CORPORATE KEYNOTE SERIES
Tendai Gomo
(Google, USA)
Bio: Tendai Gomo has 20 years of experience in technology and is currently a Technology Program Manager for Google Cloud currently responsible for managing over 10 products in Google Cloud Storage. Previously Tendai was an Executive Director at JPMorgan Chase where he was responsible for Cyber Security and Technology Controls for Cloud Technology. Previously Tendai has worked for companies like UBS, Barclays, and Deloitte.
Title of the talk: Building low-level software for high-level function
Abstract: First, in this talk, I will present a personal project designing an application and API for Google Glass. I did this work before I joined Google. Indeed, I sold my software system to a large Software Company. Later on, I joined Google.In the second part of this talk, I will discuss managing global scope projects and the art and science of software development in and out of the Cloud. This is very germane for managing substantial global projects.In the third part of this talk, I will connect the dots for global project management. In particular, I will discuss creating habits and feedback loops that enhance productivity. This will be focused on technical projects with technical details on how to leverage the global technological environment.
Michele Lynn-Moore Myauo
(Microsoft Corporation, USA)
Bio: Michele Lynn-Moore Myauo, Ph.D., is a cybersecurity and IT executive, author, speaker and professor. She is a director of cybersecurity & secure infrastructure services delivery for the global secure infrastructure practice at Microsoft. She previously worked at IBM, where she was service area manager for the operations and supply chain management practice and deputy director of enterprise architecture. She also worked as a professor of engineering management and systems engineering, with a focus on cybersecurity policy and compliance, at The George Washington University in Washington, D.C. Myauo has over 17 yrs. experience leading cybersecurity, systems engineering, and IT services business execution across academia, industry, and many levels of government, including the U.S. intelligence community and federal departments of commerce, defense, energy, state, and homeland security. She holds a doctorate in systems engineering from The George Washington University, a M.S. in industrial and organization psychology from University of Baltimore, and a B.S. in psychology from Bethany College in Bethany, W.Va.
Title of the talk: You are under attack
Abstract: Either you’re under attack and you know it. Or you’re under attack and you don’t know it yet. Most organizations are breached within 24 hours, and attackers lurk in environment for more than a year before detection. As much of our daily interaction now takes place online, criminals increasingly seize the opportunity to launch cyber-attacks.
By 2022, the cybersecurity industry is expected to gross more than $232 billion globally. Cyber- attackers exploit people, processes, and technologies to steal high-value data. Their attacks are complex and costly, and they require rapid and comprehensive counter measures – which in turn require a workforce of great diversity. Demand for cybersecurity professionals is expected to rise to six million worldwide by 2019, with a projected shortfall of 1.5 million. To withstand increasing and evolving cyber threats, organizations must understand the current and emerging landscape and systematically implement a holistic approach to cybersecurity. This keynote will offer real-world insights on helping global organizations manage cyber risk, recover from cyber-attacks, and mitigate future threats.
Hossam Fattah
(Microsoft Corporation, USA)
Bio: Hossam Fattah received his Ph.D. in Electrical and Computer Engineering from University of British Columbia, Vancouver, Canada in 2003. In 2000, he received his Masters of Applied Science in Electrical and Computer Engineering from University of Victoria, Victoria, Canada. He completed his B.Sc. degree in Computers and Systems Engineering from AlAzhar University, Cairo, Egypt in 1995.
Between 2004 to 2013, he has been with the academia and industry, including Texas A&M University and Spirent Communications, USA, working on wireless communication technology, cellular systems, and research and development for several networking and wireless standards and protocol stacks including Zigbee, WiFi, WiMax, CDMA, and 3G/4G/5G systems. Since 2013, he has been with Microsoft Corporation, USA, working on different networking products and services for Windows and Cloud networking and technology. He has contributed to many technical publications in referred conferences, journal, patents, and a Book author. He is a registered Professional Engineer with the Engineers and Geoscientists of British Columbia, Canada.
Title of the talk: Traffic Monitoring in Microsoft Azure Cloud
Abstract: Storing, viewing, and analyzing network flows in a Cloud environment is an important Virtualized Network Function (VNF) for Cloud tenants and users. It is used to store, track, and analyze traffic that belongs to Virtual Networks (VNETs), Virtual Machines (VMs), or Network Interfaces (NICs). It is used for logging ingress and egress IP traffic flows, number of bytes and packets transmitted and received, and network connections. Flow logging is critical for the investigation of firewall functionalities, security incidents, and threat detection. Moreover, it can be used for detecting connection and network anomalies such as connection outages, configuration changes, or malicious activities. Alerts can be fired for any suspicious network activities. Visualization of flows logs provides insights such as who is using a web-service or an application, when customers are logged in and out, and what are the geographical locations where connections are being initiated or terminated. In this Talk, we talk about a VNF in Azure Cloud that details the framework for logging network flows in a Cloud environment. The method aims at accommodating multiple and simulations Cloud tenants and enabling the logging of network flows while at the same time accommodates high incoming rates of flow events and data. One of the major benefits of this flow logging is that it supports high number of flows per second that facilitates flow logging of high traffic volumes. Not only customers can experience higher number of flows logged, but the flow logs are visualized and contain the number of packets and bytes transmitted and received for outbound and inbound flows, respectively.
Alexander Podelko
(Consultant Member, Oracle, USA)
Bio: Alexander Podelko has specialized in performance since 1997, working as a performance engineer and architect for several companies. Currently, he is Consulting Member of Technical Staff at Oracle, responsible for performance testing and optimization of Enterprise Performance Management and Business Intelligence (a.k.a. Hyperion) products. Alexander periodically talks and writes about performance-related topics, advocating tearing down silo walls between different groups of performance professionals. His collection of performance-related links and documents (including his recent articles and presentations) can be found at https://www.alexanderpodelko.
Alexander received his Ph.D. in Computer Science from Gubkin University and his MBA from Bellevue University.
Title of the talk: Internet of Things: Performance, Capacity, and Scalability Aspects
Abstract: According to an independent global survey of 800 CIOs, 74% of IT leaders are concerned that Internet of Things (IoT) performance problems could directly impact business operations and significantly damage revenues. IoT brings in a unique combination of challenges, including increased complexity, limited visibility, and data explosion. While IoT systems are very diverse and it is difficult to provide generic recommendations, in this session we will consider some typical issues and approaches for every stage of system's lifecycle – design, development, testing, and operations.
Hugh Seaton
(Adept Reality, USA)
Bio: Hugh Seaton has spent his career involved in the creation and marketing of new technologies. From novel steel wire in southern Taiwan to flat screens at Philips, Walkman at Sony and online services at AOL, and now AI powered talent development at Aquinas Learning, Hugh has driven innovation and adoption for over 20 years. Since returning from China in 2012, Hugh has led creation and execution of 20+ hackathons, and created conferences in Connecticut & New York City. His most recent passion project is the creation of a world class AR cloud in Stamford, CT. Hugh is graduate of Columbia Business School, writing his graduate thesis on diffusion of innovations.
Title of the talk: Unfinished Gateways: Mobile & Wearable Devices In the ARCloud
Abstract: The world is becoming increasingly instrumented, modeled and represented digitally. The growth of IoT across urban and industrial landscapes, combined with emergence of augmented reality systems capable of representing those dataflows in real time against a fully modeled digital twin of the real world, represents a step change in how we can interact with the world and its data flows. How this is coming together, the progress and opportunities it presents for new areas of research and commercial growth will all be explored through the aperture of the mobile & wearable devices that make it all accessible. Specific topics will include the ARCloud, Natural Language Processing, Computer Vision and hardware present & near future.
Douglas Blank
(Head Of Research at Comet.ml, USA)
Bio: Douglas Blank is the head of research at Comet ML, a machine learning experiment management platform that makes machine learning experiments easy to run, visualize, understand, and reproduce. He is also a Professor Emeritus of Computer Science at Bryn Mawr College where he’s taught for eighteen years. Professor Blank's core research area is in machine learning where he explored deep learning on robots in order for them to develop artificial intelligence through experience.
Title of the talk: Software Engineering for Machine Learning
Abstract: Software engineering is a well-established field with many best-practices. However, many of the best practices and methodologies of software engineering principles don’t apply to machine learning (ML) and data science. ML can be used to solve problems very different from that of software engineering. For example, rather than relying on human-designed specifications, ML can solve problems by merely seeing examples of solutions. This has huge implications throughout the software industry. Concepts such as software security, quality assurance, maintenance, and team organization need to be restructured in order to be applied to ML. This talk will explore some of the issues in designing software engineering for machine learning.
Bernard François
(Founder, PreviewLabs Inc., USA)
Bio: Bernard Near the end of 2009, Bernard decided to combine his passion for game design and game programming by starting the first company dedicated to the development of prototypes using game technology: PreviewLabs. PreviewLabs turns ideas into interactive prototypes, allowing its clients to evaluate concepts early on. This service enables them to explore more different concepts and ultimately helps them to be more successful developing new products. In the first nine years of PreviewLabs, Bernard oversaw the development of prototypes for over 200 different concepts, for clients including Walt Disney Imagineering and Yale University, but also a large amount of startups seeking to develop new products.
Title of the talk: Rapid Prototyping for IoT and Augmented Reality
Abstract: When a new technology or medium comes up, some interesting challenges present themselves when developing new applications. For instance, how do you find the best way of using the new technology for your needs? How do you effectively pitch your ideas? And what are effective ways to study the feasibility for your target audience?
RESEARCH KEYNOTE SERIES
Prof. Vincent W. S. Chan
(Massachusetts Institute of Technology, USA)
Throughout his career, Professor Chan has spent his research focus on communication and networks, particularly on free space and fiber optical communication and networks and satellite communications. His work has led the way to a successful laser communication demonstration in space and early deployment of WDM optical networks. His recent research emphasis is on algorithmically-optimized heterogeneous network architectures with stringent performance demands.
Title of the Talk: Research frontiers in communications and networks
Abstract: Due to the advent of disruptive new technology and driven by radically new applications different from the traditional ones, the network of the future will grow at least 3 orders in magnitude in capacity and more significantly much more agile in its response to changing demands. This talk will highlight including providing conjectures on the architecture of future networks. Emphasis of the talk will be placed on new service requirements and network architecture and algorithms.
Prof. Ken Birman
(Cornell University, USA)
Bio: Ken Birman is the N. Rama Rao Professor of Computer Science at Cornell. An ACM Fellow and the winner of the IEEE Tsutomu Kanai Award, Ken has written 3 textbooks and published more than 150 papers in prestigious journals and conferences. Software he developed operated the New York Stock Exchange for more than a decade without trading disruptions, and plays central roles in the French Air Traffic Control System and the US Navy AEGIS warship. Other technologies from his group found their way into IBM’s Websphere product, Amazon’s EC2 and S3 systems, Microsoft’s cluster management solutions, and the US Northeast bulk power grid. His Vsync system (vsync.codeplex.com) has become a widely used teaching tool for students learning to create secure, strongly consistent and scalable cloud computing solutions. Derecho is intended for demanding settings such as the smart power grid, smart highways and homes, and scalable vision systems.
Title of the Talk: Building Smart Memories and Responsive Edge Services with Derecho
Abstract: The Derecho platform was created to support a new generation of Internet-of-Things (IoT) applications with online machine-learning components. At cloud-scale, such applications require a new edge u-service ecosystem, which I like to think of a as a form of “smart memory”. I’m using this term to refer to a customizable service designed to be hosted in the cloud edge, where it would accept high-bandwidth data pipelines from sources, apply machine-learning tools to analyze and understand received content, perform initial data transformations such as image segmentation, tagging and other basic AI functions, and support ways to query the resulting knowledge base with minimal delay. Such services would also need to scale out, yet must maintain their rapid responsiveness and strong consistency.
Derecho, which is now fully implemented (github.org/Derecho-Project), leverages persistent memory and RDMA to solve this problem with exceptional performance and scalability. Derecho is also interesting from a theoretical perspective.In particular, the core protocols used implement Paxos state machine replication in a novel manner optimized for RDMA settings. These protocols have been proved correct, and are also highly efficient in terms of delay before message delivery, progress during failures and even the mapping to RDMA hardware.
Prof. Amy Greenwald
(Brown University, USA)
Bio: Dr. Amy Greenwald is Professor of Computer Science at Brown University in Providence, Rhode Island. She studies game-theoretic and economic interactions among computational agents, applied to areas like autonomous bidding in wireless spectrum auctions and ad exchanges.During the 2018--19 academic year, she was a visiting researcher at the Artificial Intelligence Research Center at the Japanese National Institute of Advanced Industrial Science and Technology in Tokyo. In 2015, she was a visiting researcher in the
Algorithmic Economics Lab at Microsoft Research in New York City. In 2011, she was a visiting professor at the Erasmus
Research Institute of Management in Rotterdam.
In 2011, she was also named a Fulbright Scholar (though she declined the award). She was awarded a Sloan Fellowship in 2006;she was nominated for the 2002 Presidential Early Career Award for Scientists and Engineers (PECASE); and she was named one of the Computing Research Association's Digital Government Fellows in 2001. Before joining the faculty at Brown, Dr. Greenwald was employed by IBM's T.J. Watson Research Center. Her paper entitled "Shopbots and Pricebots" (joint work with Jeff Kephart) was named Best Paper at IBM Research in 2000.
Title of the Talk: Learning Equilibria in Simulation-Based Games ... and the Ensuing Empirical Design of Mechanisms
Abstract: We describe a methodology for the design of parametric mechanisms, which are multiagent systems inhabited by strategic agents, with knobs that can be adjusted to achieve specific goals. For example, a network designer might seek a design that minimizes congestion assuming selfish agents. Our methodology applies under two key conditions: 1. the mechanisms induce games that can be simulated, but that do not afford an analytic description, 2. the agents play approximate equilibria in these simulation-based games. Under these conditions, we use the probably approximately correct learning framework to construct algorithms that learn equilibria. We show experimentally that our methodology can be used to design effective mechanisms that capture stylized, but rich multiagent systems, such as advertisement exchanges, which are not generally amenable to analytical mechanism design.
Prof. Lyle Ungar
(University of Pennsylvania, USA)
Bio: Dr. Lyle Ungar is a Professor of Computer and Information Science at the University of Pennsylvania, where he also holds appointments in multiple departments in the Schools of Business, Medicine, Arts and Sciences, and Engineering and Applied Science. Lyle received a B.S. from Stanford University and a Ph.D. from M.I.T. He has published over 250 articles, supervised two dozen Ph.D. students, and is co-inventor on ten patents. His current research focuses on developing scalable machine learning methods for data mining and text mining, including deep learning methods for natural language processing, and analysis of cell phone and social media to better understand the drivers of physical and mental well-being.
Title of the Talk: Measuring Well-Being Using Social Media
Abstract: Social media such as Twitter and Facebook provide a rich, if imperfect, portal into people's lives. We analyze tens of millions of Facebook posts and billions of tweets to study variation in language use with age, gender, personality, and mental and physical well-being. Word clouds provide insights into stress, anxiety, and depression, while correlations between language use and county-level health data suggest connections between health and happiness, including potential psychological causes of heart disease.
Prof. Stephen B. Wicker
(Cornell University, USA)
Bio: Dr. Stephen B. Wicker is a Professor of Electrical and Computer Engineering at Cornell University, and a member of the graduate fields of Computer Science, Information Science, and Applied Mathematics. He teaches and conducts research in wireless information networks, cellular networks, and digital telephony. He currently focuses on the interface between information networking technology, law, and sociology, with a particular emphasis on how design choices and regulation can affect the privacy and speech rights of users.
Professor Wicker’s most recent book, Cellular Convergence and the Death of Privacy, was published by Oxford University Press in August 2013. Professor Wicker received a Cornell College of Engineering Teaching Award in 1998, 2009, and 2013. He also received the Cornell School of Electrical and Computer Engineering Teaching Award in 2000. As of early 2019, he has supervised 44 doctoral dissertations.
Professor Wicker is also the author of Codes, Graphs, and Iterative Decoding (Kluwer, 2002), Turbo Coding(Kluwer, 1999), Error Control Systems for Digital Communication and Storage (Prentice Hall, 1995) and Reed-Solomon Codes and Their Applications (IEEE Press, 1994).Professor Wicker is the Cornell Principal Investigator for the TRUST Science and Technology Center – a National Science Foundation center dedicated to the development of technologies for securing the nation’s critical infrastructure. He is a Fellow of the IEEE.
Title of the Talk: Reading in the Panopticon: A Case Study in Wireless Surveillance
Abstract: In this talk I pursue the Panoptic metaphor by considering surveillance technologies that may be built into our eBooks. I choose the words “may be” with great care; my students and my studies of Amazon’s patents indicate the potential for extensive surveillance, but when we asked Amazon to confirm or deny their use of these technologies, we received what can best be described as a non-answer. It follows that Kindle users don’t know that the surveillance technologies that I will describe are actually in use, only that they are available for use. And that, of course, is the underlying power of the Panopticon.
Having described Amazon’s patented Kindle surveillance technology, I turn to the question of why we should care. Using case law and common sense, I suggest that anonymous reading is connected to free expression. Surveillance creates a chilling effect on one’s choice of reading material, which in turn limits what one has to contribute to the marketplace of ideas. I conclude with a brief discussion of possible policy solutions.
Prof. Julie Dorsey
(Yale University, USA)
Bio: Dr. Julie Dorsey is a professor of Computer Science at Yale University, where she teaches computer graphics. She came to Yale from MIT, where she held tenured appointments in both the Department of Electrical Engineering and Computer Science (EECS) and the School of Architecture. She received undergraduate degrees in architecture and graduate degrees in computer science from Cornell University. Her research interests include photorealistic image synthesis, material and texture models, sketch-based modeling, and creative applications of AI. Her current and recent professional activities include service as the Editor-and-Chief of ACM Transactions on Graphics (2012-15) and membership on the editorial boards of Foundations and Trends in Computer Graphics and Vision, Computers and Graphics, and IEEE Transactions on Visualization and Computer Graphics. She has received several professional awards, including MIT’s Edgerton Faculty Achievement Award, a National Science Foundation Career Award, an Alfred P. Sloan Foundation Research Fellowship, along with fellowships from the Whitney Humanities Center at Yale and the Radcliffe Institute at Harvard; she was winner of Microsoft's international Female Founders Competition. She is co-author of Digital Modeling of Material Appearance and the founder and chief scientist of Mental Canvas, a NYC-based software company that is developing a new type of interactive graphical media and a system to design this form of media.
Title of the Talk: The Future of Sketch: How Would Leonardo Draw Today?
(Columbia University, USA)
Bio: Dr. Peter K. Allen is Professor of Computer Science at Columbia University, and Director of the Columbia Robotics Lab. He is the recipient of the CBS Foundation Fellowship, Army Research Office fellowship, the Rubinoff Award for innovative uses of computers, and the NSF PYI award. His current research interests include robotic grasping, medical robotics and Brain-Computer Interfaces for Human- Robot Interaction.
Title of the Talk: Teaching Robots to Grasp via Multi-Modal Geometric Learning
Abstract: Complex, high degree-of-freedom tasks such as grasping and manipulation are often difficult for robots to accomplish. AI and machine learning are promising technologies that can transfer skills from humans to robots. In this talk, we will describe methods to enable robots to grasp novel objects using multi- modal data and machine learning. The starting point is an architecture to enable robotic grasp planning via shape completion using a single occluded depth view of objects. Shape completion is accomplished through the use of a 3D CNN. The network is trained on our open source dataset of over 440,000 3D exemplars captured from varying viewpoints. At runtime, a single 3D depth image captured from a single point of view is fed into the CNN, which fills in the occluded regions of the scene,allowing grasps to be planned and executed on the completed object, which extends to novel objects as well. We have extended this network to incorporate both depth and tactile information. Offline, the network is provided with both simulated depth and tactile information and trained to predict the object's geometry, thus filling in regions of occlusion. At runtime, the network is provided a partial view of an object and exploratory tactile information is acquired to augment the captured depth information.We demonstrate that even small amounts of additional tactile information can be incredibly helpful in reasoning about object geometry.