News and Events

ICDS Events

ICDS hosts a wide range of events, from training sessions on using our high-performance computing system to seminars about the latest topics in computational research. Here, you will find a list of upcoming ICDS events, as well as other events that may be of interest to the computational and data sciences community. Sign up for our mailing list to receive alerts about our events.

Want to learn what ICDS researchers are working on? Check out our Seminar series.

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New User Training

Date: Wednesday, January 29–Thursday, April 2

Location: 223 Computer Building

Learn the basics of working in the ICDS-ACI environment. Note: The April 2 edition of this training will be available via Zoom video conferencing only..

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Seminar: Embracing uncertainty in Earth system modeling to assess climate change risks

Date: Monday, March 23

Time: 4:00 p.m.–5:00 p.m.

Location: Online:

Chris Forest, ICDS associate and professor of climate dynamics, will present a seminar, "Embracing uncertainty in Earth system modeling to assess climate change risks," as part of the Earth and Environmental Systems Institute's EarthTalks Series. Join the talk at when it begins.

Data Science Community Talks

Date: Monday, March 30

Time: 10:00 a.m.–11:00 a.m.

Location: Online:

Join the Penn State data science community online (via Zoom) for two 13-minute talks from researchers leveraging advanced data science techniques in their work. "Pathways of combining process-based knowledge with deep learning for hydrologic modeling" Chaopeng Shen, Associate Professor, Civil and Environmental Engineering Abstract: Here I demonstrate selected pathways, out a many, to combine the power of both machine learning and process-based knowledge in improving our predictive capability of hydrologic variables. Compared to purely data-driven models, process-based models (PBM) can produce seamless solutions of observed or unobserved hydrologic variables at continental scales. However, a longstanding difficulty was to effectively and efficiently obtain parameters for PBMs. Here we show the vastly superior efficiency of a deep-learning-based parameter estimation framework that is based on a completely different paradigm of parameter estimation. We can gain five orders of magnitude of computational savings in calibration/training while achieving better calibrated parameters using the new framework. In addition, we comment on other forms of physics-informed neural networks. "My Journey to Dynamical Systems Modeling as a Behavioral Data Scientist" Sy-Miin Chow, Professor, Human Development and Family Studies Abstract: Dynamical systems models have historically been workhorses of the physical sciences and applied mathematics, but have begun to gain traction in statistics, and more recently, in the behavioral sciences. The recent influx of intensive longitudinal data from wearable devices, smartphones, Global Positioning System (GPS), and other sensors has introduced a pressing need, and also unique opportunities for developing novel data science approaches to examining the systems dynamics of individuals, family systems, social networks, and their interplay with environmental factors. In this talk, I will highlight some of my current work and ideas for future collaborations utilizing intensive longitudinal health data from individuals and family systems. Join the Talks on Zoom

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Intermediate HPC Training

Date: Wednesday, April 1–Wednesday, April 1

Go beyond the basics of working in the ICDS-ACI environment. NOTE: April 1 session will be offered via Zoom video conferencing ONLY.  

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Getting Your Software Running on ICDS-ACI

Date: Tuesday, April 7

Learn the basics of using your software in the ICDS-ACI environment. Attend in person, or view remotely via Zoom video conferencing. Offered on multiple dates: February 6 & April 7.

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SEA’s Improving Scientific Software Conference 2020

Date: Monday, April 27–Friday, May 1

Location: NCAR Center Green Campus, Boulder, CO

The 2020 annual SEA’s Improving Scientific Software conference will take place in Boulder, CO at the NCAR Center Green Campus from the afternoon of Monday April 27th to Friday May 1st

We are soliciting talks, tutorials and papers on Improving Scientific Software related to any of the following: Influence of computer architecture on scientific software design, including but not limited to:
  •  Modern architectures (such as GPU, ARM, etc)
  • Post-modern architectures (such as Quantum Computing, Neuromorphic, etc)
  • Extreme Heterogeneity (intra-node and inter-system)
  • Edge computing
  • Communication/computation overlap
  • Performance, Portability & Productivity
  • Modern tools for
  • Data Analysis, Processing and Visualization
  • Scientific Workflows: Purpose and Product Review.
  • Machine learning for Scientific Computing
  • Containers in scientific software
  • Leveraging Cloud Computing Resources for HPC Development and Operations

PEARC 2020

Date: Sunday, July 26–Thursday, July 30

Location: Portland, OR

The Practice and Experience in Advanced Research Computing (PEARC) Conference Series is a community-driven effort built on the successes of the past, with the aim to grow and be more inclusive by involving additional local, regional, national, and international cyberinfrastructure and research computing partners spanning academia, government and industry. The PEARC Conference Series is working to integrate and meet the collective interests of our growing community by providing a forum for discussing challenges, opportunities and solutions among the broad range of participants in the research computing community. The PEARC Conferences are organized by a group of dedicated volunteers from the community and are sponsored by the Association for Computing Machinery (ACM), the world’s largest educational and scientific computing society.

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