Lead Research Data Scientist
Prior to joining Research Computing in 2018, Geoffrey worked in industry as a Data Scientist at the largest public power utility in the country. He has an academic background in Astrophysics and spends his time working with faculty and students on data science and high-performance computing projects.
Geoffrey started his career as an undergraduate Physics student at Purdue in 2008. His passion in science remains primarily within Physics and Astronomy. His interest in computational science started at Purdue with large scale N-body simulations of galaxy formation. While at the University of Louisville his research and dissertation centered on automated signal processing of deep archival data. Geoffrey also developed software for modeling probabilities and statistics of populations of stars in our galaxy. He went on to Notre Dame for another two years working on his PhD in Near-Field Cosmology and Large Scale Survey Astronomy. While at Notre Dame he earned a reputation for caring about building better scientific software. He left the program early to pivot towards data science and industrial applications.
Geoffrey has been working on data science topics and high-performance computing applications since 2015. His primary responsibilities encompass advanced user support on data science, data processing, high-throughput computing, workflow management, and other topics. He consults with faculty and students on their projects and applications. He is a prolific builder of tools and automation.
- B.Sc., Physics, Purdue University (2013).
- M.Sc., Physics, University of Louisville (2015).
- Ph.D. (ABD), Astrophysics, University of Notre Dame (2017).
- Conference Tutorials: "Python 201: Building Better Scientific Software in Python" (Geoffrey Lentner, Lev Gorenstein, and Amiya K. Maji) in Practice and Experience in Advanced Research Computing Conference Series (PEARC 2020, 2021).
- Manage Hackathons: Computing Challenge Day: Data Science Challenge (2019, 2020, 2022).
- Organizer and regular participant in RCAC Coffee Hour Consultations.
- G. Lentner and L. Gorenstein. 2022. “HyperShell v2: Distributed Task Execution for HPC,” In Practice and Experience in Advanced Research Computing (PEARC '22). Association for Computing Machinery, New York, NY, USA, Article 80, 1–3. doi: 10.1145/3491418.3535138.
- T. Wu, S. Harrell, G. Lentner, A. Younts, S. Weekly, Z. Mertes, A. Maji, P. Smith, X. Zhu, 2021. “Defining Performance of Scientific Application Workloads on the AMD Milan Platform,” In Practice and Experience in Advanced Research Computing (PEARC '21). ACM, New York, NY, USA, Article 32, 1–4. doi: 10.1145/3437359.3465596.
- N. Sravan, D. Milisavljevic, J. Reynolds, G. Lentner, M. Linvill, 2020. “Real-time, Value-driven Data Augmentation in the Era of LSST”. Astrophysical Journal. vol. 897, pp. 127, April 2020. doi: 10.3847/1538-4357/ab8128.
- G. Lentner, A. Maji, and L. Gorenstein, 2020. “Python 201: Building Better Scientific Software in Python”. In Proceedings of the Con- ference on Practice and Experience in Advanced Research Computing (PEARC '20 Companion). ACM, New York, NY, USA, Article 7, 1. doi: 10.1145/3425306.3444778.
- A. Maji, L. Gorenstein, G. Lentner, 2020. "Demystifying Python Package Installation with conda-env-mod," IEEE/ACM International Workshop on HPC User Support Tools (HUST) and Workshop on Programming and Performance Visualization Tools (Pro- Tools), 2020, pp. 27-37, doi: 10.1109/HUSTProtools51951.2020.00011.
- G. Lentner, 2019. “Shared Memory High Throughput Computing with Apache ArrowTM”. In Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) (PEARC '19). ACM, New York, NY, USA, Article 119, 2 pages. doi: 10.1145/3332186.3335197.
- D. Carollo, T. C. Beers, V. M. Placco, R. M. Santucci, P. Denissenkov, P. B. Tissera, G. Lentner, S. Rossi, Y. S. Lee, J. Tumlinson. 2016. “The age structure of the Milky Way’s halo”. Nature Physics. (2016) doi: 10.1038/nphys3874.
- G. Lentner, 2015. “The Local Cygnus Cold Cloud and further constraints on a local Hot Bubble.” Electronic Theses and Dissertations. Paper 2213. doi: 10.18297/etd/2213.
- Workflow Automation Tools for Many-Task Computing (2022).
- Jupyter Kernels and HPC (2020).
- SNEWS Hackathon (May 2021): Tips and Ideas for Cleaner Code in Python
Other Activities and Fun Facts
- Started college as an English major
- Lived in ten US states (including Alaska — twice)
- Eagle Scout
- Plays Clarinet
- Enjoys premium bourbon