Find Academic Supervisors

• Computer Architecture
• Edge AI Systems
• Memory Systems
• +6 more

Rafael Medina Morillas is a researcher at the Embedded Systems Laboratory (ESL) at Ecole Polytechnique Fédérale de Lausanne (EPFL), where he focuses on computer architecture and hardware acceleration for edge AI systems. His research addresses the memory wall problem through innovative architectural designs that improve energy efficiency and performance in data-intensive applications. His primary research interests include: Compute-near-Memory architectures Hardware acceleration for machine learning Edge AI systems Chiplet architectures and interconnects Wireless communication for computing systems Medina Morillas' publication record demonstrates significant advancements in memory systems and hardware acceleration. His work on SideDRAM shows up to 83% EDAP reduction compared to state-of-the-art designs, while his research on wireless communication achieves up to 2.64x speedup for deep neural networks. His recent publications focus on structured pruning techniques for transformers, co-design frameworks for edge AI, and thermal management solutions for heterogeneous systems. His research is supported by collaborations with IMEC, Université de Bordeaux, and HEIG-VD, as well as funding from EC H2020 projects and the ACCESS-AI Chip Center. These partnerships enable comprehensive exploration of architectural innovations across different technology domains. As evidenced by his doctoral thesis 'System-aware Architectural Co-design to Tackle the Memory Wall,' Medina Morillas takes a cross-layer approach to system design, integrating hardware and software optimizations to address fundamental bottlenecks in modern computing systems. His work demonstrates how system-aware architectural design can achieve improvements in runtime, energy consumption, and thermal behavior for data-intensive applications.

Aleks NivinaView profile

Assistant Professor

• Natural product biosynthesis
• modular polyketide synthases
• antibiotic biosynthesis
• +4 more

Aleks Nivina serves as a Junior Group Leader at the University of Zurich's Department of Evolutionary Biology and Environmental Studies, holding a prestigious SNSF Ambizione fellowship since 2023. Her interdisciplinary work bridges molecular biology, genetics, and evolutionary studies to decipher mechanisms of natural product biosynthesis and genetic innovation in bacterial systems. Her academic foundation includes a Pharm.D. in Pharmaceutical Research (2006-2015) and M.Sc. in Systems and Synthetic Biology (2011-2012) from Paris Descartes University, followed by a Ph.D. in Interdisciplinary Biology at the Institut Pasteur (2012-2016). Postdoctoral training at Stanford University (2017-2022) and industry experience at Codexis Inc. (2022-2023) preceded her current independent research position. Nivina's research centers on natural product biosynthesis , particularly modular polyketide synthases and antibiotic pathways, with critical investigations into antibiotic resistance mechanisms . She pioneers studies on enzyme evolution through DNA recombination and gene conversion, employing cutting-edge approaches from single-molecule biophysics to machine learning. Her work reveals how genetic elements like integrons and GRINS systems accelerate evolutionary innovation in biosynthetic pathways. Analysis of her 15 most recent publications shows a cohesive trajectory from fundamental studies of DNA recombination dynamics to engineered applications in polyketide synthase diversification. Her scholarship demonstrates increasing integration of computational methods with experimental validation, particularly in refining recombination sites and modeling evolutionary landscapes in antibiotic-producing systems. Her scientific recognition includes: SNSF Ambizione fellowship (2023-present) Funded by her Ambizione grant, Nivina leads an independent research group establishing novel methodologies for genetic engineering of biosynthetic pathways. While currently building her team and not yet supervising graduate students, her lab focuses on harnessing evolutionary principles to combat antibiotic resistance through rational design of antimicrobial compounds and resistance-bypassing strategies. Based in Zurich's Winterthurerstrasse campus, her laboratory combines structural biology, evolutionary genetics, and synthetic biology approaches to investigate how DNA secondary structures and recombination mechanisms drive functional innovation in natural product biosynthesis, with implications for next-generation antibiotic development.

Artem MishchenkoView profile

Professor

• Condensed Matter Physics
• Quantum Materials
• Two-Dimensional Materials
• +3 more

Professor Artem Mishchenko, affiliated with the Faculty of Science and Engineering at The University of Manchester, is a leading condensed matter physicist specializing in quantum phenomena within two-dimensional (2D) materials and van der Waals heterostructures. His research focuses on atomic-scale interactions in layered ultra-thin crystals, aiming to uncover novel electronic, magnetic, and optical behaviors. Condensed Matter Physics Quantum Materials 2D Materials Van der Waals Heterostructures Machine Learning in Experimental Physics Quantum Transport Mishchenko's laboratory employs advanced techniques such as crystal growth, nanofabrication, and high-field magnetotransport, integrating these with machine learning models for dynamic experimental design. During his 2025–2026 fellowship, he will lead the AI x Quantum Materials project to create a curated dataset for accelerating quantum material discovery. Scientific Awards: EMFL Prize (2018) Blavatnik Award for Young Scientists (2021) Highly Cited Researcher (Clarivate Analytics, 2018–2024) Mishchenko has secured major funding, including an ERC Consolidator Grant (2020–2025) and an EPSRC Early Career Fellowship (2016–2021). His work extends to public engagement via the Quantum Futures program, bridging AI-driven science with philosophy and art.

JennyView profile

Professor

• Turbulent Combustion Modeling
• Computational Fluid Dynamics
• Rarefied Gas Kinetics
• +4 more

Professor Jenny leads the Jenny Research Group at ETH Zürich, specializing in turbulent reactive flows, rarefied gas kinetics, and biomedical fluid dynamics. Her work bridges fundamental research with industrial applications in energy systems and fluid mechanics. Develops advanced turbulence models (TDDM, hybrid LES/RANS) for multi-scale flows Pioneers data assimilation frameworks for RANS simulations using adjoint methods Advances particle-based stochastic algorithms for fractured porous media transport Her recent publications emphasize adaptive time integration techniques, probabilistic modeling of non-linear transport phenomena, and optimized simulation tools for hydrogen storage systems. The group's methodological innovations focus on reducing computational costs while maintaining physical accuracy through novel regularization strategies. Key applications include combustion device optimization, high-pressure tank filling analysis, and fractured reservoir simulations. Current projects integrate machine learning with traditional CFD methods to address challenges in droplet clustering, flame surface density propagation, and supersonic spray dynamics. The research framework spans from direct numerical simulations of fundamental flow physics to industrial-scale hybrid modeling implementations.