Quantum computing is evolving fast and is challenging the security of the existing computing systems and the entire digital industry – beyond a certain threshold of computing power, it can break several classical public-key cryptography protocols. On the other end of the quantum evolution, quantum cryptography, random number generation, and quantum key distribution capabilities developed on top of quantum systems can support somewhat stronger security and privacy guarantees but are more expensive to support and can only be used with certain other constraints. Post-quantum cryptography, quantum random number generation, quantum key distribution, and quantum cryptography are evolving fast, and are building blocks of the remediation plan against quantum threats and for a viable quantum network in future. In this panel, we plan to discuss the post-quantum cryptography and security threats and what needs to be the technical and business execution plan to remain secure against such threats.
Bio - Dr. Ashish Kundu is a distinguished scientist, a leader in the area of Security, Privacy, Compliance and AI Ethics, and a distinguished speaker. He is currently working as a Head of Cybersecurity Research at Cisco Research. He has led security and compliance of self-driving cars, tele-operated driving, across all the stacks. He has also led the security and compliance of cloud-based healthcare, and cloud-based AI-driven education platforms. He has led cybersecurity of Nuro as its Head of Cybersecurity. Dr. Kundu also worked as a Master Inventor and Research Staff Member at IBM T J Watson Research Center. His research has led to more than 150 patents filed with more than 110 patents granted, and more than 40 research papers. Dr. Kundu received his Ph.D. in Cybersecurity from Purdue University. His work has been recognized with several awards and honors. Dr. Kundu has been honored with the prestigious Master Inventor recognition multiple times by IBM Research, New York. He has been privileged to be recognized as an ACM Distinguished Member, and in the past, he has been named as an ACM Distinguished Speaker. Dr. Kundu’s doctoral research at Purdue University received the prestigious CERIAS Diamond Award for his outstanding contributions to cybersecurity.
Bio Craig Costello is a Principal Researcher in the Cryptography and Security Group at Microsoft Research. His current research aims to develop efficient, compact, and secure post-quantum cryptography using supersingular isogenies.
Bio - Dr. Bing Qi is a quantum communication researcher at Cisco Systems, Inc. Prior to joining Cisco, he was a senior research scientist at Oak Ridge National Laboratory, Oak Ridge, TN, USA, and a Joint Faculty Associate Professor with the Department of Physics and Astronomy, the University of Tennessee, Knoxville, TN, USA. Dr. Qi received the B.S. degree in physics from Nanjing University, Nanjing, China, in 1990, and the Ph.D. degree in optical instruments from the Dalian University of Technology, Dalian, China, in 1996. From 1996 to 1999, he was a Postdoctoral Researcher at Tsinghua University, China. From 1999 to 2002, he was a Visiting Scholar at Virginia Tech, Blacksburg, VA, USA. From 2002 to 2013, he held various positions as a Postdoctoral Researcher, a Research Associate, and a Senior Research Associate with the University of Toronto, Toronto, ON, Canada. His noticeable works include the first demonstration of the decoy-state quantum key distribution (QKD) protocol, the invention and demonstration of measurement-device-independent QKD, the invention and demonstration of quantum random number generator based on laser phase noise, and the development of continuous variable QKD scheme using a true local oscillator. His current research interests include quantum cryptography, quantum network and optical sensing.
Bio - Vadim Lyubashevsky is a principal research scientist in the security group at IBM Research Europe in Zurich. He received his Ph.D. from the University of California San Diego in 2008, and then held positions as a post-doc at Tel Aviv University, and as a researcher at Inria in Paris. He was a recipient of a Starting European Research Council (ERC) research grant for developing constructions of practical lattice-based encryption and digital signatures, and is currently a holder of a Consolidator ERC grant focused on constructing next-generation lattice-based zero-knowledge protocols. The work of Vadim and his colleagues on the Ring-LWE problem and lattice-based digital signatures laid the foundations for today's most efficient lattice-based constructions. He is currently actively involved in the NIST PQC standardization process, being a part of consortia for three submissions, all of which are among the finalists.
Bio - Michele Mosca is co-founder of the Institute for Quantum Computing at the University of Waterloo, a Professor in the Department of Combinatorics & Optimization of the Faculty of Mathematics, and a founding member of Waterloo's Perimeter Institute for Theoretical Physics. He is co-founder and CEO of the quantum-safe cybersecurity company, evolutionQ, and co-founder of the quantum software and applications company, softwareQ. He serves as co-chair of the board of Quantum Industry Canada. He started working in cryptography during his undergraduate studies and obtained his doctorate in Mathematics in 1999 from the University of Oxford on the topic of Quantum Computer Algorithms. His research interests include algorithms and software for quantum computers, and cryptographic tools designed to be safe against quantum technologies. He co-founded the not-for-profit Quantum-Safe Canada, and the ETSI-IQC workshop series in quantum-safe cryptography and is globally recognized for his drive to help academia, industry and government prepare our cyber systems to be safe in an era with quantum computers. Dr. Mosca’s awards and honours include 2010 Canada's Top 40 Under 40, Queen Elizabeth II Diamond Jubilee Medal (2013), SJU Fr. Norm Choate Lifetime Achievement Award (2017), and a Knighthood (Cavaliere) in the Order of Merit of the Italian Republic (2018).
In the new digital world, data and its use governs the life of individuals. Data collection is ubiquitous and the use of Artificial Intelligence and Machine Learning tools often means that decisions are made regarding individuals using data that may or may not be collected with their consent and/or knowledge. This affects individuals in all spheres of their life: the private sphere, in public spaces, when receiving governmental services, and in their commercial activities. Fairness and equity is crucial to ensure that the results of advanced analytics provide equitable benefits to all people and do not unfairly benefit one subpopulation over another. At the same time, ensuring the privacy the data is necessary, given the sensitivity of personal data and the potential for its misuse. However, there may be an inherent tension between ensuring both privacy and fairness. This panel will explore several issues related to ensuring both privacy and fairness in analytics, including questions such as: Are privacy and fairness inherently conflicting? Is it at the data level or at the level of results? How do we balance fairness and privacy in the analysis of personal data? Can black-box algorithms be both privacy-preserving and fair? What are the key technical challenges in this area? What technological advances do you expect to see?
Bio - Jaideep Vaidya is a Professor in the MSIS Department at Rutgers University and the Director of the Rutgers Institute of Data Science, Learning, and Applications. He received the B.E. degree in Computer Engineering from the University of Mumbai, the M.S. and Ph.D. degree in Computer Science from Purdue University. His general area of research is in data mining, data management, security, and privacy. He has published over 190 technical papers in peer-reviewed journals and conference proceedings, and has received several best paper awards from the premier conferences in data mining, databases, digital government, security, and informatics. He has also received the NSF Career Award, the Rutgers Board of Trustees Research Fellowship for Scholarly Excellence, and the Junior Faculty Research Award from Rutgers Business School. He is a Fellow of the IEEE and an ACM Distinguished Scientist.
Bio Murat Kantarcioglu is Ashbel Smith professor of Computer Science and the director of the UTD Data Security and Privacy Lab at The University of Texas at Dallas. He holds a BS in Computer Engineering from Middle East Technical University, and MS and PhD degrees in Computer Science from Purdue University. He is the recipient of an NSF CAREER award and a Purdue CERIAS Diamond Award for academic excellence. Currently, he is also a visiting scholar at Harvard's Data Privacy Lab. Kantarcioglu's research focuses on creating technologies that can efficiently extract useful information from any data without sacrificing privacy or security. His research has been supported by awards from NSF, AFOSR, ONR, NSA, and NIH. He has published over 165 peer-reviewed papers. His work has been covered by media outlets such as the Boston Globe and ABC News, among others, and he has received three best paper awards. He is an AAAS Fellow, IEEE Fellow and ACM distinguished scientist.
Bio - Ling Liu is a Professor in the School of Computer Science at Georgia Institute of Technology. She directs the research programs in Distributed Data Intensive Systems Lab (DiSL), examining various aspects of large scale big data systems and analytics, including performance, availability, security, privacy and trust. Prof. Liu is an elected IEEE Fellow and a recipient of IEEE Computer Society Technical Achievement Award (2012). She has published over 300 international journal and conference articles and is a recipient of the best paper award from numerous top venues, including ICDCS, WWW, IEEE Cloud, IEEE ICWS, ACM/IEEE CCGrid. In addition to serve as general chair and PC chairs of numerous IEEE and ACM conferences in big data, distributed computing, cloud computing, data engineering, very large databases fields, Prof. Liu served as the editor in chief of IEEE Transactions on Service Computing (2013-2016), on editorial board of over a dozen international journals. Ling’s current research is sponsored primarily by NSF and IBM.
Bio - Gerome Miklau is a Professor of Computer Science at the University of Massachusetts, Amherst. His research focuses on private, secure, and equitable data management. He designs algorithms to accurately learn from data without disclosing sensitive facts about individuals, primarily in the model of differential privacy. He studies fair and responsible data management. He has also designed novel techniques for controlling access to data, limiting retention of data, and resisting forensic analysis. He recently co-founded Tumult Labs, a start-up focused on commercializing privacy technology. Prior to that, he consulted for the U.S. Census Bureau on algorithms that will be deployed for the 2020 decennial census. Professor Miklau received the ACM PODS Alberto O. Mendelzon Test-of-Time Award in both 2020 and 2012, the Best Paper Award at the International Conference of Database Theory in 2013, a Lilly Teaching Fellowship in 2011, an NSF CAREER Award in 2007, and he won the 2006 ACM SIGMOD Dissertation Award. He received his Ph.D. in Computer Science from the University of Washington in 2005. He earned Bachelor's degrees in Mathematics and in Rhetoric from the University of California, Berkeley, in 1995.
Bio - Vivek Singh is an Associate Professor in the School of Communication and Information and the Director of the Behavioral Informatics Lab at Rutgers University. His research lies at the intersection of Computational Social Science, Data Science, and Multimedia Information Systems. Before joining Rutgers, he was a post-doctoral researcher at the MIT Media Lab. He holds a Ph.D. in Information and Computer Science from the University of California, Irvine. His work has appeared in leading disciplinary and interdisciplinary publication venues (e.g. Science, ACM CHI, JASIST) and has been covered by popular media (e.g. New York Times, BBC, Wall Street Journal). Singh's research is supported by the US National Science Foundation and Google.
The SARS-CoV-2 virus was first identified to cause severe respiratory illness in December 2019. The World Health Organization (WHO) declared it as a Public Health Emergency of International Concern on 30 January 2020, and a pandemic on 11 March 2020. The whole world was quite unprepared for this pandemic of epic proportions that has caused severe public health, economic, and social disruptions, including the largest global recession since the Great Depression in the 1930s. Although, taken aback initially, the global scientific community has now taken the bull by its horns and began to fight back. Information Technology, especially developments in machine intelligence, collaborative computing and trust, security and privacy has played key role in the global war against the pandemic, starting with novel methodologies for rapid vaccine development, newer techniques for contact tracing, health monitoring, well-being and patient care, to efforts to fight spread of misinformation, enhance social support, remote workplace and so on. In this panel, four eminent scholars in the IT area discuss their views on what have been achieved so far and how we can be better prepared from an IT perspective to face Pandemic 2023 heads on.
Bio - Dr. Indrajit Ray is a Professor and Associate Chair of Computer Science at Colorado State University. He is also Co-Director of the NSF IUCRC Center for Cybersecurity Analytics and Automation and leads the Database and Applications Security Research Group. His primary research interests are in computer security and privacy. His major research contributions have been in security and privacy models, in security risk modeling, trust model, and access control models, and in security protocol design using applied cryptographic techniques. His research has been well funded through various federal agencies. He has advised and co-advised several Ph.D. students many of whom hold tenured positions in academia. He recently completed a stint at the U.S. National Science Foundation where he served as a Program Director in the Secure and Trustworthy Cyberspace (SaTC) program. During his career Dr. Ray has served on various program committees, panels, and academic review committees. He has also played leadership roles in the academic community by serving as program chairs in various conferences, such as, the General Chair of the 2015 ACM Conference on Computer and Communications Security, and the General Chair of the 2017 IEEE Communications and Network Security conference. He currently serves on the editorial board of two journals including the IEEE Transactions on Services Computing and the International Journal on Security and Networks. He was the founder of the IFIP TC 11, WG 11.9 on Digital Forensics and its first Chair. He is a Senior Member of both the IEEE and the ACM and a member of IFIP TC-11.
Bio Dr. Ritwik Banerjee is Research Assistant professor at the Department of Computer Science, Stony Brook University, and affiliated with the Institute for AI-Driven Discovery and Innovation. In 2017, Dr. Banerjee held a joint appointment with the Department of Computer Science and the Department of Emergency Medicine, Stony Brook School of Medicine. Dr. Banerjee received his Ph.D. in Computer Science from Stony Brook University in December 2015. Prior to joining the department as a doctoral student, he had worked in several technology startups in India after receiving a M.Sc. in Computer Science and B.Sc. in Mathematics and Computer Science, both from Chennai Mathematical Institute, India. Dr. Banerjee’s areas of interest are natural language processing (NLP), machine learning (ML), and artificial intelligence (AI), with a focus on two areas in particular: learning in the biomedical domain for applications in healthcare informatics, and language use & society. He has made significant contributions in these areas. Dr. Banerjee’s team has developed AI-driven systems that can distill patient-specific information from large amounts of natural language data as well as structured databases. This has led to automatic recommendation of the most relevant laboratory tests for a patient, depending on the precise circumstances, and personalized identification of adverse drug reactions and attribution of patient's symptoms to their drug regimen. More recently, Dr. Banerjee has been studying the evolution and spread of misinformation in healthcare. Changes in the meaning of information as it passes through cyberspace can mislead those who access the information. Dr. Banerjee’s work develops a new dataset and algorithms to identify and categorize medical information that remains true to the original meaning or undergoes distortion.
Bio - Dr. Nalini Venkatasubramanian is a Professor of Computer Science in the Donald Bren School of Information and Computer Sciences at the University of California, Irvine. She is known for her work in effective management and utilization of resources in the evolving global information infrastructure. Her research interests are Multimedia Computing, Networked and Distributed Systems, Internet technologies and Applications, Ubiquitous Computing and Urban Crisis Responses. Dr. Venkatasubramanian's research focuses on enabling effective management and utilization of resources in the evolving global information infrastructure. She also addresses the problem of composing resource management services in distributed systems. As a key member of the Center for Emergency Response Technologies at UC Irvine, Dr. Venkatasubramanian recent research has focused on enabling resilient, sustainable and scalable observation and analysis of situational information from multimodal input sources; dynamic adaptation of the underlying systems to enable information flow under massive failures and the dissemination of rich notifications to members of the public at large. She is the recipient of the prestigious NSF Career Award, an Undergraduate Teaching Excellence Award from the University of California, Irvine in 2002 and multiple best paper awards. Prof. Venkatasubramanian has served in numerous program and organizing committees of conferences on middleware, distributed systems and multimedia and on the editorial boards of journals. She received her M.S and Ph.D in Computer Science from the University of Illinois in Urbana-Champaign. Her research is supported both by government and industrial sources such as NSF, DHS, ONR, DARPA, Novell, Hewlett-Packard and Nokia. Prior to arriving at UC Irvine, Nalini was a Research Staff Member at the Hewlett-Packard Laboratories in Palo Alto, California.
Bio - Dr. Ramesh Raskar is Associate Professor of Media, Arts and Sciences and NEC Career Development Professor at MIT Media Lab and directs the Camera Culture research group. His focus is on AI and Imaging for health and sustainability. They span research in physical (e.g., sensors, health-tech), digital (e.g., automated and privacy-aware machine learning) and global (e.g., geomaps, autonomous mobility) domains. Dr. Raskar joined the Media Lab from Mitsubishi Electric Research Laboratories in 2008. Recent projects and inventions include transient imaging to look around a corner, a next generation CAT-Scan machine, imperceptible markers for motion capture (Prakash), long distance barcodes (Bokode), touch+hover 3D interaction displays (BiDi screen), low-cost eye care devices (Netra, Catra), new theoretical models to augment light fields (ALF) to represent wave phenomena and algebraic rank constraints for 3D displays (HR3D). In 2004, Dr. Raskar received the TR100 Award from Technology Review, which recognizes top young innovators under the age of 35, and in 2003, the Global Indus Technovator Award, instituted at MIT to recognize the top 20 Indian technology innovators worldwide. In 2009, he was awarded a Sloan Research Fellowship. In 2010, he received the Darpa Young Faculty award. Other awards include Marr Prize honorable mention 2009, LAUNCH Health Innovation Award, presented by NASA, USAID, US State Dept and NIKE, 2010, Vodafone Wireless Innovation Project Award (first place), 2011. He holds over 40 US patents and has received four Mitsubishi Electric Invention Awards. He is currently co-authoring a book on Computational Photography.
Bio - Dr. Calton Pu is Professor and John P. Imlay, Jr. Chair in Software in the College of Computing at Georgia Tech. He is also the Director of the Center for Experimental Research in Computer Systems and affiliate faculty of Institute for Information Security and Privacy (IISP) at Georgia Tech. Dr. Pu’s research interests are in the areas of service computing, distributed and cloud computing, integration, and veracity of big data. He has worked on several projects in systems and database research. His contributions to systems research include program specialization and software feedback. His contributions to database research include extended transaction models and their implementation. His recent research has focused on automated system management in clouds, information quality (e.g., spam processing), and big data in Internet of Things. His current projects include cloud computing (WISE/Elba project) and big data (GRAIT-DM project) research. Using experimental data from realistic benchmarks, the WISE project studies the interesting phenomena such as very short bottlenecks that have large impact on n-tier system response time. The GRAIT-DM project collects real world data from social sensors (e.g., Twitter and Facebook) and authoritative sources (e.g., CNN.COM and CDC for COVID-19 information) to detect physical events and manage real-time information on them. The sponsors for Dr. Pu’s research include both government funding agencies such as NSF, and companies from industry such as HP, Fujitsu, and IBM. He is also the director of RCN on Big Data for Smart Cities, managed as part of the GRAIT-DM project. He has collaborated extensively with scientists and industry researchers all around the world.