Deep Learning and Artificial Intelligence with
GPU Computing

Gil Bloch is an HPC and AI specialist with broad experience in fast interconnect technologies for clusters, datacenters and cloud computing. His current responsibilities include switch ASIC and systems architecture as well as in-network computing for HPC and machine learning. Before working on in-network computing, Gil had multiple engineering and architecture positions including network adapters ASIC design and architecture, RDMA offload ASIC and open source networking software for High Performance Computing (HPC). He is an author/co-author of multiple patents in the area of computer networks and network adapters. Gil holds a BSc degree in Electrical Engineering from the Technion, Israel Institute of Technology.

Coming soon

Andreas Geiger is a Max Planck Research Group Leader at the MPI for Intelligent Systems in Tübingen heading the Autonomous Vision Group (AVG), and a Visiting Professor at ETH Zürich. Prior to this, he was a research scientist in the Perceiving Systems department at MPI Tübingen. He studied at KIT, EPFL and MIT and received his PhD degree in 2013 from the Karlsruhe Institute of Technology. His research interests are at the intersection of 3D reconstruction and visual scene understanding with a particular focus on rich semantic and geometric priors for bridging the gap between low-level and high-level vision. He is particularly interested in autonomous driving applications. His work has received several prizes, including the Heinz Maier Leibnitz Prize, the Ernst-Schoemperlen Award, as well as best paper awards at CVPR, GCPR and 3DV. He is an associate member of the Max Planck ETH Center for Learning Systems and serves as area chair and associate editor in computer vision (CVPR, ECCV, PAMI).

Adam Wiśniewski is a Director and Co-Founder of PwC Drone Powered Solutions Global Centre of Excellence. He focuses on the practical implementation of technologies that increase situational awareness of all stakeholders of construction process. He is responsible for the roll-out of the solution across the PwC Network globally. Adam is also leading the PwC CEE practice, specialising in Deep Learning for image data analytics. Adam has over 10 years of experience in operational consulting and geospatial data analytics and has worked for clients from various industries all over the world. He has practical experience in operating drones as a certified VLOS and BVLOS pilot.

Federico Pernici received his PhD degree in Information Engineering and Computer Science from the University of Florence in 2005. He is an Assistant Professor of Computer Science at the same university in the Media Integration and Communication Center (MICC). He regularly reviews papers for major computer vision journals, has served on panels, and has served on program committees for major conferences in computer vision. He is an associate editor of Machine Vision and Application. Frederico works on computer vision and machine learning with his focus being different aspects of visual tracking and incremental learning.

Dr. Jean-Loup Loyer is a Lead Data Scientist at L'Oréal where he has been dealing with a large diversity of data-related problems: hybrid chemical formulation combining machine learning and physics, signal processing for audio analysis and motion classification, colorimetry and spectral data analysis, statistical sensory evaluation, consumer purchasing habits and ultimately deep learning with GPU technology. In particular, he designed and industrialized the algorithms for Kérastase’s Smart Hairbrush (Innovation Award - Consumer Electronics Show 2017) and participated in the technical development of several personalized beauty projects focused on skin and hair. In his spare time outside L’Oréal, he has been working actively on team projects involving spatiotemporal models for election forecasting, Natural Language Processing and agent-based models for the analysis of innovation ecosystems. A R and Python programmer, he has production experience in Big Data (Hadoop, Spark), HPC and cloud technology (AWS, Azure). Before joining L’Oréal in 2014, he spent 4 years in Lisbon as a PhD candidate at Instituto Superior Técnico, developing machine learning models to predict the maintenance of jet engines, working with Rolls-Royce plc and MIT as industrial and academic partners. He also served 3 years as a strategy analyst on digital & aerospace affairs in the French Prime Minister administration, where he discovered the power of machine learning by analyzing Open Data. Jean-Loup also holds a M.Sc degree in Aerospace engineering from Toulouse’s Institut Supérieur de l’Aéronautique et de l’Espace and Imperial College London (2007) and a M.Sc degree in statistics from the University of Toulouse (2012).

Bernard Ghanem is currently an Assistant Professor in the CEMSE division and a member of the Visual Computing Center at KAUST. Before that, he was a Senior Research Scientist at the University of Illinois Urbana-Champaign (UIUC) in Singapore, where he still holds an adjunct position. He leads projects that develop algorithms in computer vision, machine learning, and optimization geared towards real-world applications, including semantic video analysis in sports and automated surveillance, content-based image retrieval, large-scale activity recognition, and 2D/3D scene understanding. He received his Bachelor’s degree in Computer and Communications Engineering from the American University of Beirut (AUB) in 2005 and his MS/PhD in Electrical and Computer Engineering from UIUC in 2010. His work has received several awards and honors, including the Henderson Graduate Award from UIUC, two consecutive CSE fellowship awards from UIUC, a Best Paper Award (CVPRW 2013), a two-year KAUST Seed Fund, and a Google Faculty Research Award in 2015. He has co-authored more than 40 peer reviewed conference and journal papers in his field, as well as 4 patents. He is also a co-founder of AutoScount Inc. that provides automated solutions for sports video analytics.

Patrick van der Smagt is head of Volkswagen Group's Fundamental AI Research in Munich’s Data Lab, focusing on probabilistic deep learning for unsupervised time series modelling. He previously directed a lab as Professor for Machine Learning and Biomimetic Robotics at the Technical University of Munich, and was the Head of Bionics at the DLR Oberpfaffenhofen. Besides publishing numerous papers and patents on machine learning, robotics, and motor control, he has won various awards, including the 2013 Helmholtz-Association Erwin Schrödinger Award, the 2014 King-Sun Fu Memorial Award, and the 2013 Harvard Medical School/MGH Martin Research Prize, as well as many best-paper awards. He is a founding chairman of a non-for-profit organisation for Assistive Robotics for tetraplegics and co-founder of various companies.

Erik Nygren holds a M.Sc. in Theoretical Particle Physics and a Ph.D. in Computational Neuroscience. He currently works at the Research and Innovation Lab at Swiss Federal Railways SBB.

Soumith Chintala is a Researcher at Facebook AI Research, where he works on deep learning, reinforcement learning, generative image models, agents for video games and large-scale high-performance deep learning.

Yasser has a master's background in Mathematics and Computer Science, and holds a PhD in Control Theory from the University of Stuttgart and ETH Zurich. He is the Global Head of the BOSCH Center for AI (BCAI) Research, consisting of research teams in Renningen and Palo Alto. Yasser is strongly tied to the BCAI-funded Deep Learning Technology Lab in Amsterdam and the Cyber Valley initiative in Tübingen. The recently founded BCAI Research aims to create differentiating, cutting-edge AI solutions for intelligent Bosch products and strives for a world-wide leading technological position of Bosch in AI.

Rita Cucchiara (Laurea in Electronic Engineering in 1989 ;Ph.D. in Computer Engineering in 1992 at University of Bologna)is full professor with the Dipartimento di Ingegneria “Enzo Ferrari” at UNIMORE, Università di Modena e Reggio Emilia, Italy since 2005. She leads the Research Lab Imagleab. She is Rector Delegate of UNIMORE for Industrial Research, innovation and technology transfer of Emilia-Romagna and is Director of the Interdip- Center of Research in ICT Softech-ICT of the Modena Technopole. She holds the courses of “Computer architecture ” for Computer Engineering ungraduated cv and “Computer Vision” for Magistrale cv and Director of Master in “Visual Computing and Multimedia Technology” . Since 2016, Rita Cucchiara is the President of the Italian Association on Pattern Recognition GIRPR and member of the Governing Board dell’Intern. Association on Pattern Recognition IAPR, Member of the advisory Board of the Computer Vision Foundation and Member of the Board of Directors of Italian Institute of Tehcnology (IIT), Expert Member for Italian APRE Commission in LEIT-ICT Horizon 2020. Her research activities include: computer vision, pattern recognition, machine learning and deep learning for video surveillance and human behavior understanding, for videosurveillance, sport and automotive; multimedia video annotation, summarization, captioning, media big data analysis for cultural heritage and creative industries; wearable sensors, egocentric-vision, and IoT data processing for HCI and robot interaction. Rita Cucchiara coordinates several national and international research projects. In automotive and AI cities, she supervises a PhD Curriculum in a joint project with Ferrari spa and works in the Modena Smart Area Project, a joint initiative with Italian MIUR; Modena Municipality, Maserati and UNIMORE. In the Cultural and Creative industries program, she is the Scientific coordinator of the project “Educating City” Italian Technology Clusters in smart cities and communities 2015-18 and the VIDEOCult 2018-19 project of Cluster Cultural Heraitage of MIUR. She is also the scientific coordinator of the collaboration with Panasonic USA for PhD Exchange. In 2016, she received the prize from Facebook for including Imagelab in the 15 FAIR Labs. Rita Cucchiara was co-funder of two spin-off and co-authors of two patents. She is currently involved in many scientific initiatives; recently she was General chair of ICPR 2020, Milano, Italy. Program chair of ICCV 2017, and CIBR 2017, AVSS 2017, Area chair for ICPR 2012,2016, ACM Multimedia 2013, 2017, CVPR 2014, , 2016, NIPS 2017. She is Associated Editor of IEEE Transactions of Multimedia. Rita Cucchiara is author of more than 300 papers. She has currently H-INDEX=41, citation 10400 (google scholar 2017).

Romeo Kienzler is the Chief Data Scientist of IBM Watson IoT and, as IBM Certified Senior Architect, he helps clients worldwide to solve their data analysis challenges. He holds an M.Sc. (ETH) in Computer Science with specialisation in Information Systems, Bioinformatics and Applied Statistics from the Swiss Federal Institute of Technology. He works as an Associate Professor for artificial intelligence at a Swiss University and his current research focus is on cloud-scale machine learning and deep learning using open source technologies, including R, ApacheSpark, ApacheSystemML, ApacheFlink, DeepLearning4J and TensorFlow. He also contributes to various open source projects. He regularly speaks at international conferences including significant publications in the area of data mining, machine learning and Blockchain technologies. Recently his latest book on Mastering Apache Spark V2.X has been published. Romeo Kienzler is a member of the IBM Technical Expert Council and the IBM Academy of Technology - IBM’s leading brain trusts.

Paul has been at the bleeding intersection of real-time computers graphics and AI since 2000 when he founded AI.implant to use AI (flocking behaviours and path finding) to create and simulate huge crowds of interacting autonomous characters. Customers included Disney and Lucas Film for visual effects; Bioware and EA for game development; and L3 and Lockheed Martin for military simulation. AI.implant was acquired in 2005 by Presagis, the world’s leading developer of software tools for military simulation and training. In 2007, he founded GRIP to use AI (behaviour trees) to create high fidelity autonomous characters capable of rich and complex behaviours. Customers included Bioware, Disney, EA and Eidos. GRIP was acquired in 2011 by Autodesk, the world’s leading developer of software tools for digital entertainment. In 2014, he founded wrnch to use AI (deep learning and computer vision) to enable computers to see and interact with humans. As a serial entrepreneur, Paul has been hustling and hacking since he was 12, when he leveraged a $250 livestock sale into a $1000 TRS-80 Color Computer to program video games and calculate Pi to as many digits as possible. Paul went on to obtain a Ph.D. in computer science from McGill University, during which time the book “The Algorithmic Beauty of Plants” hooked him on computer graphics & AI. He enjoys a crisp gin martini (stirred not shaken) whilst reading New Scientist.

Alexander Khanin is the Founder and CEO of VisionLabs, which he founded in April 2012. A team leader and author of visual recognition technology, Alexander studied Computer Vision at ICVSS in 2014, Visual Recognition and Machine Learning at ENS/INRIA in 2013, Robotics at Imperial College in 2012 and Computer Vision at a Microsoft Summer School in 2011. From 2009 – 2012, he lead a department at the Scientific Research Institute. From 2011 – 2014, Alexander was a PhD student in Computer Vision & Robotics at Bauman Moscow State Technical University. In 2011, he graduated with honors from the Bauman Moscow State Technical University as a Robotics Engineer (Mechatronics, Robotics, and Control Automation Theory). Alexander Khanin is an OMG-Certified UML Professional Advanced. Currently, he is developing and raising VisionLabs as CEO. Alexander also lectures Control Automation Theory at Bauman Moscow State Technical University, sharing his expertise and inspiring his students.

Alexey Brodskiy was born on November 17, 1984, in Yaroslavl, Russia. He earned his Bachelor's and Master's degrees with honours in Computer Science at Demidov Yaroslavl State University. After graduating, Alexey obtained his Ph.D. in Discrete Mathematics and Mathematical Cybernetics from Lobachevsky State University of Nizhni Novgorod in 2011. In his thesis work, he investigated neighbourly random polytopes and confirmed the well-known Gale's conjecture, in general. To bridge the gap between academic research and applied technology, he received his second M.S. in Data Analysis from Yandex School of Data Analysis in 2009. Alexey has rich industrial experience. He started his career at Yandex (the most popular search engine in Russia) as a Software Engineer Intern in 2007. After his internship, Alexey worked as a Software Engineer and led the Analytical Instruments Development Team and Data Analysis Service for 3 years. In particular, he implemented change points detection and the forecasting system for the main Yandex business processes. After Yandex, Alexey was a CTO at the iBinom startup project, where he created and launched the beta version of the service. Alexey also has an extensive background in big data analysis and data mining and is an expert in machining learning and information retrieval. He has thirteen scientific publications and one technical report to his name. In 2017, Alexey joined the Cattle Care project.

Anna Maraga is the Chief Scientific Officer at Metaliquid, where she is responsible for research projects based on machine learning. Her current work focuses on applying deep learning technologies to video content analysis and video encoding. She earned her PhD in Theoretical Physics in 2015.

Chris Fregly is Founder and Research Engineer at PipelineAI, a Streaming Machine Learning and Artificial Intelligence Startup based in San Francisco. He is also an Apache Spark Contributor, a Netflix Open Source Committer, founder of the Global Advanced Spark and TensorFlow Meetup, author of the O’Reilly Training and Video Series titled, "High Performance TensorFlow in Production." Before founding PipelineAI, Chris was a Distributed Systems Engineer at Netflix, a Data Solutions Engineer at Databricks, and a Founding Member and Principal Engineer at the IBM Spark Technology Center in San Francisco.

Dr. Daniel Egloff is Managing Director of QuantAlea, a Swiss software engineering company specialized in AI, Machine Learning and GPU software development. He studied mathematics, theoretical physics and computer science and worked for almost 20 years as a quant and software engineer.

Dieter Weiler received his degree in Computer Science from RWTH Aachen, Germany in 1989. After this, he worked as a freelancer until he founded Q2WEB GmbH in 2004, where he is the CTO. Dieter holds several patents in computer security and GPU-computing. He has a deep understanding of big data, predictive analytics, machine learning and deep learning.

Dong Meng is a Data Scientist for MapR. In his role, Dong helps customers solve their business problem through big data ecosystems. He translates the value from customers’ data and turns them into actionable insights or machine learning products. He has several years of experience in statistical machine learning, data mining, and big data product development. Previously, Dong was a Senior Data Scientist for ADP, where he built machine learning pipelines and data products on HR and payroll data to power ADP Analytics, thereby helping companies to find and retain the right talent. Prior to ADP, Dong was a Staff Software Engineer for IBM, SPSS, where he was part of the team built for Watson analytics. During graduate study, he served as a Research Assistant at the Ohio State University, where he concentrated on compressive sensing and solving point estimation problems on reconstructing sparse signal and recovering the communication channel from a Bayesian perspective.

Giuseppe Piero Brandino has a Ph.D. in statistical Physics. He has a lot of experience in HPC, scientific computing and scientific research. He got his Ph.D from SISSA(Trieste, Italy) and has served as postdoctoral researcher at the University of Amsterdam. He was a visiting scientist and consultant for the Brookhaven National Lab (NY), where he was involded, as an assistant coordinator and teacher, in the Master in High Performance Computing, a postgraduate program that trains scientists in the field of HPC, GPU computing and advanced computational techniques. Since 2016, he has been working as the R&D manager at eXact-lab s.r.l., working on HPC, Cloud Computing, Machine Learning/Deep Learning and Data Analytics.

John Barco leads the product efforts for NVIDIA GPU Cloud, overseeing business strategy, product management, product marketing, and more. John has held senior positions at companies such as Sun Microsystems, NComputing, and ForgeRock, and brings years of cloud and enterprise experience to his role at NVIDIA.

Louis Chevallier is the Principal Scientist at Technicolor Research engineer specialized into audio-visual analysis for multimedia understanding and indexing with extensive experience on machine learning and multimedia features extraction. He holds a degree of Engineer from the Institut National des Sciences Appliquées.

Marco is the Head of Tech at Happy Finish UK. After his research work in Human-Computer Interfaces and Mixed Reality at the University of Bologna and in Machine Learning and Conversational Models at Apple in Siri, he joined the Happy Finish Interactive Team in London to push the boundaries of the creative industry using deep learning and computer vision. His main interests are in Generative Models and Reinforcement Learning applied to Computer Graphics and Media.

Matthew is a Principal Solutions Architect at Kinetica, where he is responsible for designing, documenting, and presenting complex solutions for new and existing customers. Matthew is an experienced professional services consultant with a strong background in designing and integrating enterprise class solutions. He has over six years of increasing responsibility and experience in a variety of engineering roles. Prior to Kinetica, Matthew was a Data Architecture and Integration Manager for Swell EU. Earlier in his career, Matthew was a Technical Account Manager for Datameer, where he was responsible for Hadoop configuration, implementation, security, Java development, and front-end customisation. Prior to that role, Matthew was a Systems Engineer for Openwave Messaging. He began his career as a UNIX System Administrator for the Co-operative Banking Group. Matthew holds a BSc (Hons) degree in Computing and Multimedia Systems from Staffordshire University in England.

Sorin Cristian Cheran is a Deep Learning Institute Instructor and a Technology Strategist as part of the HPC Competency Center in Grenoble. He has been working for HPE since 2007 and before that he obtained his PhD in Computer Science (Artificial Intelligence) from Universita degli Studi di Torino in Italy.

Tim Rocktäschel is a postdoctoral researcher in the Whiteson Research Lab at University of Oxford's Department of Computer Science. He obtained his Ph.D. from University College London where he worked in Sebastian Riedel's Machine Reading group. Tim is a recipient of a Google Ph.D. Fellowship in Natural Language Processing and a Microsoft Research Ph.D. Scholarship. His research focus is on machine learning models that acquire reusable abstractions and that generalize from few training examples by incorporating various forms of prior knowledge. His work is at the intersection of deep learning, reinforcement learning, natural language processing, program induction, and formal logic.

Todd Mostak is the founder and CEO of MapD, a pioneer in building GPU-tuned analytics and visualisation applications for the enterprise. Todd conceived the idea of using GPUs to accelerate the extraction of insights from large datasets while conducting his Harvard graduate research on the role of Twitter in the Arab Spring. Frustrated by the capabilities of conventional technologies to allow for the interactive exploration of these multi-million row datasets, Todd built one of the first GPU-based databases. Upon completion of his studies at Harvard, Todd joined MIT as a research fellow at the Computer Science and Artificial Intelligence Laboratory, focusing on GPU databases and visualisation before founding MapD in late 2013. Todd received his undergraduate degree from the University of North Carolina at Chapel Hill in Economics and Anthropology.

Wiro Niessen is a Full Professor in Biomedical Image Analysis at Erasmus MC, Rotterdam where he leads the Biomedical Imaging Group Rotterdam and at Delft University of Technology. He is the Chief Scientific Officer of Quantib BV, which develops quantitative medical image analysis techniques to support diagnosis and therapy of neurological and cardiovascular diseases. His interest is in the development, validation and implementation of quantitative imaging biomarkers in clinical practice and biomedical research. His focus areas are neurodegenerative disease, atherosclerosis, and oncology. He is active in biological image analysis and improved image guidance in minimally invasive interventions. He has published over 200 journal articles in these areas. He is a Fellow and President of the Medical Image Computing and Computer Assisted Interventions Society, and Director of the Biomedical Image Analysis Platform of the European Institute of Biomedical Imaging Research. In 2015, he received the Simon Stevin Master award, the largest prize in the Netherlands in the field of Applied Sciences. In 2017, he was elected to the Royal Netherlands Academy of Arts & Sciences.

Coming soon

Mr. Wustlich manages the R&D of Planet AI as the CTO. Besides organizing many international research projects he is responsible for Planets R&D strategy and for the development of new technologies guiding internal projects and teams. He coordinates the European research project with leading European research partners and European universities. Besides participating in scientific research (e.g. Neural Computation), Mr Wustlichs main focus is, integrating newest state-ofthe-art technologies into Planets recent product development.