whose career is marked by a robust academic foundation and diverse professional experiences. With a Doctor of Philosophy (Ph.D.) in Neurobiology and Behavior from the University of Washington and a Bachelor of Science (B.S.) in Engineering & Applied Science from the prestigious California Institute of Technology (Caltech), Peter has established a solid groundwork in both the theoretical and practical aspects of his field. His academic background in experimental psychology and visual perception has equipped him with unique insights into the measurement of perception and behavior, which are invaluable in addressing complex challenges in user experience (UX), behavioral metrics, visualization, and ultimately, data science.
Professionally, Peter's journey has seen him thrive in various roles, showcasing his versatility and passion for innovation. He's had the privilege of working at renowned organizations where he has applied his deep understanding of measurement and applied science. As a Software Engineer II at Microsoft, he honed his software engineering skills, exploring the intersections of data science and user experience. His earlier role as a software engineer at Second Sight Medical Products allowed him to delve into cutting-edge technologies in medical devices, further enriching his capacity to contribute to meaningful, real-world applications of data science.
Peter's experience as a research associate at the University of Washington underscores his commitment to academic inquiry and exploration. Here, he applied his expertise in experimental psychology, working closely with complex datasets to unearth insights that inform both academic and practical applications in the field. His tenure as an Undergraduate Research Fellow at Caltech not only laid the groundwork for his expansive knowledge in engineering and applied science but also ignited his enthusiasm for rigorous scientific inquiry and test-driven development.
In addition to his roles in engineering and research, Peter is passionate about the methodologies behind software development. He advocates for test-driven development and values the importance of refactoring and reproducible data analysis, ensuring that his approach to data science is not only innovative but also robust and reliable. His enthusiasm for these practices speaks to his commitment to maintaining high standards in all aspects of his work, ultimately leading to better products and findings.
Throughout his career, Peter has demonstrated a strong ability to bridge the gap between theoretical knowledge and practical application. He expresses a keen interest in advancing UX, behavioral metrics, and visualization techniques. Moreover, his diverse background and rich experiences make him a valuable asset to any team focused on pushing the boundaries of data science.
Professional Background
Peter Meilstrup's career trajectory is a testament to his dedication and expertise in the field of data science. With a keen interest in the applications of experimental psychology and visual perception, he has developed competencies that align well with the growing demand for nuanced understanding in user experience (UX) and behavioral metrics. Having worked in notable positions at leading organizations, he has amassed significant experience across various sectors. His role as a Software Engineer II at Microsoft allowed him to merge his software engineering skills with advanced data science concepts, contributing to the development of innovative solutions that enhance user experience on a large scale. Additionally, at Second Sight Medical Products, Peter applied his engineering knowledge to develop medical device technologies, marrying his passion for science with real-world applications that positively impact lives.
Prior to these significant roles, Peter contributed as a Research Associate at the University of Washington, where he translated theoretical principles into tangible research outcomes. His academic involvement has consistently informed his practical skills and vice versa, creating a strong feedback loop that enhances his capabilities as a data scientist. As an Undergraduate Research Fellow at Caltech, he engaged deeply in experimental design and technical research methodologies, laying the groundwork for a career dedicated to inquiry and impactful scientific contributions.