Principal Engineer and Senior Staff Data Scientist
McAfee LLC, U.S.A.
Dr. Catherine Huang is a Principal Engineer and Senior Staff Data Scientist at McAfee AI Research. Her research interests are adversarial machine learning, machine learning and artificial intelligence for cybersecurity. She was VIP at Forbes 2021 Roundtable Discussion on Solving for Tech’s Gender Gap. She was a guest speaker of McAfee CTO at MPOWER 2020 Executive Keynotes. Catherine presented her keynote on Adversarial Machine Learning at IEEE SSCI2016. She has 16 patents and 42 papers. Previously, Catherine was a Senior Research Scientist at Security & Privacy Research at Intel Labs in 2011-2017. She directed machine learning research at the Intel Science and Technology Center for Security Computing at University of California Berkeley in 2015-2016. Prior to joining Intel, Catherine was a postdoc researcher at Neurotechnology Lab in Oregon Health & Science University. Catherine received her Ph.D. in Biomedical Engineering from Oregon Health & Science University in U.S., M.S. in Electrical Engineering from University of New Brunswick in Canada, and B.S. degree in Electrical Engineering from South China University of Technology.
Catherine was elected member of IEEE Computational Intelligence Society Administrative Committee for 2020-2021. She serves as the Workshop co-Chair of IJCNN2021 and Secure Learning Task Force Chair of IEEE Neural Networks Technical Committee. She is an Associate Editor of IEEE Transactions of AI and a Guest Editor of Springer Complex and Intelligent System Journal. Catherine was the Chair of IEEE Cognitive and Developmental Systems Technical Committee from 2019-2020. She was the chair of IEEE CIS 1st Technical Challenge in 2019. She has served in the organizing committee for many IEEE conferences including WCCI, SSCI, IJCNN, MLSP.
President of the IEEE Computational Intelligence Society
Sorbonne Université - CNRS, Paris, France
Bernadette Bouchon-Meunier is a director of research emeritus at the National Centre for Scientific Research and Sorbonne University, the former head of the department of Databases and Machine Learning in the LIP6 laboratory. She is the Editor-in-Chief of the International Journal of Uncertainty, Fuzziness and Knowledge-based Systems and the Co-executive director of the IPMU International Conference held every other year since 1986. B. Bouchon-Meunier is the (co)-author of five books and the (co)-editor of 30. She has (co)-authored more than 400 papers on the applications of fuzzy logic and machine learning techniques to decision-making and data science.
She was elected President of the IEEE Computational Intelligence Society for 2020-2021. She is an IEEE Life Fellow, an IFSA Fellow and an Honorary Member of the EUSFLAT Society. She received the 2012 IEEE CIS Meritorious Service Award, the 2017 EUSFLAT Scientific Excellence Award, the 2018 IEEE CIS Fuzzy Systems Pioneer Award and the 2019 Outstanding Volunteer Award of the IEEE France Section.
Fahmida N Chowdhury
National Science Foundation, U.S.
Dr. Fahmida Chowdhury is a Program Director in the NSF Office of International Science and Engineering (OISE). Before joining NSF in 2008, she was a Professor of Electrical and Computer Engineering at the University of Louisiana, Lafayette, where she held the W. Hansen Hall and Mary O. Hall Endowed Chair in Computer Engineering. In NSF/OISE, Fahmida handles a portfolio of countries in South and SE Asia, and a few countries in Eastern Europe. She represents NSF in the Global Research Council’s Gender Working Group. Fahmida received a combined BSc/MSc degree in electromechanical engineering from Moscow Power Engineering Institute, Moscow, Russia (1980), and PhD in electrical engineering from Louisiana State University, Baton Rouge, Louisiana (1988). She was a Fulbright Fellow (2001) and is currently an IEEE Distinguished Lecturer. She is an Associate Editor of the newly launched IEEE Transactions on Artificial Intelligence.
Senior Principal Engineer and Chief Data Scientist
McAfee LLC, U.S.
Celeste Fralick, Senior Principal Engineer and Chief Data Scientist, is responsible for innovating advanced analytics and analytic processes at McAfee. She was named one of Forbes’ inaugural “Top 50 Women in Technology (Americas)” in Dec. 2018 and CDO Magazine’s 2020 & 2021 “Global Power Data Women” while earning her company the coveted 2020 IEEE CIS Outstanding Organization Award. 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 numerous patents and a Ph.D. in Biomedical Engineering from Arizona State University, concentrating in Deep Learning, Design of Experiments, and neuroscience.
Sr. Principal AI Engineer
Intel Corporation, U.S.
Dr. Monica Martinez-Canales is a Sr. Principal AI Engineer at Intel Corporation. She is responsible for driving new opportunities in data analytics, AI/DL/ML algorithms, and mathematics-based breakthroughs for deployment in operational processes, software, platforms, accelerators or Silicon and driving new use cases for Edge-to-Data-Center analytics, supporting software optimization on Intel Architecture, and providing insights on industry trends. Prior to her current role, Monica has been Director and Research Lead of the Applied Research & Pathfinding team for the Autonomous Vehicle R&D Data Center Platform, delivering scalable and distributed perception, privacy, and learning for Autonomous Vehicles; Director of Strategic Mathematics Solutions / Applied Mathematics exploring Clifford algebras and their applications; and Director of Big Data for Science & Technology in Genomics and Precision Medicine developing Big Data and HPC architectures and data flow processes linking genome data to disease risk. Monica joined Intel in 2008 as a Principal Engineer leading Strategic Initiatives in Validation Business Intelligence and Analytics within the Platform Validation Engineering Group developing operational processes to accelerate product delivery schedules.
Prior to joining Intel, Monica had been a Principal Member of the Technical Staff at Sandia National Laboratories, and Principal Investigator leading award-winning research in verification, validation, and quantifications of margins under uncertainty of multi-fidelity, multi-disciplinary complex systems within defense and energy programs. Monica completed a National Science Foundation Post-Doctoral Fellowship at Stanford University. She also conducted postdoctoral research at University of Texas at Austin, where she developed Hilbert Space Filling Curve-based key-value indexing to manage domain decomposition parallelization strategies of numerical Finite Element Models of hyperbolic partial differential equations on Intel Paragon, Cray Y-MP, IBM SP2, and heterogeneous clusters. Monica earned a Ph.D. in Computational and Applied Mathematics from Rice University and received a B.S. in Mathematics from Stanford University. Monica has authored/co-authored multiple reports, papers, presentations, and patents/patent-applications. Monica was named a HENAAC Luminary in 2007, named to Hispanic Business Magazine’s 25 Elite Women in 2009, and profiled in CAWIT’s Women Innovators Series in 2017. Monica has been a long-time STEM/STEAM advocate and mentor.
Research Data Scientist
Dr. Serena Zhang is a senior data scientist with 7+ years of industry experience. Her experiences include building highly scalable data science/ML/analytics solutions and services in an end-to-end manner. Throughput her career, she mostly works through cross-functional collaboration with product, engineering and upper management team steered by business objectives. Currently, she is helping Facebook build products and solutions that protect the privacy of over 3 billion people. Serena received her Ph.D. from University of Washington in U.S.
Professor of Computer Science, IEEE CIS VP Member Activities
Otto-von-Guericke Univeristy Magdeburg, Germany
Sanaz is an active member in international communities. She is the vice president of IEEE Computational Intelligence Society (starting from 2021) and served as adcom member for two terms (2015-2020). She is a technical committee member at IEEE CIS and since 2012 is serving as an associate editor for IEEE transactions on evolutionary computation and since 2020 as an associate editor of IEEE Transactions on AI. She was the chair of task force Evolutionary Multi-objective Optimization of IEEE-CIS and the founding chair for task force Optimization Methods in Bioinformatics and Bioengineering (OMBB) of IEEE-CIS (chair: 2013-2015).
Professor in Computational Intelligence, Chair IEEE Woman in Computational intelligence sub-committee
Manchaster Metropolitan University, UK
Keeley currently leads the Computational Intelligence Lab within Centre for Advanced Computational Science at Manchester Metropolita University, Her main research interests include fuzzy systems, computational approaches to natural language processing, and computational intelligence for psychological profiling (comprehension and deception). She is leading work on Place based practical Artificial Intelligence, facilitating a parliamentary inquiry conducted in 2020 with Policy Connect and the All-Party Parliamentary Group on Data Analytics (APGDA) in June and July 2020 as part of Metropolis funding. She has and is working on numerous projects receiving grants from the European Union H2020 Programme for novel research, the academic co-lead in the ERDF £6m funded GM Artificial Intelligence Foundry, to Innovate UK funding where the focus is on knowledge transfer partnerships with business. Keeley is currently the Chair of the IEEE Women into Computational Intelligence sub-committee, Co-Chair of the IEEE WIE Educational Outreach sub-committee, IEEE UKRI SIGHT Ethics and Wellbeing officer and a member of numerous CIS subcommittees. She is a Senior Fellow of the Higher Education Academy. Keeley serves as an Associate Editor on the IEEE Trans. Emerging Topics in Computational Intelligence, IEEE Trans. Artificial intelligence and IEEE Trans on Fuzzy systems. She is the current Chair of the IEEE Task Force on Ethical and Social Implications of Computational Intelligence and will serve as Co-General Chair at IEEE SSCI, Orlando 2021. She is Track Chair AI and Big Data at IEEE ISC2 2021 IEEE International Smart Cities Conference – 2021 and Workshop Chair at 2021 IEEE INTERNATIONAL HUMANITARIAN TECHNOLOGY CONFERENCE (IHTC 2021).