SCW75 launches to recognise the architects of scientific computing’s new era

Scientific computing is no longer confined to specialist computing centres. Across laboratories, engineering teams, pharmaceutical companies and research-intensive industries, advanced computing infrastructure is becoming central to how discovery, simulation and innovation are delivered.

Today, Scientific Computing World launches the inaugural SCW75 — a new recognition programme celebrating 75 of the most influential figures driving this transformation.

Bringing together leaders from high-performance computing (HPC), AI infrastructure, simulation, laboratory informatics, computational engineering and research computing, the SCW75 highlights the individuals translating increasingly complex technology into practical scientific and engineering outcomes.

The launch comes at a time of unprecedented investment across AI and scientific computing infrastructure. According to Hyperion Research, the HPC, AI and technical computing market grew by 23.5% in 2024 and is projected to exceed $100bn by 2028. Intersect360 Research reported that the worldwide market for accelerated and high-performance infrastructure serving AI workloads reached $193bn in 2024, up 121% year-on-year.

Yet the SCW75 reveals that the challenge facing scientific computing is no longer simply about building larger systems.

As Sadaf Alam, Chief Technology Officer and Director of Advanced Computing Strategy at the Bristol Centre for Supercomputing, University of Bristol, explains:

“The most significant challenge in scientific computing today is not technical; it is architectural and strategic.”

Across industries, organisations are grappling with the realities of scaling AI and HPC infrastructure while maintaining usability, governance, reproducibility and sustainability.

The SCW75 survey found that 57% of respondents expect scientific computing investment to increase over the next year, with many already managing infrastructure projects worth several million pounds. But as budgets rise, expectations are rising with them.

Samar Aseeri, Computational Scientist at the King Abdullah University of Science and Technology, highlighted the growing challenge of translating advanced technologies into everyday research environments:

“A significant challenge is bridging the gap between rapidly evolving computational technologies and their practical, scalable adoption in research environments.”

The programme also reflects how scientific computing is increasingly converging across disciplines. Bioinformaticians, automotive engineers, semiconductor researchers, computational chemists and simulation specialists may work in different sectors, but they now share common infrastructure demands: scalable compute, high-performance storage, workflow orchestration, trusted data management and AI-enabled software platforms.

In engineering, simulation and digital design are becoming increasingly central to product development. In life sciences, AI and computational methods are transforming genomics, drug discovery and laboratory workflows. Meanwhile, cloud computing, GPUs and accelerated infrastructure are reshaping how organisations approach research at scale.

Ayesha Afzal, Researcher at Erlangen National High Performance Computing Center, described the growing complexity challenge facing the industry:

“We have reached a point where trial-and-error benchmarking is no longer a viable engineering strategy; it is a costly and unsustainable barrier to entry.”

The inaugural SCW75 features honourees from 14 countries across North America, Europe, Asia and the Middle East, reflecting the increasingly global nature of scientific computing leadership. The United States leads the list with 31 honourees, followed by the United Kingdom with 21 and Germany with 10.

The programme also highlights the growing contribution of women across scientific computing, simulation and HPC leadership. Women represent 31% of the inaugural list — a figure Scientific Computing World hopes will continue to grow in future editions.

Robert Roe, Editor of Scientific Computing World, said:

“Scientific computing has become one of the defining enabling technologies of modern research and engineering. The SCW75 exists to recognise the people making that infrastructure usable, scalable and impactful across industry and academia. These are the individuals helping turn computational investment into scientific progress.”

For more information, visit Scientific Computing World

David Bader

David Bader develops computing methods that make it possible to analyse some of the world’s largest and most complex datasets. His work in high-performance computing and graph analytics has helped shape how researchers study networks in fields ranging from cybersecurity to biology.

• Organisation: New Jersey Institute of Technology
• Role: Distinguished Professor
• Based in: Newark, New Jersey, United States

It is a career defined by pivotal moments. “Each pivot has reinforced a throughline: building the people, platforms and intellectual frameworks that let computation transform science and society,” Bader explains. From early innovations in supercomputing to leadership in data science, his work has consistently focused on enabling computation at scale.

Prof Bader’s research sits at the crossroads of high-performance computing, data science and large-scale network analysis. His work focuses on developing algorithms and systems capable of analysing massive, complex datasets – particularly graphs that underpin applications in cybersecurity, biology, social networks and infrastructure.

His foundational breakthrough came in 1998, when he built one of the first high-performance Linux supercomputers at the University of New Mexico. At a time when proprietary systems dominated, this work demonstrated that commodity hardware and open-source software could deliver competitive performance at significantly lower cost. The approach would go on to reshape the field, with Linux now underpinning virtually all of the world’s fastest supercomputers.

Following this, Bader moved to Georgia Institute of Technology, where he founded and chaired the School of Computational Science and Engineering.

This marked a shift from individual research to institution-building, creating a new academic structure dedicated to interdisciplinary computational methods.

He later joined New Jersey Institute of Technology, where he established the Institute for Data Science. Here, his work reflects a broader convergence between high-performance computing and data-driven research, recognising that large-scale computation is now central across disciplines. Alongside this, he has remained deeply engaged with the global community, serving as Editor-in-Chief of ACM Transactions on Parallel Computing and contributing to major benchmarking initiatives such as Graph500.

Today, his research focuses on scalable graph analytics and network algorithms. Through frameworks such as Arachne and Arkouda, his group is developing interactive tools that allow analysts to work with billion-edge graphs using accessible programming environments.

These systems aim to democratise capabilities that were previously limited to specialists, enabling real-time exploration of complex networks.

His work extends into broader questions of computing’s societal impact. As a recognised expert on AI and computing infrastructure, Bader contributes to public discourse, helping to translate technical developments into accessible insights for policymakers and wider audiences.

A central challenge in his field lies in the nature of graph computation itself. Unlike traditional numerical workloads, graph problems are irregular, memory-bound and difficult to optimise on modern hardware. This creates a gap between theoretical algorithmic advances and their practical application. Bridging this divide, making large-scale graph analytics both performant and accessible, remains a core focus.

Looking ahead, Bader aims to make real-time analysis of billion-scale dynamic graphs a routine capability.

His goal is to enable researchers and practitioners to interactively analyse evolving networks using intuitive tools, without requiring deep expertise in parallel computing. Achieving this would significantly expand access to advanced computational methods and accelerate insight across a range of domains.

For early-career researchers, his advice reflects the lessons of his own journey. Building something tangible, a system that works at real scale, can have far greater impact than theoretical contributions alone. At the same time, investing in people and institutions is essential. Mentoring students, fostering collaborations and shaping research environments all contribute to long-term influence.

He also emphasises the importance of communication. Translating complex ideas for broader audiences, including policymakers and the public, is increasingly critical as computing technologies shape society at large.

With recognition including the IEEE Sidney Fernbach Award and induction into the Computer History Museum, Bader’s contributions have lasting impact. Yet throughout his career, the focus has remained: enabling computation to move beyond theory and into practice, where it can drive meaningful change across science and society.

You can find David at:

• His personal website: www.davidbader.net
• Google Scholar: scholar.google.com/citations?user=uXUA1pgAAAAJ
• LinkedIn: linkedin.com/in/dbader13

https://www.scientific-computing.com/article/david-bader