Organizers

Dr. Yuri Alexeev is a senior quantum algorithm engineer at NVIDIA Corporation and a senior member of the IEEE Society. He has expertise in the development of quantum algorithms using the NVIDIA CUDA-Q framework and GPU-optimized quantum circuit simulators. Before joining NVIDIA, he worked in Argonne Leadership Computing Facility to parallelize and optimize scientific codes for exascale supercomputers and integration of of high-performance computing with quantum computing. He completed PhD studies at Iowa State University and contributed to over 100 publications.

Dr. Elica Kyoseva is director of quantum algorithm engineering at NVIDIA, where she leads the quantum algorithm engineering and applied research teams. Her focus is on using AI Supercomputing to overcome the bottlenecks of quantum computing, which include enabling large-scale device modelling, quantum circuit generation, and algorithm development, among others. Prior to her role at NVIDIA, Elica envisioned, launched, and led the Quantum for Bio program at Wellcome Leap, a 50M USD program aimed at accelerating the applications of quantum computing in human health. Elica earned her PhD in Quantum Optics from the University of Sofia, Bulgaria. She was a Marie Curie fellow at Tel Aviv University and a Research Fellow at the Massachusetts Institute of Technology. In 2016 she was awarded the 2016 John Atanasoff Award of the President of the Republic of Bulgaria for internationally recognized young researchers working in the fields of informatics and information technology. 

Dr. Pooja Rao is a senior quantum algorithm engineer at NVIDIA, specializing in the intersection of quantum computing, HPC, and AI. She works on NVIDIA CUDA-Q, a hybrid open-source platform, to build scalable multi-GPU and multi-QPU quantum-classical applications and algorithms. During her academic career as a computational fluid dynamicist, she focused on designing computational algorithms and developing in-house code to simulate fluid flows at HPC scale, including turbulence modeling for fusion experiments and fluid-particle transfer phenomena in aerospace applications. Her current interests include accelerated quantum computing and exploring quantum computing for fluid dynamics.

Dr. Aniello Esposito works as a principal research engineer in the EMEA research lab at HPE, where he is involved in advanced customer collaborations and mainly responsible for the cooperation with KAUST (KSA). He has a pivotal role in the advancement of hybrid quantum-classical supercomputing at HPE and is involved in pre-sales as an expert application analyst for European procurements as well as for acceptance testing and application support. Aniello studied physics at ETH Zurich, followed by a PhD on simulation of semiconductor devices and postdoctoral research in computational microscopy. He joined Cray as an application analyst at the HLRS in Stuttgart (Germany) and soon began supporting users of other European sites with specialized workshops and acceptance testing. His expertise and interests reside in the development and optimization of hybrid scientific supercomputing applications.

Dr. K. Grace Johnson is a principal research scientist at Hewlett Packard Labs where she works on integrating quantum computing with HPC. She develops hybrid quantum-classical approaches for partitioning quantum workloads that aim to solve challenging real-world problems in the near term. Prior to joining HPE in 2023, Grace received her PhD in quantum chemistry from Stanford University, where she was also a DOE Computational Science Graduate Fellow and research intern at NREL and Nvidia. During this time, she developed frameworks to parallelize and accelerate quantum chemistry simulations for supercomputing as well as simulate quantum circuits using tensor network methods.

Dr. Xin Zhan is a research software engineer at Hewlett Packard Labs where her work is mainly focusing on evaluation of Quantum SDKs with different programming models on HPE Cray EX systems, and extension of quantum computing capability into Cray Programming Environment. She received her PhD from Massachusetts Institute of Technology. Prior to HPE, she has been working in ExxonMobil Corporation as a HPC computation research scientist. And subsequently in Intel Corporation as a software enabling and performance optimization engineer working on Aurora Exascale Computing Project for GPU offloading and heterogeneous compilation tool chain development.

Dr. Masoud Mohseni is a distinguished technologist at Hewlett Packard Enterprise who is a cofounder and head of Emergent Machine Intelligence and HPE Quantum teams, developing a heterogeneous high-performance hybrid quantum-classical computing platform. Formerly, Dr. Mohseni was a senior research scientist at Google Quantum Artificial Intelligence Laboratory and a research scientist and a principal investigator at the Research Lab of Electronics at MIT. His research addresses some of the hardest problems at the interface of artificial intelligence, quantum computing, and statistical physics. He was the tech lead of an open-source software platform known as "TensorFlow Quantum,". He also led the development of "IsingFlow," for physics-inspired optimization and sampling on Google's distributed computing platform known as Borg. Dr. Mohseni has also contributed to the development of seminal quantum machine learning algorithms, including quantum PCA, quantum SVM, quantum k-mean clustering, and entanglement-assisted quantum tomography.