AI Systems Summit Research | Kisaco Research

Bringing together AI researchers & systems engineers from research institutions worldwide.

View Sample Attendees
VIRTUAL EVENT | PDT Timezone
30-31 March, 2021

“This [AI Hardware] summit is a great place where lots of people interested in AI can come together, exchange ideas, and work out how to make the technology better. There’s a synergistic effect at these summits that is really amazing and that powers the entire industry.”

John L. Hennessy, Chairman, Alphabet Inc.

Why Attend

The AI Systems Summit, Research brings together researchers, engineers and architects at research/public institutions worldwide that will focus on the design and deployment of AI systems for scientific purposes. The event is a miniature virtual conference that is free to attend for registrants from research institutions & national laboratories.

Attend to meet researchers working on the same challenges as you in an hour of dedicated networking time on each day. There will also be an opportunity to meet and hear from some of the leading AI Hardware technology providers . 

On the HPC side, the summit will cover topics such as the convergence of HPC & AI (University of Stuttgart), heterogeneous systems design (Lawrence Livermore National Lab), the application of AI hardware to non-AI HPC workloads (Simula Research Laboratory) and early impressions of the Cerebras CS-1 system and the advent of 3D monolithic SoCs (US National Energy Technology Lab).

On the Edge device side, the summit will look at design & engineering challenges for robotic systems (NASA) and neuromorphic and brain inspired systems (UTSA and Oak Ridge National Lab).

WHO WILL BE THERE

38%
Research Scientists & Engineers
23%
Professors
22%
Research Directors
17%
PhD Students & Graduates

Research Scientists & Engineers

Professors

Research Directors

PhD Students & Graduates

Platinum Partners

Media Partners

Partnership Opportunities

The AI Systems Summit offers a rare opportunity to engage and meet with a very specific set of engineers and leaders solely from global National Labs and Research Institutes. This event gathers a group of people focused on designing, building and deploying HPC and AI systems to tackle the most arduous of AI use cases.

These organisations are looking to scout the latest technology to deploy to advance these systems, which offers a unique partnership opportunity for:

  • Early-stage AI technology startups looking for applications & opportunities to prove their tech
  • Mature startups with off-the-shelf technology ready to benefit scientific research
  • AI systems & application builders – suppliers of HPC systems, memory solutions, software and more.

As a two day, virtual summit we can offer a host of options to engage this audience including (but not limited to):

Contact us today for more information and to build a package that will get you the results you need – [email protected]

Agenda

AI Systems Summit Research Agenda

AI Systems Summit Research Agenda

AI Systems Summit Research Agenda

AI Systems Summit Research Agenda

Please complete your details to download a pdf copy of the agenda.

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Resources

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Portfolio attendees include:

Speakers

 

Are Magnus Bruaset

Research Director, Software Engineering & HPC
Simula

Are Magnus Bruaset is Director of Research at Simula Research Laboratory. He is also Professor of Scientific Computing at the University of Oslo. Previously, he has been an entrepreneur in the software industry, specialised in software environments for numerical simulations based on partial differential equations. His research is concentrated on software development for large-scale simulations, in particular for applications in geoscience.

Are Magnus Bruaset

Research Director, Software Engineering & HPC
Simula

Are Magnus Bruaset

Research Director, Software Engineering & HPC
Simula

Are Magnus Bruaset is Director of Research at Simula Research Laboratory. He is also Professor of Scientific Computing at the University of Oslo. Previously, he has been an entrepreneur in the software industry, specialised in software environments for numerical simulations based on partial differential equations. His research is concentrated on software development for large-scale simulations, in particular for applications in geoscience.

 

Bronis de Supinski

CTO, Livermore Computing
Lawrence Livermore National Lab

Bronis R. de Supinski is the Chief Technology Officer (CTO) for Livermore Computing (LC) at Lawrence Livermore National Laboratory (LLNL). In this role, he is responsible for formulating LLNL's large-scale computing strategy and overseeing its implementation. His position requires frequent interaction with high performance computing (HPC) leaders and he oversees several collaborations with the HPC industry as well as academia.

Bronis de Supinski

CTO, Livermore Computing
Lawrence Livermore National Lab

Bronis de Supinski

CTO, Livermore Computing
Lawrence Livermore National Lab

Bronis R. de Supinski is the Chief Technology Officer (CTO) for Livermore Computing (LC) at Lawrence Livermore National Laboratory (LLNL). In this role, he is responsible for formulating LLNL's large-scale computing strategy and overseeing its implementation. His position requires frequent interaction with high performance computing (HPC) leaders and he oversees several collaborations with the HPC industry as well as academia. He is also the LLNL principal point of contact for the Scientific Discovery through Advanced Computing (SciDAC) program's Institute for Sustained Performance, Energy and Resilience (SUPER), for which he leads the resilience thrust.

Prior to becoming CTO for LC, Bronis led several research projects in LLNL's Center for Applied Scientific Computing (CASC). Most recently, he led the Exascale Computing Technologies (ExaCT) project and co-led the Advanced Simulation and Computing (ASC) program's Application Development Environment and Performance Team (ADEPT). ADEPT is responsible for the development environment, including compilers, tools and run time systems, on LLNL's large-scale systems. ExaCT explored several critical directions related to programming models, algorithms, performance, code correctness and resilience for future large scale systems. He currently continues his interests in these topics, particularly programming models, and serves as the Chair of the OpenMP Language Committee.

 

Bronis earned his Ph.D. in Computer Science from the University of Virginia in 1998, and he joined CASC in July 1998. His dissertation investigated shared memory coherence based on isotach logical time systems. His research has covered a wide range of topics, including applications of data mining techniques to performance analysis and modeling including performance modeling through non-linear regression techniques (i.e., artificial neural networks and piecewise polynomial regression), investigations into mechanisms and tools to improve memory performance, a variety of optimization techniques and tools for MPI, and several issues with OpenMP, including its memory model and tool support.

 

Throughout his career, Bronis has won several awards, including the prestigious Gordon Bell Prize in 2005 and 2006, as well as an R&D 100 for his leadership of a team that developed a novel scalable debugging tool. He serves on the program committees of numerous conferences and workshops. He is a member of the ACM and the IEEE Computer Society.

 

 

Catherine Schuman

Research Scientist
Oak Ridge National Laboratory

Catherine (Katie) Schuman is a research scientist at Oak Ridge National Laboratory (ORNL). She received her Ph.D. in Computer Science from the University of Tennessee, where she completed her dissertation on the use of evolutionary algorithms to train spiking neural networks for neuromorphic systems. She is continuing her study of models and algorithms for neuromorphic computing at ORNL. Katie has a joint faculty appointment with the Department of Electrical Engineering and Computer Science at the University of Tennessee, where she co-leads the TENNLab neuromorphic research group.

Catherine Schuman

Research Scientist
Oak Ridge National Laboratory

Catherine Schuman

Research Scientist
Oak Ridge National Laboratory

Catherine (Katie) Schuman is a research scientist at Oak Ridge National Laboratory (ORNL). She received her Ph.D. in Computer Science from the University of Tennessee, where she completed her dissertation on the use of evolutionary algorithms to train spiking neural networks for neuromorphic systems. She is continuing her study of models and algorithms for neuromorphic computing at ORNL. Katie has a joint faculty appointment with the Department of Electrical Engineering and Computer Science at the University of Tennessee, where she co-leads the TENNLab neuromorphic research group. Katie has over 45 publications as well as six patents in the field of neuromorphic computing. Katie received the U.S. Department of Energy Early Career Award in 2019. 

 

Michael James

Co-Founder & Chief Architect, Advanced Technologies
Cerebras

Michael is co-founder and Chief Architect of Advanced Technologies at Cerebras, the company that created the world’s largest and most powerful computer processor. Michael leads the effort to reimagine the algorithmic building blocks for the next generation of AI technologies.

Michael James

Co-Founder & Chief Architect, Advanced Technologies
Cerebras

Michael James

Co-Founder & Chief Architect, Advanced Technologies
Cerebras

Michael is co-founder and Chief Architect of Advanced Technologies at Cerebras, the company that created the world’s largest and most powerful computer processor. Michael leads the effort to reimagine the algorithmic building blocks for the next generation of AI technologies. Prior to Cerebras, Michael was a Fellow at AMD, where he pioneered a technique of adaptive and self-healing circuits based on cellular automata that was applied toward distributed fault tolerant machines. Michael focuses his career on exploration at the intersection of natural phenomena, mathematics, and engineered machines.

 

Shreyansh Daftry

Robotics Technologist
NASA

Shreyansh Daftry is a researcher, technologist and consultant in the fields of Artificial Intelligence (AI) and Space Technology. He is interested in pushing the boundaries of technology with innovation in the fields of Computer Vision, Machine Learning and Autonomous Robotics - Drones, Self-Driving (or Flying) Cars, etc. His lifelong ambition is to promote both the exploration of space and improvement of sustainable living on Earth.

Shreyansh Daftry

Robotics Technologist
NASA

Shreyansh Daftry

Robotics Technologist
NASA

Shreyansh Daftry is a researcher, technologist and consultant in the fields of Artificial Intelligence (AI) and Space Technology. He is interested in pushing the boundaries of technology with innovation in the fields of Computer Vision, Machine Learning and Autonomous Robotics - Drones, Self-Driving (or Flying) Cars, etc. His lifelong ambition is to promote both the exploration of space and improvement of sustainable living on Earth.

Shreyansh received his M.S. degree in AI and Robotics from School of Computer Science, Carnegie Mellon University USA in 2016, and his B.S. degree in Electronics and Communication Engineering in 2013. Currently, he is a Research Scientist at NASA Jet Propulsion Laboratory (JPL) in California, working on AI technologies for robotic exploration of Earth, Mars and beyond!

 

Shimon Ben David

CTO
WekaIO

As WekaIO’s CTO, Mr Shimon Ben-David actively engages with customers and partners to track emerging trends and to bring actionable feedback to Engineering and Product Management, with a focus on Financials and Life science markets as well as AI/ML and GPU workloads. In his more than 6 years at WekaIO, he grew with leadership roles in both Support and Sales Engineering organizations. Prior to joining WekaIO he led the Support Services for Primary Data, XtremIO, and IBM XIV. Shimon met the leadership team of WekaIO when he managed IT at XIV, acquired by IBM in 2007.

Shimon Ben David

CTO
WekaIO

Shimon Ben David

CTO
WekaIO

As WekaIO’s CTO, Mr Shimon Ben-David actively engages with customers and partners to track emerging trends and to bring actionable feedback to Engineering and Product Management, with a focus on Financials and Life science markets as well as AI/ML and GPU workloads. In his more than 6 years at WekaIO, he grew with leadership roles in both Support and Sales Engineering organizations. Prior to joining WekaIO he led the Support Services for Primary Data, XtremIO, and IBM XIV. Shimon met the leadership team of WekaIO when he managed IT at XIV, acquired by IBM in 2007.

 

Dhireesha Kudithipudi

Professor & Director, AI Consortium
The University of Texas at San Antonio

Dhireesha Kudithipudi

Professor & Director, AI Consortium
The University of Texas at San Antonio

Dhireesha Kudithipudi

Professor & Director, AI Consortium
The University of Texas at San Antonio
 

Dirk Van Essendelft

General Engineer
National Energy Technology Laboratory

Dr. Van Essendelft is the principle investigator for the integration of AI/ML with scientific simulations within in the Computational Device Engineering Team at the National Energy Technology Laboratory.  The focus of Dr.

Dirk Van Essendelft

General Engineer
National Energy Technology Laboratory

Dirk Van Essendelft

General Engineer
National Energy Technology Laboratory

Dr. Van Essendelft is the principle investigator for the integration of AI/ML with scientific simulations within in the Computational Device Engineering Team at the National Energy Technology Laboratory.  The focus of Dr. Van Essendelft’s work is building a comprehensive hardware and software ecosystem that maximizes speed, accuracy, and energy efficiency of AI/ML accelerated scientific simulations.  Currently, his work centers around building Computational Fluid Dynamics capability within the TensorFlow framework, generating AI/ML based predictors, and ensuring the ecosystem is compatible with the fastest possible accelerators and processors in industry.  In this way, Dr. Van Essendelft is developing NETL’s first cognitive-in-the-loop simulation capability in which AI/ML models can be used any point to bring acceleration and/or closures in new ways.  Dr. Van Essendelft sits on the Technical Advisory Group for NETL’s new Science-Based Artificial Intelligence/Machine Learning Institute (SAMI) and holds degrees in Energy and Geo-Environmental Engineering, Chemical and Biochemical Engineering, and Chemical Engineering from the Pennsylvania State University, University of California, Irvine, and Calvin College respectively.

Recent publications:

  • Rocki, K., Van Essendelft, D., Sharapov, I., Schreiber, R., Morrison, M., Kibardin, V., Portnoy, A., Dietiker, J. F., Syamlal, M., and James, M. (2020) Fast stencil-code computation on a wafer-scale processor, In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp pp 1-14, IEEE Press, Atlanta, Georgia.

 

Michael Resch

Professor & Director, Institute for HPC (HLRS)
University of Stuttgart

Since 2003, Prof. Michael Resch has been the Director of the High-Performance Computing Center Stuttgart, home of one of the fastest civil computing systems in Europe.He also manages the Institute of High Performance Computing.

Michael Resch

Professor & Director, Institute for HPC (HLRS)
University of Stuttgart

Michael Resch

Professor & Director, Institute for HPC (HLRS)
University of Stuttgart

Since 2003, Prof. Michael Resch has been the Director of the High-Performance Computing Center Stuttgart, home of one of the fastest civil computing systems in Europe.He also manages the Institute of High Performance Computing.

Born in Graz, Austria in 1964, Prof. Resch studied technical mathematics at the Technical University in Graz. Work for the Joanneum Research Association in Graz was followed by employment as a technical assistant and department and team head at the Computing Center of the University of Stuttgart and the High-Performance Computing Center Stuttgart until 2001. In 2002, he became assistant professor at the University of Houston, Texas, USA.

Prof. Resch has received numerous awards, including the Award for High Performance Distributed Computing of the National Science Foundation, the HPC Challenge Award, and the Microsoft Early Contributor Award. He has also received honorary doctorates from the Technical University at Donezk, Ukraine and the Russian Academy of Sciences. Prof. Resch is an honorary professor of the Russian Academy of Sciences.

 

Olivier Beaumont

Research Director
INRIA

Olivier Beaumont, Ph.D. holds a senior researcher position (Directeur de Recherche) at Inria since October 2008. He defended his PhD thesis in 1999 and his Habilitation in 2004. His main interests are in scheduling, load balancing, HPC and memory optimization and parallelization of training. He served as PC Chair (Algorithm Track) for many HPC conferences (SuperComputing, IPDPS, ICPP, HIPC,...) and he is acting as Associate Editor in Chief of JPDC (Journal of Parallel and Distributed Computing). He is the author of more than 90 papers in international journals and conferences.

Olivier Beaumont

Research Director
INRIA

Olivier Beaumont

Research Director
INRIA

Olivier Beaumont, Ph.D. holds a senior researcher position (Directeur de Recherche) at Inria since October 2008. He defended his PhD thesis in 1999 and his Habilitation in 2004. His main interests are in scheduling, load balancing, HPC and memory optimization and parallelization of training. He served as PC Chair (Algorithm Track) for many HPC conferences (SuperComputing, IPDPS, ICPP, HIPC,...) and he is acting as Associate Editor in Chief of JPDC (Journal of Parallel and Distributed Computing). He is the author of more than 90 papers in international journals and conferences.

 

Bruno Raffin

Research Director
INRIA

Bruno Raffin is Director of Research at INRIA Grenoble Rhône-Alpes and leader of the DataMove team. Bruno Raffin has a PhD from the Université d’Orléans on parallel programming language design (1997). After a 2 years postdoc at Iowa State University he refocused his research on high performance interactive computing. He led the development of the FlowVR middleware for large scale data-flow oriented parallel applications, used for virtual reality, telepresence and computational steering. He recently retargeted FlowVR at in-situ analytics for large scale parallel application.

Bruno Raffin

Research Director
INRIA

Bruno Raffin

Research Director
INRIA

Bruno Raffin is Director of Research at INRIA Grenoble Rhône-Alpes and leader of the DataMove team. Bruno Raffin has a PhD from the Université d’Orléans on parallel programming language design (1997). After a 2 years postdoc at Iowa State University he refocused his research on high performance interactive computing. He led the development of the FlowVR middleware for large scale data-flow oriented parallel applications, used for virtual reality, telepresence and computational steering. He recently retargeted FlowVR at in-situ analytics for large scale parallel application. He also worked on parallel algorithms and cache-efficient parallel data structures (cache oblivious mesh layouts, parallel adaptive sorting), strategies for task-based programming of multi-CPU and multi-GPU machines. He initiated and steered the multi-camera Grimage platform to develop real-time full-body 3D interactions and 3D telepresence. Today he is refocusing is research activity on high performance computing. He leads the INRIA Integrated Project Lab  focused on the convergence between HPC, AI and Big Data. Bruno Raffin accounts for more than 60 international publications,  advised 16 PhD students. He was responsible for INRIA of more than 15 national and European grants,  was the co-founder of the Icatis startup company (2004-2008), and transferred several codes to other companies.  Bruno Raffin has been involved in more than 30 program committees of international conferences.  He is the head of the steering committee  of the Eurographics Symposium on Parallel Graphics and Visualisation.

 

Rob Schreiber

Distinguished Engineer
Cerebras

Rob Schreiber is a Distinguished Engineer at Cerebras Systems, Inc., where he works on architecture and programming of systems for accelerated training of deep neural networks. Schreiber’s research spans sequential and parallel algorithms for matrix computation, compiler optimization for parallel languages, and high performance computer design. With Moler and Gilbert, he developed the sparse matrix extension of Matlab.  He created the NAS CG parallel benchmark.  He was a designer of the High Performance Fortran language.

Rob Schreiber

Distinguished Engineer
Cerebras

Rob Schreiber

Distinguished Engineer
Cerebras

Rob Schreiber is a Distinguished Engineer at Cerebras Systems, Inc., where he works on architecture and programming of systems for accelerated training of deep neural networks. Schreiber’s research spans sequential and parallel algorithms for matrix computation, compiler optimization for parallel languages, and high performance computer design. With Moler and Gilbert, he developed the sparse matrix extension of Matlab.  He created the NAS CG parallel benchmark.  He was a designer of the High Performance Fortran language. Rob led the development at HP of the PICO system for synthesis of custom hardware accelerators.  He has help pioneer the exploitation of photonic signaling in processors and networks. He is an ACM Fellow, a SIAM Fellow, and was awarded, in 2012, the Career Prize from the SIAM Activity Group in Supercomputing.

 

Johannes Langguth

Research Scientist
Simula

Johannes Langguth is a research scientist at Simula reseach laboratory, Oslo, Norway. He received his PhD in computer science from the University of Bergen, Norway in 2011, and master degrees in computer science and economics from university of Bonn, Germany. After a postdoctoral appointment at ENS Lyon, France, he joined Simula in 2012.

Johannes Langguth

Research Scientist
Simula

Johannes Langguth

Research Scientist
Simula

Johannes Langguth is a research scientist at Simula reseach laboratory, Oslo, Norway. He received his PhD in computer science from the University of Bergen, Norway in 2011, and master degrees in computer science and economics from university of Bonn, Germany. After a postdoctoral appointment at ENS Lyon, France, he joined Simula in 2012. His research focuses on the design of discrete algorithms for irregular problems on parallel heterogeneous architectures such as multi-core CPUs and GPUs, and their applications in scientific computing, graph analytics, machine learning, computational social science, and high-performance codes for cardiac electrophysiology.

 

Sorin Cheran

VP & Fellow, AI Strategy & Solution Group
HPE

Sorin Cheran is an HPE Fellow and currently serves as vice president of HPE’s AI Strategy and Solutions Group which is responsible for the company’s global AI strategy.

Sorin Cheran

VP & Fellow, AI Strategy & Solution Group
HPE

Sorin Cheran

VP & Fellow, AI Strategy & Solution Group
HPE

Sorin Cheran is an HPE Fellow and currently serves as vice president of HPE’s AI Strategy and Solutions Group which is responsible for the company’s global AI strategy.  Since 2007, Sorin has held positions including AI and Chief Architect in Hewlett Packard Labs and as a key member in the Hybrid IT Presales team in the High-Performance Computing (HPC) and AI Competency Center in Grenoble, France. Sorin’s drive, creativity, energetic leadership and spirit of collaboration consistently delivers outstanding business outcomes for HPE and its customers. He has nurtured and evangelized Artificial Intelligence within HPE, as well as externally with customers and partners. 

 is an HPE Fellow and currently serves as vice president of HPE’s AI Strategy and Solutions Group which is responsible for the company’s global AI strategy.  Since 2007, Sorin has held positions including AI and Chief Architect in Hewlett Packard Labs and as a key member in the Hybrid IT Presales team in the High-Performance Computing (HPC) and AI Competency Center in Grenoble, France. Sorin’s drive, creativity, energetic leadership and spirit of collaboration consistently delivers outstanding business outcomes for HPE and its customers. He has nurtured and evangelized Artificial Intelligence within HPE, as well as externally with customers and partners. 

 

Emre Neftci

Assistant Professor
UC Irvine

Dr. Neftci is an assistant professor in the department of Cognitive Sciences and Computer Science at UC Irvine. He received his master's degree in Physics at Ecole Polytechnique Federal de Lausanne (EPFL) and his PhD in Neuroinformatics from the Institute of Neuroinformatics at the university of Zurich and ETH Zurich in neuromorphic engineering.

Emre Neftci

Assistant Professor
UC Irvine

Emre Neftci

Assistant Professor
UC Irvine

Dr. Neftci is an assistant professor in the department of Cognitive Sciences and Computer Science at UC Irvine. He received his master's degree in Physics at Ecole Polytechnique Federal de Lausanne (EPFL) and his PhD in Neuroinformatics from the Institute of Neuroinformatics at the university of Zurich and ETH Zurich in neuromorphic engineering. His current research explores the bridges between neuroscience and machine learning, with the focus of theoretical and computational modeling of learning algorithms that are best suited to neuromorphic hardware and non-von Neumann computing architectures.

 

Subhasish Mitra

Professor of Electrical Engineering and of Computer Science
Stanford University

Subhasish Mitra is Professor of Electrical Engineering and of Computer Science at Stanford University. He directs the Stanford Robust Systems Group, leads the Computation Focus Area of the Stanford SystemX Alliance, and is a member of the Wu Tsai Neurosciences Institute. Prof. Mitra also holds the Carnot Chair of Excellence in NanoSystems at CEA-LETI in France. His research ranges across Robust Computing, NanoSystems, Electronic Design Automation (EDA), and Neurosciences.

Subhasish Mitra

Professor of Electrical Engineering and of Computer Science
Stanford University

Subhasish Mitra

Professor of Electrical Engineering and of Computer Science
Stanford University

Subhasish Mitra is Professor of Electrical Engineering and of Computer Science at Stanford University. He directs the Stanford Robust Systems Group, leads the Computation Focus Area of the Stanford SystemX Alliance, and is a member of the Wu Tsai Neurosciences Institute. Prof. Mitra also holds the Carnot Chair of Excellence in NanoSystems at CEA-LETI in France. His research ranges across Robust Computing, NanoSystems, Electronic Design Automation (EDA), and Neurosciences. Results from his research group have influenced almost every contemporary electronic system, and have inspired significant government and research initiatives in multiple countries. Prof. Mitra also has consulted for major technology companies including Cisco, Google, Intel, Samsung, and Xilinx.

In the field of Robust Computing, he has created many key approaches for circuit failure prediction, on-line diagnostics, QED system validation, soft error resilience, and X-Compact test compression. Their adoption by industry is growing rapidly, in markets ranging from cloud computing to automotive systems. His X-Compact approach has proven essential for cost-effective manufacturing and high-quality testing of almost all 21st century systems, enabling billions of dollars in cost savings.

With his students and collaborators, he demonstrated the first carbon nanotube computer. They also demonstrated the first 3D NanoSystem with computation immersed in data storage. These received wide recognition: cover of NATURE, Research Highlight to the US Congress by the NSF, and highlight as "important, scientific breakthrough" by global news organizations.

Prof. Mitra's honors include the Newton Technical Impact Award in EDA (test of time honor by ACM SIGDA and IEEE CEDA), the Semiconductor Research Corporation’s Technical Excellence Award, the Intel Achievement Award (Intel’s highest honor), and the US Presidential Early Career Award. He has published award-winning papers at major venues such as the Design Automation Conference, International Solid-State Circuits Conference, International Test Conference, Symposium on VLSI Technology, and Formal Methods in Computer-Aided Design. Stanford undergraduates have honored him several times "for being important to them." He is an ACM Fellow and an IEEE Fellow.

 

 

Ashkan Seyedi

Senior Research Scientist, HP Labs
HPE

Ashkan Seyedi is a senior research scientist for Hewlett Packard Labs. Ashkan received a dual bachelor’s degree in electrical and computer engineering from the University of Missouri-Columbia. He earned his Ph.D. from the University of Southern California working on photonic crystal devices, high-speed nanowire photodetectors, efficient white LEDs, and solar cells. Since 2014 at HPE, he has worked on developing high-bandwidth, efficient optical interconnects for exascale and high-performance computing applications.

Ashkan Seyedi

Senior Research Scientist, HP Labs
HPE

Ashkan Seyedi

Senior Research Scientist, HP Labs
HPE

Ashkan Seyedi is a senior research scientist for Hewlett Packard Labs. Ashkan received a dual bachelor’s degree in electrical and computer engineering from the University of Missouri-Columbia. He earned his Ph.D. from the University of Southern California working on photonic crystal devices, high-speed nanowire photodetectors, efficient white LEDs, and solar cells. Since 2014 at HPE, he has worked on developing high-bandwidth, efficient optical interconnects for exascale and high-performance computing applications.

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