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Mohan KelkarView profile

Professor

• Reservoir Engineering
• Production Optimization
• Petroleum Economics
• +2 more

Mohan Kelkar serves as an Applied Professor of Petroleum Engineering at The University of Tulsa, holding a prominent position within the McDougall School of Petroleum Engineering under the College of Engineering & Computer Science. With over 60 refereed publications, 250+ technical presentations, and three authoritative books—including the SPE best-seller 'Applied Geostatistics for Reservoir Description'—he has established himself as a leading figure in petroleum engineering research and education. His academic credentials include: Ph.D. in Chemical Engineering, University of Pittsburgh (1982) M.S. in Petroleum Engineering, University of Pittsburgh (1981) B.S. in Chemical Engineering, University of Mumbai (1979) Dr. Kelkar's research centers on reservoir optimization, production modeling, and development planning for oil and gas reservoirs, with significant contributions to petroleum economics and expert consultation in oilfield legal disputes. His work bridges advanced engineering techniques with economic evaluation frameworks, particularly evident in his books 'Natural Gas Production Engineering' and 'Petroleum Economics and Property Evaluation.' Analysis of his 15 most recent publications reveals a dominant focus on reservoir simulation methodologies, unconventional resource development, and innovative optimization techniques. Key trends include the application of fast marching methods for well placement, liquid loading prediction in gas wells, and shale reservoir modeling, demonstrating consistent evolution from foundational reservoir engineering toward cutting-edge computational approaches. His exceptional contributions have been recognized through numerous prestigious awards: SPE International Honorary Member Award (2024) SPE Distinguished Service Award (2018) The University of Tulsa Outstanding Teacher Award (2014) SPE International Distinguished Member Award (2010) Tau Beta Pi Teaching Excellence Award (2001) Dr. Kelkar maintains active professional engagement through SPE leadership roles—including Board of Directors service (2010-2013) and General Chair of the SPE IOR meeting (2006)—while balancing academic responsibilities with community leadership as President of the South Asian Performing Arts Foundation. His career exemplifies the integration of scholarly rigor, industry impact, and cultural contribution within the petroleum engineering discipline.

Foto N. AfratiView profile

Professor

• Parallel and distributed computation
• Processing of very large data
• MapReduce
• +6 more

Professor Foto N. Afrati is a Distinguished Faculty Member at the National Technical University of Athens, specifically within the School of Electrical and Computing Engineering and the Division of Communication, Electronic and Information Engineering. She has held this position since 1993, following previous academic ranks at the same university as Associate Professor (1989-1993), Assistant Professor (1985-1989), Lecturer (1982-1985), and Research Fellow (1980-1982). She completed her PhD in Electrical Engineering at Imperial College of the University of London in March 1980, with a dissertation focused on Error Correcting Codes by Algorithms. Her academic journey also included a Diploma from Imperial College (March 1980) and an earlier Diploma in Electrical and Mechanical Engineering from the National Technical University of Athens (June 1976). Professor Afrati's research interests span several critical areas in computer science: Parallel and distributed computation Processing of very large data (including MapReduce) Data and web mining Database Systems Information integration Query optimization Computation and complexity of algorithms Approximation algorithms Her most recent publications demonstrate expertise in MapReduce environments, query optimization with views, and data exchange frameworks. These works are published in prestigious venues like EDBT, VLDB, PODS, and ICDT, with specific focus areas including adaptive sampling techniques, data source integrity, and algorithm complexity in database environments. Professor Afrati has received significant recognition in her field, including Fellow of the Association for Computing Machinery (ACM) Best Paper Award at the International Conference on Database Theory (ICDT) 2009 She has advised numerous PhD students throughout her career, including Theodoros Mitakos, Ezz Hattab, Nikos Kiourtis, and Angelos Vasilakopoulos. Her current PhD students include Victor Kyritsis and Nikos Stassinopoulos. Professor Afrati maintains strong professional networks through her various visiting positions at institutions such as Google, Stanford University, IBM Research Center, University of Helsinki, University of Paris, DIMACS, and others. She has served as associate editor and reviewer for major academic journals and conferences including IEEE TKDE, ACM Transactions of Database Systems (TODS), Journal of ACM (JACM), and Theoretical Computer Science (TCS). Her extensive work in research projects spans both national and international initiatives, with funding from sources including the European Union's Thalis project, ESPRIT working groups, HCM networks, and Greek General Secretariat of Research and Technology grants.

• Applied Geophysics
• Glaciology
• Geophysical Data Integration
• +3 more

Alberto Godio is a Full Professor at the Politecnico di Torino, affiliated with the Department of Environmental, Land and Infrastructure Engineering (DIATI). He coordinates Latin America relations under the University Strategic Plan and is a member of the Interdepartmental Center Photonext for Applied Photonics. His research focuses on Applied Geophysics, Geophysical Data Integration, and Glaciology. He graduated in Mining Engineering (1988) and earned a PhD in Underground Resources Engineering (1993). He has been an Associate Professor (2005-2024) and Full Professor (2024-present) at PoliTO, leading projects funded by EU (FP7, LIFE, Horizon), MIUR (PRIN, FIRB), and regional bodies. His recent publications explore geophysical methods for subsurface modeling, glacial systems, and environmental remediation, with keywords spanning Geophysics, Hydrology, and Climate Science. His work emphasizes ground-penetrating radar, seismic noise analysis, and hybrid modeling techniques. Scientific awards include the Best Paper Award at the Near Surface Geoscience Conference (2008). He has supervised PhD students on fiber optic sensors and GPR optimization, advised projects on digital twins, and led EU-funded research on biogas enhancement in landfills.

Maurice van KeulenView profile

Associate Professor

• Artificial Intelligence
• Data Mining
• Process Mining
• +7 more

Maurice van Keulen is an Associate Professor affiliated with the University of Twente's research institutes including Datamanagement & Biometrics, Digital Society Institute, and TechMed Centre. His multidisciplinary work bridges computer science, healthcare, and social systems. Research Focus: Van Keulen specializes in artificial intelligence applications with emphasis on: Data management (quality, integration, probabilistic databases) Explainable AI and interpretable machine learning models Healthcare informatics (cancer prediction, medical imaging, outcome analysis) Natural language processing and social media analytics His recent work explores dynamic sparse training, meta-learning for data imputation, and ethical AI frameworks. Publication Trends: Recent articles (2023-2025) show strong focus on: Interpretable AI methods in healthcare diagnostics Robust machine learning under data corruption Meta-learning approaches for data preprocessing 3D medical imaging and reconstruction techniques Awards: Beste paper award (2018) for work on probabilistic data conditioning Supervision & Activities: Has supervised 14 research projects and serves on executive boards including EDBT (Extending DataBase Technology) and IFIP WG 2.6. Leads research on ethical dimensions of AI systems.

Jeremiah M. BlockiView profile

Associate Professor

• Cryptography
• Information Security
• Usable Privacy and Security
• +7 more

Jeremiah M. Blocki is an Associate Professor in the Department of Computer Science at Purdue University. His research focuses on cryptography, usable privacy and security, and authentication protocols. He joined Purdue in Fall 2016, previously completing his PhD at Carnegie Mellon University and a postdoc at Microsoft Research New England. Education: PhD in Computer Science, Carnegie Mellon University, 2014 Bachelor of Science in Computer Science, Carnegie Mellon University, 2009 Research Interests: Dr. Blocki’s work emphasizes applying theoretical computer science to practical security challenges, including password management, memory-hard functions, and differential privacy. His recent projects include developing distribution-aware password throttling and analyzing the post-quantum security of cryptographic algorithms. Publications: His research spans cryptographic protocols, security mechanisms, and privacy-preserving algorithms. Notable contributions include advancements in memory-hard functions (e.g., CRYPTO 2016, 2019) and differential privacy techniques (e.g., ITCS 2025). Recent work explores the intersection of cryptography with quantum computing and sublinear-time algorithms. Awards: NSF CAREER Award (2021) Purdue Seed for Success Award (2019) Allen Newell Award for Excellence in Undergraduate Research (2009) Advising & Grants: Supervised multiple PhD students and postdocs. Key grants include the NSF CAREER award ($591k) and a $10.7M HACCLE project (IARPA) for secure multi-party computation. Labs/Teams: Co-leads the HACCLE project, focusing on high-assurance cryptographic languages and environments. Active in Purdue’s CERIAS security initiatives.

Roberto FranzosiView profile

Professor

• Sociology
• Social Movements
• Content Analysis
• +6 more

Roberto Franzosi is a Professor of Sociology and Linguistics at Emory University's Department of Sociology within the Emory College of Arts and Sciences. He specializes in narrative analysis, content analysis, and historical sociology. His research focuses on social protest, political violence, and language measurement, with notable projects on Italian fascism and racial violence in Georgia. Franzosi has authored influential books such as From Words to Numbers and Quantitative Narrative Analysis , advancing methodologies for analyzing textual and narrative data. Education: PhD in Sociology, Johns Hopkins University, 1981 BA in Literature, University of Genoa, 1975 Research Interests: Franzosi's work bridges sociology and linguistics, emphasizing the application of quantitative methods to narrative data. His projects include analyzing labor strikes in Italy, the rise of fascism, and racial lynchings using newspaper archives. He advocates for integrating narrative analysis with computational tools to study historical and social phenomena. Publications: Franzosi's recent articles explore semantic grammars, frame analysis, and network analysis of narrative content. His work addresses methodological debates in mixed-methods research, emphasizing the synergy between qualitative and quantitative approaches. Teaching & Engagement: He teaches courses on data science, sociolinguistics, and historical sociology. His office is located at Tarbutton Hall 212, and he can be reached via email at rfranzo@emory.edu .

Kevin F. KellyView profile

Associate Professor

• Optics and Photonics
• Nanotechnology
• Imaging and Spectroscopy
• +7 more

Kevin F. Kelly is an Associate Professor in the Department of Electrical and Computer Engineering at Rice University. He was formerly the Chair of the Applied Physics Program and is affiliated with the Smalley-Curl Institute. Additionally, he has been a member of the Penn State Center for Nanoscale Science and the Mid-Infrared Technologies for Health and the Environment (MIRTHE) Center at Princeton University. Dr. Kelly co-founded Inview Technology Corporation as its Chief Scientist, focusing on commercializing compressive imaging technologies. He has also consulted for the Baker Institute for Public Policy regarding photovoltaics and taught courses in anthropology and history at Rice. Dr. Kelly holds a B.S. in Engineering Physics from the Colorado School of Mines (1993), followed by an M.S. (1996) and Ph.D. (1999) in Applied Physics from Rice University. His postdoctoral work included fellowships at the Institute for Materials Research in Sendai, Japan, and the Chemistry Department at Penn State University. His research interests span Optics and Photonics, Imaging and Spectroscopy at the nanoscale, and the role of mathematics in image acquisition. He develops Scanning Probe Microscopy techniques and studies Electronic Materials such as graphene and topological insulators. A major focus is Compressive Hyperspectral Imaging systems, including single-pixel camera innovations and advanced microscopy methods. He also pioneers molecular machines like the Nanocar and investigates charge transport in polymer photovoltaics. Over recent years, his work emphasizes interdisciplinary applications, such as integrating compressive sensing with neural networks for machine vision and exploring technological disaster analysis through history courses. His contributions have been recognized with awards like the IEEE Fellow (2022) and Technology Review’s Top 10 Emerging Technologies (2007). In addition to academic roles, Dr. Kelly has co-founded Inview Technology and contributed to grants and collaborations through his involvement in the MIRTHE Center and other institutes. While no formal advisees are listed, his teaching includes courses on nanotechnology since 2009 and he actively engages in policy consultations for photovoltaic commercialization. His lab at Rice and collaborations with the Smalley-Curl Institute drive advancements in nanotechnology and imaging, with a particular emphasis on practical applications of compressive sensing and molecular-scale devices.

Ngoc Cuong NguyenView profile

Researcher

• Computational Mechanics
• Molecular Mechanics
• Nanophotonics
• +7 more

Ngoc Cuong Nguyen is a Principal Research Scientist in the Department of Aeronautics and Astronautics at MIT and a member of the MIT Center for Computational Engineering. His research focuses on computational mechanics, numerical simulation, and advanced numerical methods such as hybridizable discontinuous Galerkin (HDG) methods for multi-scale and multi-physics problems. Education: PhD in High Performance Computation for Engineered Systems (2005), National University of Singapore BEng in Aeronautical Engineering (2001), Ho Chi Minh City University of Technology Research Interests: Computational Mechanics, Molecular Mechanics, Nanophotonics Numerical Simulation & Optimization, Scientific Computing, Machine Learning Reduced Basis Methods, High-Order Methods (e.g., HDG), Uncertainty Quantification Key Projects: Development of HDG methods for fluid dynamics, structural mechanics, and electromagnetics Plasmonic nanostructure simulations using quantum hydrodynamic models Space weather modeling via GPU-accelerated HDG approaches Optimization of photonic crystals and nanostructured materials Large-eddy simulation (LES) of hypersonic flows and buffet phenomena Labs & Teams: Active contributor to the MIT Center for Computational Engineering, leading projects in numerical methods, computational fluid dynamics, and interdisciplinary applications of advanced simulation techniques.

• Bioinformatics and Computational Biology
• Machine Learning
• Data Science
• +3 more

Fardina Alam is a Lecturer in the Department of Computer Science at the University of Maryland, College Park. She holds a Ph.D. from George Mason University (2023), where she specialized in Structural Bioinformatics and Machine Learning. Her academic rank reflects UMD's Professional Track Faculty, equivalent to an Assistant Professor of Teaching. Dr. Alam's research focuses on deep learning applications in protein structure prediction, generative AI, and ethical data practices. She has contributed to projects funded by an NSF FET Grant (#1900061) and published in journals like Biomolecules. Awards include the 2023 Outstanding Dissertation Award and 2022 Editor's Choice Article recognition. Education: Ph.D. (Computer Science, George Mason, 2023); M.S. (Computer Science, George Mason, 2019); B.S. (Computer Science and Engineering, Military Institute of Science and Technology, Bangladesh, 2013). Her teaching emphasizes data science ethics and interdisciplinary applications, including a new course for UMD's Data Science minor. Professional roles include Associate Guest Editor at Bioinformatics Advances (2024), Faculty Advisor to the Bangladeshi Graduate Student Association, and Program Co-Chair for the ACM-BCB Computational Structural Bioinformatics Workshop (2023). Research Interests: Structural Bioinformatics, Generative AI, Responsible AI Ethics, Deep Learning, Machine Learning, and Data Science. Her work bridges computational biology and AI, with a focus on equitable data practices and protein structure analysis. Recent projects address challenges in generating physically-realistic protein structures and improving question-answering systems through equitable data strategies. Awards: Recipient of the 2023 Outstanding Dissertation Award (George Mason University), 2023 Best Paper Award, and 2022 Biomolecules Editor's Choice Article. These accolades highlight contributions to protein structure prediction and bioinformatics methodology. Advising & Grants: NSF FET Grant #1900061 supported her computational biology research. She advises the Nobanno graduate student group and chairs workshops in her field. Her teaching and research aim to promote inclusivity, particularly for underrepresented groups in STEM. Labs/Teams: Active contributor to the Computational Biology Lab at George Mason University and collaborates with UMD's interdisciplinary teams on data ethics and AI applications. Her work aligns with UMD's vision for data-driven education and innovation.

Daniela AndreiView profile

Associate Professor

• Workforce Management
• Employee Wellbeing
• Occupational Safety
• +5 more

Daniela Andrei is an Associate Professor at Curtin University's School of Management and Marketing, affiliated with the Faculty of Business and Law. She coordinates large-scale applied research projects addressing workforce aging, safety, and employee wellbeing. Her work focuses on understanding forces shaping work experiences across the lifespan and their impacts on performance and safety. She is an Associate Investigator with CEPAR Stream 3 (Organisations and the Mature Workforce) and a member of Cost Action - LeverAGE. Research interests include aging workforce management, safety culture in high-risk industries (e.g., maritime), and HR practices for age diversity. Her studies often involve collaborations with industry and government bodies like Safe Work Australia and the International Mining for Development Centre. Her recent articles analyze interventions for aged care job demands, safety leadership behaviors, and maritime industry fatigue. Notable contributions include frameworks for 'Include, Individualize, Integrate' HR practices and meta-strategies for age-diverse workforces. She has advised on organizational metastrategies for managing younger and older workers, emphasizing inclusive design. Labs/Teams: Active in CEPAR's benchmarking surveys of the Australian workforce and the Age in the Workplace research network. Engaged in cross-disciplinary projects linking occupational health, leadership, and sustainable work design.

Olaf SchmidtView profile

Professor

• Soil Science
• Agricultural Sustainability
• Stable Isotope Analysis
• +7 more

Olaf Schmidt is a Professor at the School of Agriculture and Food Science, University College Dublin (UCD). His academic career includes roles such as Senior Lecturer/Associate Professor (2008–2017) and extends back to a Post-doctoral Research Assistant position (1999–2001). He holds a Ph.D. from UCD (2000), an M.Sc. in Soil Science from the University of Aberdeen (1993), and a Diplom-Agraringenieur from Martin-Luther-University Halle-Wittenberg (1992). Research Focus: Schmidt specializes in soil ecology, earthworm biology, stable isotope analysis, and sustainable agriculture. His work addresses topics like soil restoration, invasive species impacts, food authentication, and ecosystem rehabilitation. He leads projects such as Edaphobase 2.0 and the Gunnera tinctoria invasion studies. His research integrates molecular techniques, isotopic tracing, and large-scale data synthesis. Awards & Recognition: Fellow of the Royal Entomological Society (2023) Honorary Member of the Association of Applied Biologists (2022) Fellow of the Institute of Soil Science (2023) Teaching & Outreach: Coordinates modules on soil science, environmental microbiology, and the circular bioeconomy. Engages in public lectures on topics like earthworm contributions to soil health. Collaborates internationally, including a visiting professorship at the University of Agriculture in Kraków (2022). Grants & Impact: Contributed to the SmartGrass project, enhancing sustainable agricultural practices through multispecies swards. His work on peat alternatives and mine tailings rehabilitation has practical implications for environmental management and policy. Labs & Collaborations: Active in the Global Soil Biodiversity Initiative and Soil BON network. Edaphobase 2.0 exemplifies his data-driven approach to soil biodiversity research.

Yevgen BiletskiyView profile

Professor

• Knowledge-Based Systems
• Artificial Intelligence
• Semantic Web
• +3 more

Yevgen Biletskiy is a Professor in the Department of Electrical and Computer Engineering at the University of New Brunswick (UNB), Fredericton. His academic roles include serving as Co-Director of the RuleML Initiative and Program Co-Chair of RuleML-2007. He holds a Ph.D. and is a licensed Professional Engineer (P.Eng.) in New Brunswick. His teaching spans graduate and undergraduate courses in software engineering, digital systems, and power electronics, including EE 6263 (Knowledge Representation for Software Engineering) and EE 6213 (Advanced Digital Systems). Research Interests: His work focuses on Knowledge-Based Systems , Artificial Intelligence , Semantic Web , Information Extraction , FPGA-based Design , and Renewable Energy . He has supervised over 40 graduate and undergraduate students, including 3 active PhD candidates, 1 completed PhD, 9 Masters, and 30+ research-based Bachelors. Publications: Over 100 peer-reviewed articles, including recent contributions on smart grid optimization, fault diagnosis in power electronics, and ontology-driven systems. Notable works include frameworks for semantic interoperability, rule-based learning systems, and FPGA applications. Professional Activities: Served as a reviewer for NSERC grants, IEEE journals (e.g., TKDE, TE), and conferences (CDC, WTAS). He has chaired tracks at international conferences and contributed to industry partnerships through consulting roles with firms like Netsphare Solutions and Vox Interactif. Labs/Teams: Active in UNB’s research initiatives involving power systems, semantic web technologies, and e-learning systems. His lab collaborates on projects like SEMESIS (semantic search systems) and advanced manufacturing post-processing techniques.

Maria Christina MarianiView profile

Professor

• Applied Mathematics
• Nonlinear partial differential equations
• Stochastic differential equations
• +5 more

Maria Christina Mariani is a Professor and Department Chair in the Department of Mathematical Sciences at the University of Texas at El Paso (UTEP). Her interdisciplinary research bridges mathematics with applications in public health, geophysics, physics, and finance, with a focus on developing novel mathematical models for complex data analysis. Dr. Mariani earned her Ph.D. in Mathematics from the University of Buenos Aires in 1992, where she received an Outstanding dissertation award. She also holds an M.S. in Physics (1996) and an M.S. in Mathematics (1987), both from the University of Buenos Aires with highest honors. Her research interests span Applied Mathematics, Nonlinear partial differential equations, Stochastic differential equations, Machine Learning techniques, Mathematical Finance, Mathematical Physics, and Numerical Methods. She has developed mathematical models for medical data analysis (particularly breast cancer, heart disease, and prostate cancer), seismic and explosive data, and financial markets. Her work emphasizes the development of mathematical models to enhance understanding of medical data and extreme events in various phenomena. Dr. Mariani's recent research focuses on applying machine learning and stochastic models to complex data sets across multiple domains. Her work demonstrates consistent innovation in developing novel algorithms for medical diagnosis and prognosis, analyzing seismic data, and modeling financial markets using Levy processes, Ornstein-Uhlenbeck models, and wavelet techniques. She has mentored numerous students throughout her career, including PhD candidates, MS students, and post-doctoral researchers, demonstrating her commitment to academic development and knowledge transfer. Dr. Mariani has served as Department Chair and holds the Shigeko K. Chan Distinguished Professor title in Mathematical Sciences, reflecting her significant contributions to the field and institution.

Brandi MacDonaldView profile

Academic

• Archaeological Science
• Multi-method Analytical Approaches
• Pigment Analysis
• +4 more

Dr. Brandi MacDonald is an Assistant Research Professor in the Archaeometry Laboratory at the University of Missouri Research Reactor (MURR). She specializes in archaeological science, focusing on multi-method analytical approaches to study pigments, rock art, ceramics, obsidian, and glass. Her current research investigates rock art and mineral pigment use in the Pacific Northwest, lower Canadian Shield, and obsidian resource use in Northwestern Patagonia. She coordinates the MURR Archaeometry Laboratory's Pre-Doctoral Internship Program. Dr. MacDonald holds a Ph.D. from McMaster University (2015, Canada). Her research integrates geochemical, petrographic, and spectroscopic techniques to address questions about material procurement, technological choices, and human mobility in prehistoric and historic contexts. Key themes include pigment provenance studies, lithic raw material circulation, and cultural connections across diverse regions. Her research spans global case studies from Patagonia to the Yucatán Peninsula, involving projects like ochre mining in submerged caves (Mexico), obsidian sourcing in Argentina/Chile, and pigment analysis in African archaeological sites. She emphasizes collaborative, community-engaged approaches in fieldwork and lab-based analysis. Publications highlight methodological advancements in geochemical analysis, including neutron activation analysis (NAA), laser ablation-inductively coupled plasma mass spectrometry (LA-ICP-MS), and portable XRF applications. These techniques enable tracing material origins and reconstructing ancient production networks.

Kostas MagoutisView profile

Professor

• Distributed computer systems
• Scalable data stream processing
• Internet of Things
• +3 more

Kostas Magoutis is Professor and Chair of the Computer Science Department at the University of Crete and collaborating researcher with FORTH-ICS. His research focuses on distributed systems, scalable data processing, IoT, and cloud computing, with projects including GreenInCities for urban regeneration and STREAMSTORE for stateful stream processing systems. Research interests include: Distributed computer systems architecture Elastic stream processing platforms Quantum-enhanced computing applications Multi-cloud application lifecycle management Recent publications demonstrate strong focus on federated data systems, quantum computing applications, and IoT-enhanced infrastructure, with consistent output in high-impact conferences and journals. Awards and distinctions: Multiple best paper awards from USENIX conferences Grand Challenge Audience Award at DEBS 2022 Marie Curie Fellowship and IBM Research awards Advises over 20 PhD and MSc students in distributed systems research. Leads multiple EU-funded projects and serves on program committees for top conferences including SOSP, EuroSys, and IEEE BigData. Directs research groups in distributed systems and cloud computing at FORTH-ICS.