Ayesha Afzal
Ayesha Afzal is a researcher working towards the PhD at the professorship for High Performance Computing at Erlangen National High Performance Computing Center (NHR@FAU) in Germany.
She holds a master’s degree in computational engineering from the Friedrich Alexander University, Erlangen-Nürnberg, Germany, and a bachelor’s degree in electrical engineering from the University of Engineering and Technology, Lahore, Pakistan.
Her PhD research lies at the crossroads of analytic performance models, performance tools and parallel simulation frameworks, with a focus on first-principles performance modelling of distributed-memory parallel programs in HPC. She also conducts research in multi-core and parallel architectures, parallel computing and algorithms, parallel programming models, modern C++, and domain-specific languages.
Ayesha contributes to scientific community events as a vice chair (p@SC24, IEEE Computer Society Germany Chapter), a chair (publicity@ICPP24, WHPC posters@ISC24, PERMAVOST@HPDC24+23, WHPC mentoring@SC23), a program committee member (SC, CLUSTER, ICPP, HPCCT, CSTA, P3HPC, Euro-Par WHPC session, IEEE TechEthics ad hoc), a journal reviewer (TPDS), a panelist (NHR23 conference), a communication liaison (SC25), a section lead (IEEEXtreme Region 8 Germany section) and an active speaker.
She has authored numerous peer-reviewed articles, received the Best Short Paper Award 2023 in the PMBS (Performance Modeling, Benchmarking, Simulation) workshop at the Supercomputing Conference, and scored first in the ISC PhD Forum Award 2021, which honors outstanding PhD work. She was named in the Top 100 Future Leaders Role Model List in 2022 and 2023/24 supported by Yahoo Finance and YouTube, respectively, and won WeAreTheCity’s Global Award for Achievement 2023.
HPC-AI Current and Future Leaders
Ayesha Afzal, Researcher, Erlangen National High Performance Computing Center (NHR@FAU)
What was your first introduction to advanced computing?
My introduction to advanced computing was not a linear path but rather shaped by a diverse set of interests. Growing up, I had a natural curiosity for solving puzzles, which eventually evolved into a passion for engineering, leading me to earn an EE degree in Pakistan. However, it wasn’t until I transitioned to computational engineering for my master’s at the Friedrich-Alexander-Universität Erlangen-Nürnberg that I truly realized the power of combining mathematics, computer science, and engineering. This interdisciplinary approach ultimately led me to HPC, where I could leverage both computational power and algorithmic sophistication to solve complex, real-world problems.
The pivotal moment came during my master’s thesis, “The Cost of Computation: Metrics and Models for Modern Multicore-based Systems in Scientific Computing,” which explored performance and energy models, multicore architectures, and energy efficiency in HPC. It was an eye-opening experience that connected theoretical work to real-world applications, from energy-efficient supercomputing to cutting-edge research, and made me truly grasp the importance of pushing computational limits. This experience sparked my decision to pursue a PhD in this area.
What year was that?
My introduction to advanced computing began in 2013 during my master’s studies, but it was my master’s thesis in 2015 that truly deepened my involvement with HPC.
What is your current title?
I am currently a researcher (German title: ‘Wissenschaftlicher Mitarbeiterin’) at the Erlangen National High Performance Computing Center (NHR@FAU).
How long have you been with your organization and in that role?
I have been with NHR@FAU for several years, contributing to various pivotal initiatives, particularly in energy-efficient computing, performance engineering, and advanced simulation frameworks. I have been in my current role for over six years.
Is there an aspect of your work that you are particularly proud of? Have you had a “Eureka” moment that you would like to share?
Instead of a singular “Eureka” moment, my work has been shaped by a series of smaller, yet impactful, moments. Whether it’s developing analytical models, optimizing complex algorithms, refining simulation frameworks, or tackling performance bottlenecks, each contributes to advancing energy-efficient computing and performance engineering. The smaller wins in my research have been equally rewarding and motivating, earning recognition such as the Best Paper Runner-up Award at IEEE TPDS, the First-place Ph.D. Forum Award ISC conference, the Best Short Paper Award at the SC PMBS workshop, the Best Research Poster Finalist at SC conference and the WeAreTheCity Global Award for Achievement, and they continue to fuel my passion for progress and innovation in the field.
Who or what has influenced you the most to help you advance your career path in this advanced computing community? Is there someone you would like to recognize?
To answer who has influenced me, the influence of my late father, a mathematician, has been profound in shaping my independent thinking and analytical mindset, which has guided me throughout my journey. Professionally, I’ve been inspired by the diverse and interdisciplinary nature of the HPC community. I’ve been fortunate to be surrounded by a network of incredible mentors, experts and colleagues, many of whom I’ve met throughout my academic and professional career, as well as through international collaborations, particularly at events like the Supercomputing Conference. These individuals have been incredibly generous with their time and guidance, always pushing me to take on larger challenges and strive for excellence. There are too many to name, but I am deeply grateful for each of them, and I owe much of my growth to their belief in me and the encouragement I received early on. From my experience, I’ve learned that these experts have often faced similar challenges and are always willing to share their advice.
To answer what has influenced me, my father’s teachings instilled in me the confidence to pursue unconventional paths and challenge established norms. Over time, I’ve come to embrace the idea that it’s okay not to have a clear path at the outset of a project — what matters is the learning experience throughout the journey itself. My curiosity, combined with a willingness to step out of my comfort zone and take risks, has been a key driver of my growth within the advanced computing community. Whenever I encounter something I don’t know, I view it as an opportunity to innovate, make a change, and pursue something new.
What is your passion related to your career path?
Solving complex real-world problems by advancing computational performance and energy efficiency!
As AI and HPC technologies scale, the energy consumption of HPC-AI systems will grow exponentially, and I’m committed to developing innovations that minimize their environmental impact. I’m particularly focused on optimizing algorithms and exploring ways to improve hardware efficiency to make computational power more accessible, efficient, and environmentally responsible.
Additionally, I work on building the performance simulation framework that helps performance engineers understand the hardware-software interaction, which is key to optimizing HPC systems. I work at the intersection of cutting-edge research and practical HPC applications, playing a pivotal role in shaping how computational research aligns with the needs of both industry and academia.
To further contribute to these topics, I also organize workshops such as EESP at ISC and PERMAVOST at ACM HPDC, which focus on energy and performance issues in HPC and provide a platform for researchers and industry professionals to share insights and collaborate on innovative solutions.
What does it take to be an effective leader in HPC and AI?
I’m still learning the ropes, but in my opinion, effective leadership in HPC and AI requires a blend of technical expertise, visionary thinking, and strong team collaboration. From what I’ve experienced, the best leaders have a clear vision, even if they don’t have all the answers at first. They stay modest, know when to seek guidance, and are adept at collaborating across organizations and fields. They understand that it takes time to identify and address root causes, rather than relying on quick fixes.
Leadership is about supporting others and encouraging risk-taking, as what matters is how you bounce back and learn from mistakes. It’s crucial to foster an environment where people feel empowered to contribute their unique perspectives, and where continuous learning and innovation are prioritized. Effective leaders are also open to new approaches, challenge their teams to think outside the box, push boundaries, and guide them through challenges. The HPC-AI integration requires leaders with both a broad perspective and deep expertise in key areas. They must be adaptable, explore interdisciplinary solutions, and always strive for global excellence.
What are your thoughts on how our countries build a stronger and deeper pipeline of talented and passionate HPC and AI professionals?
Great question! While AI enthusiasm is strong, it must be paired with a clear understanding of how to integrate AI with HPC. Building a deeper pipeline of HPC and AI talent requires a multi-faceted approach: from ensuring that educational systems prioritize computational thinking and problem-solving from an early age to fostering a more diverse workforce. We need more initiatives and interdisciplinary programs that connect industry and academia, providing students with hands-on experiences, training, mentorship, and real-world problem-solving opportunities.
At the same time, it’s essential to encourage diverse perspectives, eliminate restrictive criteria in these initiatives, and foster collaboration across global efforts. The more we highlight the rewarding and impactful nature of working in HPC and AI through visibility, clear career pathways, and open-source projects, the more we can inspire diverse and passionate individuals to pursue careers in this field.
What changes or challenges do you see for the HPC-AI community in the next five-10 years?
That’s a pressing issue! Looking ahead, the next five-10 years for the HPC-AI community will face significant challenges in managing the hyper-exponential increase in computing demand driven by AI, particularly with the stagnation of Moore’s Law and the energy crisis posed by power-hungry GPUs. Balancing performance needs with energy efficiency while maintaining sustainability in a resource-constrained environment will require ongoing research, development, and cross-industry collaboration.
However, emerging technologies offer promising solutions, and advancements in AI-HPC integration could dramatically accelerate scientific progress. Strengthening information exchange between HPC and AI communities and integrating HPC expertise into AI workflows will accelerate progress in both fields. Additionally, as AI boundaries are pushed, ethical considerations such as fairness in machine learning algorithms and data privacy will become increasingly important. The HPC and AI communities must prioritize these challenges while continuing to innovate in ways that address both technological and societal needs.
Would you like to share any personal information with the HPC-AI community?
Outside my research, I cherish spending time with my family — eight-month-old Ibrahim and nine-year-old Abrish, along with my husband Hamad. I also enjoy watching movies and meeting new people — especially those passionate about making strides in STEM fields.
