ADIA Lab Fellows
Thomas Hardjono
CTO of Connection Science and Technical Director of the MIT Trust-Data Consortium at MIT in Cambridge, MA. USA.
Dr. Hardjono is an early pioneer in the field of digital identities and trusted hardware, and has been instrumental in the development and broad adoption of the MIT Kerberos authentication protocol. His activities include leading standard development efforts, notably at the IETF, IEEE, Trusted Computing Group, Confidential Computing Alliance and others.
He has published more than 70 technical conference/journal papers, several books and more than 30 patents. He is currently involved in several startups around the MIT community. His current area of interest is Web3 Digital Assets, focusing on the interoperability of asset networks and survivability against cybersecurity attacks.
Francisco "Paco" Herrera
Professor in the Department of Computer Science and Artificial Intelligence at the University of Granada and Director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI). Member of the Royal Academy of Sciences (Spain).
Professor Herrera received his M.Sc. in Mathematics in 1988 and Ph.D. in Mathematics in 1991, both from the University of Granada, Spain. He is an academician of the Royal Academy of Engineering (Spain) and has published more than 600 journal papers, receiving more than 130,000 citations (Scholar Google, H-index 173), and acts as editorial member of a dozen academic journals. Professor Herrera has been nominated as a Highly Cited Researcher in the fields of Computer Science, Engineering and Clarivate Analytics).
His current research interests include, among others, computational intelligence, information fusion and decision making, explainable artificial intelligence and data science (including data preprocessing, prediction and big data)
Torsten Hoefler
Professor of Computer Science at ETH Zurich, Winner of the Gordon Bell Prize (2019), a member of Academia Europaea, and a Fellow of the ACM and IEEE.
Professor Hoefler, guided by a "Performance as a Science" vision, integrates mathematical models of architectures and applications to design optimized computing systems. Before joining ETH Zurich, he led the performance modeling for the Blue Waters supercomputer at the University of Illinois at Urbana-Champaign and contributed significantly to the Message Passing Interface (MPI) standard as chair of the "Collective Operations and Topologies" group.
He has received multiple best paper awards at ACM/IEEE Supercomputing (2010, 2013, 2014, 2019, 2022) and other international conferences. His accolades include the IEEE CS Sidney Fernbach Memorial Award in 2022 and the ACM Gordon Bell Prize in 2019. Elected to the steering committee of ACM's SIGHPC in 2013, he has been re-elected each term since. His research focuses on performance-centric system design, scalable networks, parallel programming techniques, and performance modeling for large-scale simulations and AI systems.
Soh Young In
Assistant Professor in the Department of Civil and Environmental Engineering and an Affiliate Faculty of the Graduate School of Green Growth and Sustainability at the Korea Advanced Institute of Science & Technology (KAIST)
Soh Young In focuses on environmental, social, and economic incentives for low-carbon transitions and sustainable infrastructure systems. Her primary research topics include "Climate Risk Analysis," "Sustainable Integration," and "Data-Driven System Transformation."
She is also a Research Fellow at the Sustainable Finance Initiative (SFI) at the Stanford Doerr School of Sustainability. Soh Young holds a B.A. in Economics and Statistics from Columbia University, an M.A. in International Policy from Stanford University, and a Ph.D. in Civil and Environmental Engineering from Stanford University.
Michael Wolf
Professor of Econometrics and Applied Statistics, University of Zurich.
Michael Wolf is a Professor of Econometrics and Applied Statistics at the University of Zurich, and holds a Ph.D. in Statistics from Stanford University. Before joining the University of Zurich's Department of Economics, he held positions at the University of California, Los Angeles (UCLA), Universidad Carlos III de Madrid, and Universitat Pompeu Fabra in Barcelona.
His research interests include resampling-based inference, multiple testing methods, the estimation of large-dimensional covariance matrices, and financial econometrics. His work has been published in leading journals such as The Annals of Statistics, Biometrika, Econometrica, Journal of the American Statistical Association, and The Review of Financial Studies.
Praneeth Vepakomma
Assistant Professor, Department of Machine Learning, Mohamed Bin Zayed University of Artificial Intelligence
Praneeth Vepakomma recently submitted his PhD at the Massachusetts Institute of Technology (MIT) and is now an Assistant Professor in the Department of Machine Learning at Mohamed Bin Zayed University of Artificial Intelligence in Abu Dhabi.
He has extensive industrial experience from his time at Meta, Apple, Amazon Web Services, Motorola Solutions, Corning and several startups. He has won the Meta PhD research fellowship in Applied Statistics and two SERC Scholarships (for Social and Ethical Responsibilities of Computing) from MIT's Schwarzman College of Computing. He co-founded a research based non-profit (Integrity Distributed) that won the Financial Times Digital Innovation Award.
He holds an MS in Mathematical and Applied Statistics from Rutgers University. His research focuses on developing algorithms for distributed computation in statistics & machine learning under constraints of privacy and efficiency.
Emilio Porcu
Department of Mathematics, Khalifa University and Visiting Professor, Trinity College Dublin.
Professor Emilio Porcu earned his Ph.D. in Statistics in 2005 and became a full professor in 2012, serving as Chair of Statistics at Newcastle University and later at Trinity College, Dublin. Since August 2020, he has been a Professor of Statistics and Data Science at Khalifa University and is a member of the Biotechnology Research Center. He has also held roles as Senior Scientist at the MIDAS Research Center in Santiago, Chile, co-Chair of Spatial Analytics in Newcastle, and Adjoint Professor at ADAPT Trinity College.
His research focuses on Statistical and Machine Learning, Data Science, and Spatial Statistics, with over 160 peer-reviewed papers published in leading journals. His work addresses climate change, catastrophes, weather forecasting, spatial criminology, and more recently, Health Data Science, including applications in computational genetics, genomics, and aging.
Oleksiy Kondratyev
Visiting Professor at the Department of Mathematics, Imperial College London, UK.
Oleksiy holds MSc in Theoretical Physics from Taras Shevchenko National University of Kyiv and PhD in Mathematical Physics from the Institute for Mathematics, National Academy of Sciences of Ukraine. His primary research interests are in quantitative finance, machine learning and quantum computing.
Oleksiy has over 20 years of quantitative finance experience in both risk management and front office roles and has been recognized as Quant of the Year (2019) by Risk magazine for his research on the application of machine learning techniques to risk factor analysis and portfolio optimisation.
Visiting Fellows
Luis Seco
Professor of Mathematics at the University of Toronto and Director of Risklab in Toronto, Canada.
Professor Seco’s core activity is bringing artificial intelligence into today’s sustainability challenges to build a new and better world.
His has extensive expertise in developing University-Industry relationships, which he has done since 1996. In October 2007, he won the Natural Sciences and Engineering Research Council of Canada Synergy Award for Innovation. In 2011, he was admitted Caballero de la Orden del Mérito Civil (Knight of the Order of Civil Merit), an award from the Government of Spain for his application of mathematics to foresee economic cycles.
Professor Seco ’s career started at Princeton University in 1985, and landed at the University of Toronto in 1992 after a short stay at the California Institute of Technology. Today, he holds adjunct appointments at Renmin University in Beijing, Florida International University, the Technical University of Munich, the University of Zurich and Kutaisi International University.
Siddiq Anwar
Consultant Nephrologist and Clinical Associate Professor of Medicine at Sheikh Shakhbout Medical City (SSMC) and Khalifa University, Abu Dhabi, UAE.
Dr. Anwar believes in using data-driven decision-making in healthcare and process optimization to improve overall healthcare outcomes. He spearheaded the digitalization of the End Stage Renal Disease program in Abu Dhabi Health Services Company (SEHA), the digitalization of the Complete Acute Kidney Injury Management pipeline at SSMC and helped set up the Paired Kidney Exchange program in UAE. This work has been awarded by HIMSS, the Arab Hospitals Federation, and the Patient Safety Conference. He also was awarded the best nephrologist in the UAE award by Health Magazine in 2023.
He is collaborating with colleagues from Khalifa University and the Mohamed Bin Zayed University of Artificial Intelligence to develop an AI Platform, “RenAIssance” to help improve Acute Kidney Injury outcomes. This team won the grand prize in a hackathon organized by Ericsson & UAE Ministry of Economy and was a semifinalist in the 3C-AI4H Bowl-Institute for Augmented Intelligence in Medicine (I.AIM), at Northwestern University, USA. In addition, he has received a Research grant from the Department of Health, Abu Dhabi.
Mecit Can Emre Simsekler
Associate Professor in the Department of Management Science & Engineering, Khalifa University, Abu Dhabi, UAE.
Dr. Simsekler is an Associate Professor and the Associate Chair for Graduate Studies in the Department of Management Science and Engineering at Khalifa University of Science and Technology. Additionally, he serves as a visiting scholar at Boston Children’s Hospital (Teaching Hospital of Harvard Medical School) and the University College London (UCL) School of Management. He received his PhD from the University of Cambridge. During his PhD, he was a visiting researcher in the Center for Medical Innovation System at the University of Tokyo and the Center for Patient Safety and Quality Research at Boston Children’s Hospital. After completing his PhD, he worked as a Research Associate at the UCL School of Management.
Dr Simsekler’s research interests span healthcare analytics and management to improve operational and safety outcomes and accelerate risk-based decision-making. Leveraging business analytics, design thinking, and systems thinking, his current research focuses on AI-driven digital transformation in building high-value, human-centered, and sustainable health systems. Dr Simsekler is the recipient of the 2022 Outstanding Global Faculty Advisor Recognition Award from the IISE, the world's largest professional society for industrial and systems engineers.
Jorge P. Zubelli
Professor and Chair of the Mathematics Department at Khalifa University.
Professor Zubelli obtained his PhD in Applied Mathematics from the University of California at Berkeley (1989), his MSc from the National Institute for Pure and Applied Mathematics (IMPA – Brazil) in 1984, and his Electrical Engineering degree from IME-RJ in 1983 with specialization on Telecommunications Engineering. He has previous experience as Professor of Mathematics at IMPA and has headed the Laboratory for Analysis and Mathematical Modeling in the Physical Sciences (LAMCA – IMPA) and, from 2002 to 2017, he coordinated the Mathematical Methods in Finance Professional MSc program at IMPA.
His main research area is Inverse Problems and Mathematical Modeling with focus on its applications to real world problems. He has published research in highly selective journals such as Science, Plos One, SIAM Journal of Numerical Analysis, SIAM Journal on Applied Mathematics, and Physical Review B. He has coordinated a number of academic and industrial projects and research networks.
Professor Zubelli has served as a member of a number of editorial boards and currently serves on the editorial board of the International Journal of Applied Finance (IJTAF), Mathematics and Computers in Simulation, and Advances in Continuous and Discrete Models.
Farah Shamout
Assistant Professor of Computer Engineering at NYU Abu Dhabi, UAE.
Farah Shamout is an Assistant Professor of Computer Engineering at NYU Abu Dhabi, where she leads the Clinical Artificial Intelligence Lab. She is also an Associated Faculty at the NYU Tandon School of Engineering (Computer Science & Engineering and Biomedical Engineering Departments) and an Affiliated Faculty at NYU Langone Health (Radiology).
At the Clinical AI Lab, Dr. Shamout is interested in developing machine learning methods and systems using heterogeneous real-world data for applications in computational precision health, including electronic health records data and medical imaging. Methodologies of interest pertain to multi-modal learning, foundation models, and trustworthiness, to achieve high performance and utility in clinical practice.
Dr. Shamout completed her DPhil (PhD) in Engineering Science at the University of Oxford as a Rhodes Scholar and was a member of Balliol College. She also completed her BSc in Computer Engineering (cum laude) at NYU Abu Dhabi.
Saleh Ibrahim
Associate Dean for Research, Professor of Medical Sciences, Khalifa University, Abu Dhabi, UAE.
Saleh Ibrahim earned his Bachelor of Medicine in Egypt, then obtained an MD in Immunology from Helsinki University. He completed postdoctoral training in molecular genetics at Princeton University, studying the genetic basis of autoimmunity, before leading a group at the University of Rostock in 1997. In 2008, he became a professor of Genetics at Luebeck University and joined Khalifa University in 2022.
Dr. Ibrahim's research focuses on investigating population differences in genetic susceptibility to complex diseases, as well as exploring the role of gene-microbiota interactions in the pathogenesis of age-related diseases.