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Aixelo Inc. has announced the formation of a scientific advisory board and its four founding members.


CAMBRIDGE, Mass., June 3, 2024 – Aixelo Inc. a Cambridge, Mass.-based technology company, has announced the formation of a scientific advisory board and its four founding members. Composed of top researchers from various disciplines and backgrounds, the board will provide strategic guidance and direction for Aixelo, which supplies the chemical and materials industries with enterprise software that integrates AI-optimized decision-making into a modernized R&D process.


Heading up the new board is Dr. Pascal Friederich, Aixelo co-founder and chief scientific officer, and a professor at the Karlsruhe Institute of Technology in Germany. Friederich said that having a strong scientific advisory board and direct connection to academia are critical for Aixelo to directly integrate the most cutting-edge scientific developments into its technology.


“The company will greatly benefit from the board’s opinions on the latest developments in AI/ML technology and related opportunities, as well as relevant applications and current challenges in chemistry and materials science,” Friederich said.


The board consists of scientists hailing from academia and industry, and across several countries. These members are Dr. Christoph Brabec, a materials science professor at Friedrich-Alexander University (FAU) in Germany; Dr. Azalia Mirhoseini, an assistant professor of computer science at Stanford University in California; Dr. Artur Schweidtmann, an assistant professor of chemical engineering at Delft University of Technology in the Netherlands; and Dr. Randall Snurr, a professor of chemical and biological engineering at Northwestern University in Illinois.


Brabec’s dedication to bridge the gap between academia and industry has led to such roles as director at the Helmholtz Institute Erlangen-Nuremberg for Renewable Energies (HI ERN), which researches and develops material- and process-based solutions for climate-neutral, sustainable and cost-effective utilization of renewable energies. In this capacity, he strives to accelerate materials discovery by combining data driven and knowledge-driven research strategies into autonomous operating research lines with the potential to transform advancements in various scientific disciplines. Brabec’s career includes having served as head of FAU’s Material Science and Engineering Department, where he has been a professor since 2009. An accomplished academic, his h-index, a metric for evaluating the cumulative impact of an author’s scholarly output and performance, is an outstanding 148. In the private sector, he has taken on executive positions at such companies as Konarka Technologies and Siemens Corporate Technology.


Mirhoseini’s research within Stanford’s Computer Science Department centers on developing capable, reliable and efficient AI systems for high-impact, real-world problems. Her work includes generalized learning-based methods for systems and chip design, self-improving AI models through interactions with the world, and scalable deep learning optimization. Prior to Stanford, Mirhoseini worked on advancing the capability of large language models at Anthropic, and at Google Brain she led the ML forcSystems team she co-founded, focusing on automating and optimizing computer systems and chip design. AI methods created by her have been used in the design of frontier large language models, as well as state-of-the-art Google AI accelerators (TPU). As a member of Aixelo’s Scientific Advisory Board, Mirhoseini said she hopes to contribute new ideas on AI methodologies in addition to insights on the software development from scientific idea to software product.


Focused on researching computer algorithms from the areas of AI, ML and process systems engineering with applications in chemical engineering, Schweidtmann develops algorithms and applies them to various chemical engineering domains including robotic chemistry, process optimization, surrogate modeling, and molecular property prediction. Besides his assistant professor role at Delft University of Technology (TU Delft), he heads the Process Intelligence Research Group at the Chemical Engineering Department. In addition, he is director of the Chemical Engineering & Medical Imaging AI Lab (CHEME AI Lab) that was established through the TU Delft AI Initiative. Schweidtmann looks forward to contributing new ideas on AI algorithms and methods on the Aixelo board in addition to offering insights on software development from scientific idea to software product.


Snurr’s expertise is in using computational modeling to accelerate the discovery of materials for particular applications. He is recognized as a pioneer in metal-organic frameworks (MOFs), having worked in this field since its infancy some 20 years ago. The goal of his research at Northwestern University is to develop new nanoporous materials to solve important energy and sustainability problems, including energy storage, carbon capture, atmospheric water harvesting, and more energy-efficient methods for separating mixtures. On the Northwestern faculty since 1995, Snurr, with an impressive h-index of 113, has been a John G. Searle professor for 10 years, six of those also as chair of the Department of Chemical & Biological Engineering. Snurr noted that Aixelo's aim to accelerate materials discovery aligns well with his own research goals.


About Aixelo

Aixelo partners with chemical and materials companies to integrate AI into their day-to-day R&D operations. Aixelo (āk-sel-o), which stands for AI-Accelerated Operations, is devoted to closing the growing gap between the rapid advances in AI technology and its actual use in labs. Eliminating the common pitfall of well-intentioned companies that thicken the already muddy cloud of AI tools and non-scalable pilot projects, Aixelo equips organizations with AI enterprise software and methodologies that facilitate adoption at scale. The company’s closed-loop AI becomes the guide in decision making to solve material science challenges faster and more successfully – its open platform empowers data science teams to integrate their own valuable know-how for maximum digital impact. For more information, visit