John Bochanski, Ph.D.

Astrophysicist and Data Science Leader

US-based, mission-driven data scientist with 20+ years of experience analyzing large, complex datasets and leading large and small interdisciplinary teams. I specialize in Python, SQL, and advanced analytics, including causal inference, regression, and machine learning to build models and metrics that inform high-stakes decisions.

Download Resume

About Me

I’m a data-driven scientist with 20+ years of experience analyzing large, complex datasets and leading interdisciplinary teams. I am an expert in scientific data analysis, with extensive experience in programming, large datasets, data visualization, and project management. I specialize in Python, SQL, and machine learning, with the ability to tell the story of disparate datasets to diverse audiences.

I’ve founded and chaired an academic department, managed technical projects from conception through delivery, and mentored faculty and students across computer science, physics, and astronomy. I enjoy translating complex quantitative work into clear, actionable insights for diverse stakeholders.

Outside of work, I enjoy getting into nature with my family, hosting star parties, and rooting for my Philly sports teams.

Some of the technologies and tools I work with:
  • Python
  • Monte Carlo Simulations
  • Modeling of Physical and Astrophysical Systems
  • SQL
  • Causal inference, regression, time-series analysis
  • numpy, scikit-learn, tensorflow, ML workflows
  • Git, Tableau, cloud environments
  • MLOps & reproducible data pipelines
  • Agile Methodologies

Experience

Associate Professor of Computer Science & Physics - Rider University
2014 – 2025
  • Founded and chaired the Computer Science & Physics department, growing it to 130+ undergraduate students across two degree programs and six full-time faculty.
  • Designed and led projects applying data science, machine learning, and analytics in educational and scientific settings.
  • Built reproducible data workflows and mentored students and faculty on statistical modeling, software engineering, and modern data tools.
  • Research Corporation for Science Advancement Scialog Fellow (2018, 2019); AI Faculty Fellow (2025).
Science Collaboration Co-Chair - Vera Rubin Observatory
2013 - 2020
  • Elected co-chair of the largest science collaboration within the Vera Rubin Observatory.
  • Managed an international collaboration of ~100 members, organizing meetings, white papers, and cross-team coordination.
  • Coordinated work between observational scientists, software engineers, and data analysts to define scientific roadmaps.
Postdoctoral Scholar & Researcher - MIT, Penn State, Haverford
2008 – 2014
  • Developed public, widely used image analysis and control software for multiple facility-class instruments.
  • Led peer-reviewed studies using some of the largest databases of low-mass stars ever assembled (TB-scale datasets).
  • Built and maintained analysis pipelines in Python for large-scale statistical modeling and uncertainty quantification.
  • Organized multi-day symposiums and large public open-house events.
Contributing Author - Sky & Telescope Magazine
2012 - 2019
  • Authored multiple online and print articles explaining recent astronomical results to a broad audience.
  • Wrote accessible summaries of complex research, emphasizing clear, engaging communication for non-specialists.

Education

2002 – 2008
Ph.D. in Astronomy
University of Washington
Dissertation research on large astronomical surveys and low-mass stars.
1998 – 2002
B.S. in Astronomy & Astrophysics
Villanova University
Magna Cum Laude; Phi Beta Kappa, Phi Kappa Phi, Sigma Pi Sigma; Goldwater Scholar.

Communication & Technical Impact

Publications
Publications Research
Publications
Complete lists (Orcid and Google Scholar) of my peer-reviewed publications, citations, and research impact.
TEDxSolebury
Public Talk Data & Astronomy
TEDxSolebury
Public talk on how modern astronomy and data analysis will reveal new insights about the universe.
Talks @ Google
Invited Talk Data at Scale
Talks @ Google
Invited Talk @ Google "Data-Driven Discovery" on large-scale astronomical datasets, statistical modeling, and robust data workflows.
Recent Media Appearances
Media
Recent Media Appearances
Discussing my LSST-DA work on ONNJ (August 2025)
Sky & Telescope Articles
Science Communication Writing
Sky & Telescope Articles
Articles written for Sky & Telescope Magazine, distilling recent astronomical results for the general public.

Achievements

AI Faculty Fellow
Selected as AI Faculty Fellow (2025), recognizing leadership in integrating artificial intelligence and data science into teaching and research.
RCSA Scialog Fellow
Twice selected as Scialog Fellow (2018, 2019), recognizing my innovation in time-domain and survey astrophysical research.
MIT SPOT Award (2009, 2010)
Recipient of MIT SPOT (Spontaneous Performance Award) recognition in 2009 and 2010 for outstanding contributions to the department as a postdoctoral scholar.
Asteroid 141414 Bochanski
Namesake of Asteroid 141414 (Bochanski), honoring contributions to astronomy and the study of low-mass stars.

Get in Touch

I’m seeking roles as a Data Scientist, Technical Lead, or Applied Scientist working with large, complex datasets. Excited to contribute to high-functioning teams. Feel free to reach out with opportunities or questions.
Email me