IEEE World Congress on Computational Intelligence (WCCI 2020)
International Joint Conference on Neural Networks (IJCNN 2020)
IJCNN 2020 Workshop on Secure Learning
Tuesday, July 21 2:00 pm to 6:20 pm (UK time).
02:00-03:00 Keynote – Danger, Danger, Danger - AI's Low Barrier to Entry
Steve Grobman, Senior Vice President and Chief Technology Officer, McAfee LLC, USA
Abstract: For most technology, lowering the barrier to entry drives value and accelerates innovation. For artificial intelligence, however, it is a double edge sword. We often focus on the positive benefits that come with easy to use, low cost AI; however, these same benefits also present a more ominous challenge. In some cases, this dark side is unintentional, such as when an engineer fails to understand the nuance of overfitting, placing organizations at great risk while attempting to detect cyber-attacks. In other cases, the dark side is the result of deception, with worthless technology appearing in products and pedaled as the snake-oil of the 21st century. Most alarmingly, the low barrier to AI and adversarial AI is an accelerant to use AI for nefarious purposes.
03:00-04:00 Keynote – Finding our way to a Safe, Reliable and Robust AI Technology
Dr. Simon See, Director of Nvidia AI Technology Center (Global), Singapore
Abstract: With the recent advancement of machine learning algorithms, techniques and computing power, the adoption of AI have been very pervasive. However like all technology, systems based on AI has it fallency. Obviously failure In critical applications can have catastrophic outcome. Thus we need to seriously build AI systems that are robust and safe which may or may be explainable or interpretable. In this talk, the author briefly discuss the path taken Nvidia AI Technology Center to build a robust and safe AI system.
04:10-05:00 Industry Panel
Title: The Industry View: How Do You Optimize AI Reliability?
Abstract: AI Reliability can be defined as model performance over time. From initial data ingestion to data management throughout the development pipeline to the customer experience, many opportunities exist to optimize this important metric known as Reliability that few have yet to acknowledge. We will examine those critical areas to design reliability up-front in model development, the checks and balances in operational monitors, and customer concerns and feedback. AI Reliability relies on all of these and more, and current democratization of AI can have disastrous, including ethical, consequences. Join our esteemed industry panel discussion by asking challenging questions regarding the best known methods for optimizing AI Reliability.
05:00-06:20 Paper Presentations
05:00-05:20 Joanna Negrete: Semi-supervised Learning To Detect Malicious IP Addresses using Graph Neural Networks
05:20-05:40 Islam Elnabarawy: Survey of Privacy-Preserving Collaborative Filtering
05:40-06:00 Raj Vardhan: GAN-based Anomaly Detection on Malware Data
06:00-06:20 Dipankar Dasgupta: AI is not magic--it is computational logic
Senior Vice President and Chief Technology Officer
Steve Grobman is senior vice president and chief technology officer at McAfee. In this role, he sets the technical strategy and direction to create technologies that protect smart, connected computing devices and infrastructure worldwide. Grobman leads McAfee’s development of next generation cyber-defense and data science technologies, threat and vulnerability research and internal CISO and IT organisations.
Prior to joining McAfee, he dedicated more than two decades to senior technical leadership positions related to cybersecurity at Intel Corporation where he was an Intel Fellow. He has written numerous technical papers and books and holds 30 U.S. patents. He earned his bachelor's degree in computer science from North Carolina State University.
Senior Director and Chief Solution Architect of Nvidia AI Technology Center (Global)
Chief Scientific Computing Officer and Professor of Shanghai Jiao Tong University
Professor Beijing University of Posts and Telecommunications (BUPT)
Professor (Adjunct) KMUTT, NTU (Singapore) and Universitas Indonesia (UI)
Professor Simon See is currently the Solution Architecture and Engineering Director and Chief Solution Architect for Nvidia AI Technology Center. He is also a Professor and Chief Scientific Computing Officer at Shanghai Jiao Tong University, Professor in Beijing University of Posts and Telecommunications (BUPT), and Professor in Universitas Indonesia (UI). He is being conferred as a Distinguished Fudan Scholar in September 2018 by Fudan University, Shanghai, China. Previously Professor See is also the Chief Scientific Computing Advisor for BGI (China) and has a position in Nanyang Technological University (Singapore) and King-Mong Kung University of Technology (Thailand). Professor See is currently involved in a number of smart city projects, especially in Singapore and China. His research interests are in the area of High-Performance Computing, Big Data, Artificial Intelligence, Machine Learning, Computational Science, Applied Mathematics and Simulation Methodology. Professor See is also leading some of the AI initiatives in the Asia Pacific. He is a Steering Committee member of NSCC’s flagship High Performance Computing Conference Supercomputing Asia (SCA) since March 2018.. He has published over 200 papers in these areas and has won various awards.
Professor See is also the member of SIAM, IEEE, and IET. He is also the committee member of more than 50 conferences. Dr. See graduated from the University of Salford (UK) with a Ph.D. in electrical engineering and numerical analysis in 1993. Prior to joining NVIDIA, Dr. See worked for SGI, DSO National Lab. of Singapore, IBM, International Simulation Ltd (UK), Sun Microsystems and Oracle. He is also providing consultancy to a number of national research and supercomputing centers.
Dr. Celeste Fralick
Bio: Celeste Fralick, Senior Principal Engineer and Chief Data Scientist for McAfee in the Office of the CTO, is responsible for innovating advanced analytics at McAfee. She was recently named one of Forbes’ “Top 50 Technical Women in America”, SC Media’s “Women in IT Security”, Industry Leaders “5 Influential Leaders in Cybersecurity” and Insights Success’ “2020’s Most Successful Business Women to Watch.” She has applied machine learning, deep learning, and artificial intelligence to 10 different markets, spanning a 40-year career in quality, reliability, engineering, and data science. Celeste holds a Ph.D. in Biomedical Engineering from Arizona State University, concentrating in Deep Learning, Design of Experiments, and neuroscience.
1. Dr. Mariano Phielipp
Bio: Dr. Mariano Phielipp works at the Intel AI Lab inside the Intel Artificial Intelligence Products Group. His work includes research and development in deep learning, deep reinforcement learning, machine learning, and artificial intelligence. Since joining Intel, Dr. Phielipp has developed and worked on Computer Vision, Face Recognition, Face Detection, Object Categorization, Recommendation Systems, Online Learning, Automatic Rule Learning, Natural Language Processing, Knowledge Representation, Energy Based Algorithms, and other Machine Learning and AI-related efforts. Dr. Phielipp has also contributed to different disclosure committees, won an Intel division award related to Robotics, and has a large number of patents and pending patents. He has published on NeuriPS, ICML, ICLR, AAAI, IROS, ICRA, IEEE, SPIE, IASTED, and EUROGRAPHICS-IEEE Conferences and Workshops.
2. Dr. Petr Somol
Bio: Petr Somol has been active in Machine Learning research for more than 25 years. He obtained his Ph.D. from the Faculty of Mathematics and Physics, Charles University in Prague. He worked as researcher at Cambridge University, UK, and at Czech Academy of Sciences. After years of academic research (https://scholar.google.com/citations?user=GYuMvRMAAAAJ&hl=en&oi=ao) he moved to industry. Having tasted the work of a Software Engineer at Oracle, he later joined Cisco Systems as Head of Research responsible for developing the Machine Learning based engine underlying Cognitive Threat Analytics (https://cognitive.cisco.com/). From February 2020 Petr assumes the role of AI Research Director at Avast Software."
3. Ms. Candace Worley
Bio: Candace Worley joined Ping Identity as Chief Product Officer (CPO) in May of 2020. As CPO, she is responsible for advancing global product vision, leading technical product innovation efforts and bringing the company’s identity solutions to market. Candace has over 25 years of enterprise strategy, product marketing and product development experience with leading companies including Amazon Web Services, McAfee, Intel Corporation and Mentor Graphics. She’s held a myriad of roles including individual contributor and management positions in product management, Business Unit General Management, VP Of Product Marketing and Chief Technical Strategist. Worley holds a bachelor's degree in management from Oregon State University and an MBA degree from Marylhurst University.
Catherine Huang: McAfee LLC, USA ([email protected])
Don Wunsch: Missouri Uni of Science & Technology, USA ([email protected])
Yaochu Jin: University of Surrey, UK ([email protected])
Yew Soon Ong: Nanyang Technological University, Singapore([email protected])
Celeste Fralick: McAfee LLC, USA ([email protected])
Dipankar Dasgupta: University of Memphis, USA( [email protected])
Daniel Tauritz: Auburn University([email protected])
Xinghua Qu: Nanyang Technological University, Singapore, ([email protected])
Xiao Huang: HSBC, UK ([email protected])
Alvin Chan Guo Wei: Nanyang Technological University([email protected])
Guoyang Xie: University of Surrey, UK ([email protected])
Jia Liu: University of Surrey, UK( [email protected])
Samuel Mulder: Sandia National Labs, USA( [email protected])
Srivathsan Srinivasagopalan: AT&T Cybersecurity, USA