Paola Buitrago leads the Artificial Intelligence and Big Data group at the Pittsburgh Supercomputing Center, which is a joint effort of Carnegie Mellon University and the University of Pittsburgh. Her group is focused on advancing and supporting the convergence of High-Performance Computing (HPC), Artificial Intelligence (AI) and Big Data. Paola initiated a new platform for AI research on emerging hardware and software technologies, enabling the development of advanced algorithms and modeling approaches. She is also leading PSC’s Big Data-as-a-Service (BDaaS) initiative, through which Internet-scale datasets are being integrated with supercomputing resources for cross-cutting research communities. Paola’s diverse background includes research in deep learning, large scale data, and workflow management for high energy physics experiments at the Fermi National Accelerator Laboratory. Paola developed courses in machine learning, simulation, and optimization at her university. She is passionate about education in technology and launched an education-focused start-up. Paola’s diverse background includes research in deep learning, large scale data, and workflow management for high energy physics experiments at the Fermi National Accelerator Laboratory. Paola developed courses in machine learning, simulation, and optimization at her university. She is passionate about education in technology and launched an education-focused start-up.
Dr. Jaime H. Moreno is a Distinguished Researcher, Senior Manager, Hybrid Cloud Infrastructure department, at IBM Research. This department addresses challenges and innovations in hardware and systems co-design for Cloud systems infrastructure, with emphasis on security, isolation, and performance issues. Previously, Jaime was Senior Manager in the Data Centric Systems department at IBM Research, where he and his team were focused on applications, hardware, and systems co-design for high-performance systems, with emphasis on the IBM supercomputers represented by the Summit and Sierra systems, which have been the two most powerful supercomputers in the world since their introduction. organization with a broad range of technical disciplines. Before that, he was Senior Manager, Microprocessor Architecture, at IBM Research, in charge of a team performing research on processor architecture and microarchitecture, and optimizing compiler technology. He also was Research Relationship Manager with academic institutions, and Co-PI for a DOE-sponsored research program.
Dr. Kevin Jorissen is AWS’ Research and Technical Computing Lead. He has 10 years of experience in computational science. He holds a PhD from the University of Antwerp (Belgium) and worked as a postdoctoral researcher in Seattle, Lausanne, and Zurich. As a physicist, he developed software solving the quantum physics equations for light absorption by materials, taught workshops to scientists worldwide, and wrote about high-performance computing in the cloud. Kevin joined Amazon in 2015 to help accelerate the adoption of cloud computing in the scientific community globally
George K. Thiruvathukal is a full professor of computer science at Loyola University Chicago. His primary research interests span high-performance computing, distributed systems, and software engineering. His current research foci are on machine learning and computer vision, empirical software engineering (in support of research software development), and the intersection of cloud computing and supercomputing.
Dr. Thiruvathukal received the PhD and MS degrees in computer science from Illinois Institute of Technology in 1995 and 1990, respectively and BA degrees in physics and computer science (mathematics minor) from Lewis University (Romeoville, IL) in 1988.
For more information, see http://luc.edu/gkthiruvathukal.
Dr. Silvio Rizzi is an Assistant Computer Scientist at the Argonne Leadership Computing Facility. His research interests are large-scale and in-situ scientific visualization and analysis, display technologies, and immersive visualization environments. He has an MS in Electrical and Computer Engineering, and a PhD in Industrial Engineering and Operations Research, both from the University of Illinois-Chicago.
Dr. Debsindhu Bhowmik is a computational Scientist in Biomedical Sciences, Engineering, and Computing (BSEC) group of Computational Sciences and Engineering Division (CSED) and Health Data Sciences Institute (HDSI) at the Oak Ridge National Laboratory (ORNL). He holds B.Sc. and M.Sc. in Physics from Jadavpur University, India, and a Ph.D. from Université Pierre et Marie Curie (UPMC), France with highest remarks for his doctoral work. He received the prestigious CFR (Contrat de formation par la recherche) Fellowship to pursue his doctoral work from CEA (Alternative Energies and Atomic Energy Commission), France. Upon finishing his Ph.D. he joined as Postdoctoral Research Fellow at the Donostia International Physics Center, Spain and later at the Wayne State University, USA.
Dr. Sergio Obando Quintero Applications Engineer at MathWorks with a focus on the areas of data analytics, machine learning, and parallel computing. He received his Ph.D., Master’s, and undergraduate degrees in Mechanical Engineering from the University of Massachusetts Lowell where he worked as a research assistant at the Laboratory for Dynamic Structures and Acoustic Systems (SDASL) specializing in modal analysis and vibrations. Sergio currently works with companies and universities in the United States and Latin America in the adoption and use of MATLAB and Simulink in projects of mathematical modeling, data analysis and simulation, and integration with production and cloud system
Arthur Petitpierre is a Compute Specialist Solutions Architect at AWS, focusing on Graviton2-based EC2 instances. He joined AWS in 2016 as a HPC Specialist Solutions in EMEA, and then moved to Seattle in 2019 to focus on Graviton2-based instances. Prior to that, he used to be ATOS HPC Services CTO and Bull HPC International Support Manager. Arthur Petitpierre received an Engineering degree from Ecole National Supérieure des Arts et Metiers in Paris, with a major in Information Systems.
Louvere is Senior Application Engineer, MathWorks.
Louvere Walker-Hannon is a MathWorks Senior Application Engineer, who provides direction and recommendations on technical workflows for various applications. Specifically, she assists with the following topics image processing, computer vision, machine learning, deep learning, geospatial analysis, and data analytics when discussing technical workflows. Louvere has worked in three different engineering roles throughout her 20 year career while at MathWorks. A prominent theme in her career is communication of technical concepts to various audiences and being involved with STEM education. She has a bachelor’s degree in Biomedical Engineering and a master’s degree in Geographic Information Technology with a specialization in Remote Sensing. Louvere has presented and continues to present at several STEM related conferences on various topics. She recently presented her work on a Natural Language Processing application at the 100th American Meteorological Society in January 2020 and at the American Association of Geographers (AAG) Virtual Conference in April 2020. She also frequently presents workshops where she recently presented a workshop on the integration between AI and IoT in March 2020 as a part of the Open Data Science Conference (ODSC) East 2020 Virtual Conference.
Dr. Dario Dematties, received his PhD. degree at the Institute of Biomedical Engineering in the University of Buenos Aires. He has worked to identify neuroanatomical and physiological features in mammalian cortical tissue that could leverage phonetic perception invariance and generalization as well as higher linguistic functions such as grammar and semantic sentence classification in biologically inspired computational models.
Dr. Dematties uses a computational approach completely unsupervised that incorporates key neurophysiological and anatomical properties that exist in brain cortex running his models on Cooley nodes (a visualization and analysis cluster at Argonne National Laboratory).
During the last years, one of his main activities has been related to High-Performance Computing and to run a profiling test of his computational approach on Cooley (Argonne Leadership Computing Facility Allocation).
Dr. Dematties’ current research interests are on brain-inspired Machine Learning, Experience Grounds Language, Multimodal Intelligence and on the implementation of complex optimization methods (i.e. backpropagation) on biologically plausible neural networks
Jose Manuel Monsalve Diaz obtained his bachelor’s degree in Electrical Engineering from the Pontificia Universidad Javeriana in Bogotá in 2013, and his Master in Electrical and Computer Engineering from the University of Delaware in 2020. After graduation in 2013, he continued his studies at the University of Delaware where he is currently pursuing his PhD on the area of Parallel Computing Architectures. He is also a graduate researcher in Argonne National Laboratory since 2018. Throughout the years he has worked as a research assistant of the CAPSL research group for Prof Guang. R. Gao, and the CRPL research group for Prof. Sunita Chandrasekaran. His areas of interest are parallel computer architecture design, parallel computer systems and parallel programming models. He has worked on validation and verification of OpenMP target offloading, as well as with OpenACC programming targetting CPU and heterogeneous systems based on GPGPUs. Other projects also involved unconventional Data-flow based programming models and computer architectures such as the Codelet Model developed at the University of Delaware.”
He did his Bachelor in Mathematics (1995), and Master in Science (MSc) in Combinatorial Optimization (1998) at Federal University of Pernambuco (UFPE), he also did his Doctoral (DSc) in Computer Graphics (2004) at Pontifical University of Rio de Janeiro (PUC-Rio). Worked for 15 years at Tecgraf Institute/PUC-Rio as a Researcher, Project Manager and for 8 years as Manager of Computational Geophysics Group, during this period was responsible for several Software Development and R&D projects for Geophysics, and other fields of the Oil&Gas industry, with a strong focus on innovation.
Franklin Martinez, PSL
Franklin obtained his MSc in Advanced Computing: Machine Learning, Data Mining, and High-Performance Computing at the University of Bristol.
Currently, leading projects based on machine learning, deep learning, and classic visual computer techniques.
Academic interest: HPC, simulation, adversarial neural networks, computational genomics, natural Language Processing, and big data.
Silvina Caíno-Lores is a Post-Doctoral Research Associate in the University of Tennessee, Knoxvile, as a member of the Global Computing Laboratory directed by Dr. Michela Taufer. She obtained her PhD in Computer Science and Technology in 2019 Department at the Carlos III University of Madrid (Spain) under the supervision of Prof. Jesús Carretero Pérez. She earned her BSc and MSc in Computer Science and Technology from the Carlos III University of Madrid in 2014 and 2015, respectively.
Silvina’s research interests include cloud computing, in-memory computing and storage, HPC scientific simulations, and data-centric paradigms. Her recent works and active collaborations focus on the area of convergence between HPC and Big Data analytics at the application and platform layers
Adriana Suarez-Gonzalez PhD
Adriana is the Science and Technology Advisor for 10x Genomics for Latinamerica and Canada, where she helps researchers to incorporate new technologies to solve their scientific questions. She has worked in a wide variety of projects of human and plant genomics. As a result of her Ph.D. from the University of British Columbia, Adriana explored how the different genomic background history affects gene function and expression and identified markers with a high potential for forest management facing, for example, climate change. While she was finishing her doctorate, Adriana was recruited for a startup company to launch pharmacogenetic testing and high precision medicine software in emerging markets.
Adriana is a strong advocate and proponent of diverse and inclusive environments. She led the creation of the first genomic hackathon in Canada focused on inclusion. She is also served on the Board of Directives of the Society for Canadian Women in Science & Technology and offers advice to incubators in the promotion of a diverse and inclusive ecosystem
Professor Barrios is a systems engineer from the Universidad Industrial de Santander (Bucaramanga, Colombia), a master in applied mathematics and computer science from the University of Grenoble-Alpes (Grenoble, France) and a Doctor in Informatics from the University of Nice-Côte d’Azur ( Nice, France), obtained a doctorate with a “very honorable” mention in the development of a French national project between INRIA (National Institute for Research in Automation and Informatics), the Grenoble computer laboratory (LIG) and the Computer Laboratory, Systems and Signals of Sophia Antipolis (I3S). He has been a visiting researcher at the Institute of Informatics of the Federal University of Rio Grande do Sul in Brazil, of the Barcelona Supercomputing Center in Spain, of the Institute of Theoretical Physics Abdub Salam (ICTP) in Trieste, Italy, the Institute of Technologies of the University de Luxembourg, among others and collaborates with some international companies such as NVIDIA, Intel, HPE, IBM, Atos-BULL, Ecopetrol among others. He has also created and led HPC courses and conferences (such as SC-CAMP, CLCAR and CARLA) as well as participates in different scientific and technological associations around the world (SIGHPC-ACM, TCC-IEEE)