Zoe Banks is a sophomore studying Computer Science at Austin Community College. When she’s not studying, she might be found out exploring the sights and sounds of Austin with her dog, Chip. Growing up, her role model was her mother.

Cierra Cage is a junior at Southern University A&M College, where she’s studying Electrical Engineering. She lists author Maya Angelou as her role model. When her engineering classes are finished, Cierra enjoys spending time in nature, reading, and socializing with family and friends (observing proper social distance rules, of course).

Erin Burba, who recently graduated from Northeastern University with a degree in Computer Science and Computer Engineering, is returning to C4C as a mentor. She spends her time outside of work playing Dungeons and Dragons over Zoom, which is only making it harder to be less of a night owl, but at least she has books, documentaries, or ‘ridiculous’ TV series to keep her company. Erin is happy to support this year’s C4C cohort, because she believes strongly in the program’s goal of bringing together people of different backgrounds to use technology to support their own communities. She always looked up to her older cousins, who have now grown into unique, successful and well-adjusted adults, so this has given Erin the courage to follow her own path. We can’t wait to see where it leads!

Erika Bailon is returning to C4C as a mentor, after participating in C4C at SC18, and recently graduating with a degree in computer science from the University of Colorado Boulder. With her new career at NASA JPL, it’s no surprise that she’s a night owl who likes to play ‘math games’ on her phone, or find some friends to play Rummikub. When she was a student participating in the challenge, Erika experienced first-hand the life changing moments that happen during C4C. She noted that many students, who might have forgotten why they wanted a career in STEM, walked away after the program with a new purpose, excited to make a change in the world. Erika also had an amazing mentor at C4C, who became a good friend. We know that Erika will offer the same kind of support to this year’s students.

Roberto Camacho is also returning to C4C as a mentor, after participating in C4C and Advanced Computing for Social Change (ACSC) in previous years. In 2019, he completed his PhD in Computer Science at the University of Texas at El Paso. After completing his dissertation, he went from being a night owl to an early riser, so he can get to work on time. In his free time, he likes to play Rummikub – he and Erika should get a game together! Roberto’s parents were his inspiration growing up, demonstrating their commitment to hard work and education, which certainly made an impact on him. Participating in C4C made Roberto realize that certain things that he takes for granted can have an effect on others, and that has made him more empathetic. We’re sure the student cohorts at this year’s C4C will appreciate his support.

Edgar Chavez, another former C4C participant-turned-mentor, graduated from California State University Los Angeles with a degree in Civil Engineering. In his free time, he also plays Dungeons and Dragons (like Erin), and can’t decide whether it’s better to be a night owl or a morning person – either way, there just aren’t enough hours in the day. Edgar’s hero growing up was a character called ‘Goku’ from the Dragon Ball Z anime series, from whom he learned to push through any boundaries or obstacles that may appear. Edgar is a huge fan of everything that ACSC and C4C stand for, combining social issues with data science, raising awareness and teaching students how to use raw data to make an informed argument. We’re so pleased to have him back, to support the students and create a richer experience for them.

Melia Soque, a student at Chaminade University of Honolulu, participated in ACSC in the summer of 2020, and is now returning as a C4C mentor. When she’s not studying, she likes to play Monopoly – and has a collection of different themed versions of the game, including M&Ms and surfing. Like so many of our other mentors, Melia is a night owl, and can often be found snacking and binge-watching different TV series. Her role model growing up was (and is) her father, who continues to model humility, hard work, and perseverance. Melia came back to C4C because she gained so much knowledge and awareness of the issues facing society, and was able to collaborate and connect with people to apply Data Science to find solutions. That sounds like a perfect advertisement for C4C!

Regina Dominguez, who is studying math and computer science at the University of Guam, was a C4C participant at SC19, and is excited to be returning as a mentor. She tends to be most productive in the late night and early morning hours, when there are fewer distractions. Otherwise, she could wind up down the rabbit hole of the internet, immersed in pop culture, new music, and TV shows. She can spend hours playing Mancala – a board game that looks simple but relies on strategy and problem-solving – with friends or in an app. Regina’s sister inspired her to try harder, influencing her work ethic, ambition, and opportunities. She’s ready to provide support and guidance to this year’s cohort of C4C students, offering the same kind of mentoring that she received last year.

Qwynci Bowman (pronounced “Quincy”) is a sophomore at Lewis and Clark College in Oregon, where she’s studying Environmental Law and Policy. When she’s not in class, or exploring the edible plants & fungi around campus, you might find her playing bluegrass music on her fiddle. Environmental science is a long way from Qwynci’s first ambition, which was to be the best (fastest) professional eater in the country! We’re glad she moved on from that to participating in C4C, where her nimble fingers will come in handy helping her team with data analysis and visualization.

Chenoa (Nona) Faletoi, who participated in last year’s ACSC, is studying Data Science at Chaminade University of Honolulu. She decided to serve as a C4C mentor because she wants to help the students understand that although research and computer science are two very different fields, combining them into data science is a valuable skill, and can help them have an impact in any field. Nona’s favorite game is Uno, but even a night owl like her sometimes has to use the time to do homework! She prides herself on being kind, helpful, and understanding, which will be greatly appreciated by the C4C students.

Lorena Barba (George Washington University) will explore the need for trustworthy computational evidence through transparency and reproducibility. With the explosion of new computational models for vital research, including COVID-19, applications that are of such importance to society highlight the requirement of building trustworthy computational models. Emphasizing transparency and reproducibility have helped us build more trust in computational findings. How should we adapt our practices for reproducibility to achieve “unimpeachable provenance”, and reach full accountability of scientific evidence produced via computation?

Shekhar Borkar (Qualcomm Inc.) will speak on the future of computing in the so-called “post Moore’s law era.” While speculations about the end of Moore’s law have created some level of fear in the community, this ending may not be coming as soon as we think. This talk will revisit the historic predictions of ‘the end’, and discuss promising opportunities and innovations that may further Moore’s law and continue to deliver unprecedented performance for years to come.

Dalia A. Conde (University of Southern Denmark) will offer a presentation on fighting the extinction crisis with data. With biodiversity loss identified by the World Economic Forum as one of humanity’s greatest challenges, computational methods are urgently needed to secure a healthier planet. We must design and implement effective species conservation strategies, which rely on vast and disparate volumes of data, from genetics and habitat to legislation and human interaction. This talk will introduce the Species Knowledge Index initiative, which aims to map, quantify, analyze, and disseminate open information on animal species to policy makers and conservationists around the globe.

Tom Conte (Georgia Tech) will examine HPC after Moore’s law. Whether Moore’s law has ended, is about to end, or will never end, the slowing of the semiconductor innovation curve has left the industry looking for alternatives. Different approaches, beyond quantum or neuromorphic computing, may disrupt current algorithms and software development. This talk will preview the road ahead, and suggest some exciting new technologies on the horizon.

Marissa Giustina (Google LLC) will share the challenges and recent discoveries in the development of Google’s Quantum computer, from both the hardware and quantum-information perspectives. This prototype hardware holds promise as a platform for tackling problems that have been impossible to address with existing HPC systems. The talk will include recent technological developments, as well as some perspective for the future of quantum computing.

Patrick Heimbach (The University of Texas at Austin) will discuss the need for advanced computing to help solve the global ocean state estimation problem. Because of the challenge of observing the full-depth global ocean circulation in its spatial detail, numerical simulations play an essential role in quantifying patterns of climate variability and change. New methods that are being developed at the interface of predictive data science remain underutilized in ocean climate modeling. These methods face considerable practical hurdles in the context of HPC, but will be indispensable for advancing simulation-based contributions to real world problems.

Simon Knowles (Graphcore) will discuss the reinvention of accelerated computing for artificial intelligence. As HPC changes in response to the needs of the growing user community, AI can harness enormous quantities of processing power – even as we move towards power-limited computing. To balance these needs, the intelligence processor (IPU) architecture is able to capture learning processes and offer massive heterogeneous parallelism. This ground-up reinvention of accelerated computing will show considerable results for real applications.

Ronald P. Luijten (Data Motion Architecture and Consulting GmbH) will offer a presentation on data-centric architecture of a weather and climate accelerator. Using a co-design approach, a non-Von-Neumann accelerator targeting weather and climate situations was developed in tandem with the application code to optimize memory bandwidth. This also led to the filing of a patent for a novel CGRA (Course Grain Reconfigurable Array) layout that reflects grid points in the physical world. The talk will include benchmarks achieved in the project, and a discussion of next steps.

Catherine (Katie) Schuman (Oak Ridge National Laboratory) will introduce us to the future of AI and HPC, in the form of neuromorphic computing and neural accelerators. These two new types of computing technologies offer significant advantages over traditional approaches, including considerably increased energy efficiency and accelerated neural network-style computing. This talk will illustrate the fundamental computing concepts involved in these new hardware developments, and highlight some initial performance results.

Compton Tucker (NASA Goddard Space Flight Center) will speak on satellite tree enumeration outside of forests at the Fifty Centimeter Scale. Non-forest trees, which grow isolated outside of forests, and are not well documented, nevertheless play a crucial role for biodiversity, carbon storage, food resources, and shelter for humans & animals. This talk will detail the use of HPC and machine learning to enumerate isolated trees globally, to identify localized areas of degradation, and quantify the role of isolated trees in the global carbon cycle.

Cliff Young (Google LLC) will entertain the question of whether we can build a virtuous cycle between machine learning and HPC. While machine learning draws on many HPC components, the two areas are diverging in precision and programming models. However, it may be possible to construct a positive feedback loop between them. The Tensor Processing Unit (TPU) could provide opportunities to unite these fields to solve common problems through parallelization, mixed precision, and new algorithms.