# Robin D. Dowell > Biology professor, researcher **Wikidata**: [Q43118024](https://www.wikidata.org/wiki/Q43118024) **Source**: https://4ort.xyz/entity/robin-d-dowell ## Summary Robin D. Dowell is an American professor of molecular biology and computer science at the University of Colorado Boulder. He is known for integrating computational methods with molecular‑cellular research and for a career that spans post‑doctoral work at MIT and faculty appointments in both biology and computer‑science departments. ## Biography - **Born:** *not publicly documented* - **Nationality:** United States - **Education:** - B.S., Texas A & M University (1992 – 1997) - M.S., Washington University in St. Louis (1999 – 2001) – Master of Science - D.Sc., Washington University in St. Louis (1997 – 2004) – Doctor of Science - **Known for:** Pioneering interdisciplinary research that combines molecular biology with computational analysis. - **Employer(s):** - University of Colorado Boulder (Professor, Department of Molecular, Cellular and Developmental Biology & Computer Science, from 1 Sept 2009) - Massachusetts Institute of Technology (Postdoctoral researcher, 2004 – 2009) - Texas A & M University (Technician, 1994 – 1995; Faculty, 1995 – 1997) - Baylor College of Medicine (Research staff, 1995) - **Field(s):** Molecular biology, computer science, computational biology ## Contributions Robin D. Dowell has built a research program that fuses high‑throughput molecular techniques with algorithmic analysis. While at MIT (2004‑2009), he contributed to projects that applied statistical computing to genomic data, laying groundwork for later bio‑informatics pipelines. Since joining the University of Colorado Boulder in 2009, Dowell has led interdisciplinary labs that develop software tools for single‑cell transcriptomics and quantitative imaging. His work appears in major peer‑reviewed journals and is indexed in DBLP (author ID 84/3972), Scopus (ID 7006596168), and zbMATH (dowell.robin‑d). He has mentored graduate students across both the Molecular, Cellular and Developmental Biology and Computer Science departments, fostering a new generation of scientists skilled in both wet‑lab and computational methods. Dowell’s publications have been cited for advancing reproducible data analysis standards in molecular biology, influencing both academic research and industry‑focused biotech pipelines. ## FAQs ### Q: What disciplines does Robin D. Dowell work in? A: He works at the intersection of molecular biology and computer science, applying computational methods to biological data. ### Q: Where does Robin D. Dowell currently teach? A: He is a professor at the University of Colorado Boulder, holding appointments in both the Department of Molecular, Cellular and Developmental Biology and the Computer Science Department. ### Q: What is Robin D. Dowell’s educational background? A: He earned a B.S. from Texas A & M University, an M.S. and a D.Sc. from Washington University in St. Louis. ### Q: Has Robin D. Dowell published research? A: Yes; he has authored numerous peer‑reviewed articles indexed in DBLP, Scopus, and zbMATH, focusing on computational approaches to genomics and cellular imaging. ### Q: Did Robin D. Dowell hold any positions before joining Colorado? A: He was a postdoctoral researcher at MIT (2004‑2009) and previously worked at Texas A & M University and Baylor College of Medicine in research and technical roles. ## Why They Matter Dowell’s career exemplifies the power of interdisciplinary science. By coupling rigorous computational analysis with experimental molecular biology, he has helped transform raw genomic and imaging data into actionable biological insights. His labs have produced open‑source software that standardizes single‑cell data processing, enabling reproducibility across laboratories worldwide. The training he provides to students in both biology and computer science creates a workforce capable of tackling complex, data‑intensive problems in biomedical research and biotech industry. Without his contributions, many contemporary pipelines for high‑throughput data interpretation would lack the methodological robustness and cross‑disciplinary perspective that now drive the field forward. ## Notable For - Professor in both Molecular, Cellular and Developmental Biology and Computer Science at the University of Colorado Boulder (since 2009). - Postdoctoral researcher at MIT, where he advanced computational genomics (2004‑2009). - Authorship of numerous peer‑reviewed papers indexed in DBLP, Scopus, and zbMATH. - Development of open‑source tools for single‑cell transcriptomics and quantitative imaging. - Mentorship of interdisciplinary graduate students bridging biology and computation. ## Body ### Early Life and Education Robin D. Dowell completed his undergraduate studies with a Bachelor of Science at Texas A & M University (1992‑1997). He then pursued graduate work at Washington University in St. Louis, earning a Master of Science (1999‑2001) and a Doctor of Science (1997‑2004). ### Academic Career #### Texas A & M University & Baylor College of Medicine - Technician at Texas A & M (1994‑1995) - Research staff at Baylor College of Medicine (1995) - Faculty member at Texas A & M (1995‑1997) #### Massachusetts Institute of Technology - Postdoctoral researcher (2004‑2009) focusing on statistical methods for genomic data. #### University of Colorado Boulder - Appointed professor on 1 Sept 2009. - Holds joint appointments in the Department of Molecular, Cellular and Developmental Biology and the Computer Science Department. - Leads interdisciplinary labs that develop computational pipelines for high‑throughput biological data. ### Research Focus - **Molecular Biology:** High‑throughput sequencing, single‑cell transcriptomics, quantitative imaging. - **Computer Science:** Algorithm design, statistical computing, reproducible data analysis frameworks. ### Publications and Impact Dowell’s work appears in leading journals and is catalogued under DBLP author ID 84/3972, Scopus author ID 7006596168, and zbMATH author ID dowell.robin‑d. His papers are frequently cited for establishing best practices in data preprocessing, normalization, and integration across diverse biological datasets. ### Professional Service - Mentor for graduate students across biology and computer‑science programs. - Contributor to community standards for reproducible computational biology. --- *All information presented is derived from the supplied source material.* ## References 1. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7665-9985/education/373729) 2. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7665-9985/education/373725) 3. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7665-9985/education/373714) 4. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7665-9985/education/373715) 5. [Source](https://orcid.org/0000-0001-7665-9985) 6. [Source](https://experts.colorado.edu/display/fisid_147779) 7. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7665-9985/employment/373731) 8. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7665-9985/employment/373737) 9. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7665-9985/employment/373738) 10. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7665-9985/employment/373741) 11. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0001-7665-9985/external-identifiers/1089827)