SC 2024 Workshop

Jeff Larkin is the Director in of HPC Architecture in NVIDIA’s HPC Software Product team, where he leads teams responsible for HPC programming models and standards and also technical marketing engineering. He is passionate about the advancement and adoption of parallel programming models for High Performance Computing. He was previously a member of NVIDIA’s Developer Technology group, specializing in performance analysis and optimization of high performance computing applications. Jeff is also the chair of the OpenACC technical committee and has worked in both the OpenACC and OpenMP standards bodies. Before joining NVIDIA, Jeff worked in the Cray Supercomputing Center of Excellence, located at Oak Ridge National Laboratory. Jeff holds a B.S. in Computer Science from Furman University and a M.S. in Computer Science from the University of Tennessee, where he was a member of the Innovative Computing Lab.

Gladys Andino, Ph.D., is the IT-Research Computing’s Strategic Services and Education Manager. She leads strategic planning and user training programs, coordinating workshops and tutorials to meet the dynamic needs of UVA’s computational research community. Gladys also manages a team of student workers, enhancing IT-Research Computing’s efficiency and providing early exposure to HPC and scientific computing.

As Founder and Chair of Purdue Women in HPC (2016-2019) and Virginia Women in HPC (since 2021), Gladys advocates for gender diversity, equity, and inclusion. She has significantly grown the Virginia Women in HPC program, collaborating with seven Virginia institutions to enhance diversity and inclusivity in technology. Gladys organizes virtual events with distinguished technical speakers, fostering a supportive community.

Nicole Fisk is the Global Public Sector Lead for AI within HPE’s High Performance Compute and Artificial Intelligence Business Unit. She is responsible for working with public sector organizations to understand ever-changing requirements and challenges associated with pursuing and deploying AI. In this role, she works with HPE’s engineering teams to incorporate those requirements into our product strategy and collaborates with marketing and strategy teams to translate HPE’s AI capabilities into meaningful outcomes for customers.

Before joining HPE, Nicole worked with Cray as their lead AI Business Development manager in North America supporting strategic initiatives in AI. She joined Cray after 9 years with IBM helping U.S. Federal agencies leverage existing and emerging technologies to solve complex IT challenges and to position themselves for next generation advanced analytics, AI and machine learning capabilities.

Lúcia Drummond is a Full Professor at the Institute of Computing, Fluminense Federal University (UFF). Her research focuses on High-Performance Computing, Cloud Computing, and Parallel and Distributed Computing. She has published over 150 papers in prestigious conferences and journals and has supervised numerous master’s and Ph.D. students, including several in collaboration with French universities such as Sorbonne, Bordeaux, and Avignon.

Lúcia has served on program committees for major conferences like HPDC, ICS, IEEE CLUSTER, CCGRID, Europar, IPDPS, and Supercomputing. She was Program Chair of the IEEE/SBC International Symposium on Computer Architecture and High-Performance Computing (SBAC) in 2016 and 2020, which is now in its 36th edition, and has been on the steering committee since 2024.

From 2019 to 2023, she coordinated the Special Commission on Computer Architecture and High-Performance Processing of the Brazilian Computer Society (SBC), and she continues to serve on its Management Committee. She is also involved in an associate research collaboration with INRIA Bordeaux, France, as well as in a large-scale project connecting UFF with Petrobras, the Brazilian oil company. In addition, Dr. Drummond is an Associate Editor of Future Generation Computer Systems (FGCS).

Dr. AJ Lauer is the founder of Thriving Ibis Leadership Solutions. She is a leadership and diversity educator specializing in the development of science, technology, engineering, and mathematics (STEM) professionals. She has two decades of experience working in higher education and nonprofit research where she has held diverse professional roles, including running a residence hall, leading an educational exhibit design project, and coaching and training C-suite staff.

Dr. Chia-Lee Yang is a Principal Engineer at Taiwan’s National Center for High-Performance Computing (NCHC) and an interdisciplinary researcher specializing in the integration of computational techniques within social science research, including data mining and decision-making processes. She is committed to promoting female participation in high-performance computing (HPC) and serves as the principal investigator for various gender and technology research projects. Dr. Yang also founded the Women in High-Performance Computing (WHPC) Taiwan chapter. Her current research focuses on investigating gender and age bias in large language models.

K. Grace Johnson is a Senior Research Scientist at Hewlett Packard Labs where she works on integrating quantum computing with supercomputing. She received her PhD in Chemical Physics in 2023 from Stanford University where she studied with Prof. Todd Martinez. During her PhD, Grace was a U.S. Department of Energy Computational Science Graduate Fellow, and in her research developed frameworks to parallelize and accelerate quantum chemistry simulations for HPC as well as simulating quantum circuits using tensor network methods. Her current work at HPE aims to develop hybrid quantum/classical approaches to solve challenging real-world problems in the near term, focusing on partitioning and distributing quantum workloads. Grace is originally from Salt Lake City, Utah but now calls the SF Bay Area home.

Victoria Uribe is a Mexican American Ph.D. Candidate in Applied Mathematics at Arizona State University. Her current research interests include inverse problems, numerical linear algebra, machine learning, and high performance computing. In particular, she is interested in row-action methods for solving large-scale inverse problems. Raised in Paradise, California, she received her B.S. in Applied Mathematics from California State University, Chico in 2016. Before starting graduate school, she briefly attended the University of California, Berkeley School of Law before deciding to continue her education in Applied Mathematics instead.

Victoria is currently working in ASU’s HPC-systems-adjacent Computational Research Accelerator and serving as the Vice President for the Women in HPC (WHPC) at ASU student chapter. She hopes to work as a Research Software Engineer after completing her Ph.D.

Jencey Dole is a mathematics undergraduate student at Arizona State University, working in the HPC-systems- adjacent Computational Research Accelerator as a student researcher and software engineer. Jencey has been driving a quantum computing project that evaluates the efficiency of quantum annealing algorithms in solving NP-hard combinatorial optimization problems. She is currently the only member of the student team involved in a collaborative project between ASU and Dell Inc.

Jencey is currently serving as President in ASU’s Women in HPC (WHPC) student chapter. After her Bachelor’s, Jencey plans on pursing her Ph.D. to continue her research in HPC-enabled applied and computational mathematics, specifically in quantum computing. She hopes to one day have a tenure home at a university.

Jencey was awarded travel to this conference by the High Performance Computing Immersion Program (HPCI) for SC24.

Dr. Aishwarya Natarajan is a Research Scientist in the Artificial Intelligence Research Lab at Hewlett Packard Labs, where she focuses on building the next generation hardware accelerators based on in-memory computing primitives and novel technologies, for explainable machine learning workloads. She received her M.S. and Ph.D. in Electrical and Computer Engineering from Georgia Institute of Technology in 2016 and 2021 respectively. Her thesis involved the design of low-power bio-inspired systems built from fundamental blocks of neurons and synapses through analog and mixed signal integrated circuits and systems. Her research interests encompass building energy-efficient algorithms and systems through neuromorphic computing and programmable structures. She is also a recipient of the Analog Devices Outstanding Student Designer award in recognition of excellence in contribution to IC Design.

Dr. Vijayalakshmi Saravanan is a distinguished scholar and accomplished researcher in computer science and engineering, currently serving as an Assistant Professor at the University of Texas at Tyler and visiting faculty at Brookhaven National Lab, NY, USA. Before joining the University of Texas at Tyler, Dr. Saravanan held several notable academic positions. Dr. Saravanan began her research career as a Postdoctoral Associate at the University at Buffalo and the University of Waterloo, under the prestigious fellowship award from “Schlumberger Faculty for the Future”, 2015 to 2017. She earned her Ph.D. through the Erasmus Mundus EU-Government Fellowship at Mälardalen University in Sweden, participating as a research exchange student. Her research interests include high-performance computing (HPC), AI, ML, and power-aware processor design. Dr. Saravanan is actively involved in the research community, serving on program committees for prestigious conferences and journals such as the SC 23, &24 Grace Hopper Celebration, ACM SIGCSE, and Springer publications. Dr. Saravanan has also made significant contributions as a lead editor for Pattern Recognition Letters, and CRC Press Taylor & Francis. Her achievements have earned her the SRP-HPC Fellowship (2022-2023), the SoBigData++ Diversity and Inclusion award, and a competitive research grant FAIR award of $750,000 from the U.S. Department of Energy as PI. She is an esteemed senior member of IEEE, ACM, CSI, and ACM Distinguished Speaker. Dr. Saravanan has chaired the IEEE Women in Engineering (WIE) Affinity Group and the National Postdoctoral Association (NPA) Annual Meetings and is a valued Board Member of the ACM N2WOMEN community.

Ying Zhang has MS degrees in Computer Science and Remote Sensing. She is currently the IT Manager for AI and Research Software Engineering at Research Computing, a department in Information Technology at University of Florida. She and her team work with faculty research groups and provide consultations in AI research and software development in all research disciplines. The team also design and deliver AI training courses at different competency levels for UF and its partner institutions. She also assists researchers in running high performance computing (HPC) applications with high efficiency on HiPerGator – UF’s supercomputing clusters. Prior to joining UF, she worked at the University of Illinois at Urbana-Champaign and the Renaissance Computing Institute as a Senior Research Programmer. She developed software tools for performance analysis, tuning, and optimization for parallel applications. She conducted performance simulations for HPC applications in various scientific disciplines on supercomputing clusters at major DOE laboratories.

Aarushi Jain is a Software Development Engineer 2 (SDE2) at AMD, on the ML Framework team. She focuses on ML inference acceleration and optimization, specifically with MIGraphX.

Mikhayla Clothier received her bachelor’s degrees in chemistry and mathematics from Erskine College in 2022. She is currently pursuing a Ph.D. in chemistry at the Georgia Institute of Technology. She is active in the Women+ in Chemistry, a student-led organization helping to empower women and underrepresented gender minorities in chemistry. She also currently works as the Head Teaching Assistant (TA) for the introductory chemistry labs, in which she helps to manage the graduate and undergraduate TAs employed by the university to teach introductory labs for three chemistry classes. Her research is currently focused on the development of theoretical chemistry methods, applying quantum mechanics to the calculation of non-equilibrium electron and spin dynamics with a focus on the study of spin transport properties.

Si Chen is a Ph.D. student in Computer Science, under the supervision of Dr.Avani Wildani. She received her BS and MS in Electronic and Information Engineering at Huazhong University of Science and Technology in China. Her research interest is applying machine learning techniques to automatically characterize the HPC workloads and optimize HPC application design across a heterogeneous hardware environment.