Aritra Dasgupta is an Assistant Professor in Data Science at the New Jersey Institute of Technology (NJIT). His work focuses on visual analytics, machine learning interpretability, and privacy-preserving visualization techniques. He holds a Ph.D. in Computer Science from the University of North Carolina at Charlotte (2012), an M.S. from the same institution (2008), and a B.Tech. in Information Technology from the West Bengal University of Technology (2005). Research interests include: Trustworthy AI and model explainability Climate and energy systems modeling Human-in-the-loop analytics Privacy-preserving data visualization Recent work emphasizes: Developing interactive tools for decision support Addressing adversarial attacks on machine learning systems Designing transparent algorithmic ranking systems His research bridges technical innovations with human factors, aiming to create usable and ethical data-driven systems. Collaborations span climate science, energy systems, and social computing domains.
Dr. Bogdan Adamyk is a Research Fellow at the Cyber Security Innovation Centre within the Operations & Information Management Department at Aston Business School, part of Aston University's College of Business and Social Sciences. He holds a PhD in Economics (Finance and Banking) from Kyiv National Economic University. His research focuses on cryptocurrency regulation, decentralized finance (DeFi), banking regulation, AI applications in finance, and cybersecurity. He leads the TRACE EU Horizon 2020 project (Grant No. 101022004) addressing illicit money flows detection. With 21 years of academic experience, he has authored over 125 publications including 7 textbooks and 4 monographs. Education: PhD in Economics (Finance and Banking), Kyiv National Economic University, Ukraine. Key research projects include TRACE (EU Horizon 2020) and studies on AI-driven risk management in DeFi. Research Interests: Dr. Adamyk's work spans blockchain technology, AI in financial systems, cybersecurity threats, and regulatory frameworks for digital assets. His recent studies explore anomaly detection in industrial systems, encryption techniques, and ethical AI adoption barriers in banking. Advising & Grants: Actively supervising PhD candidates and leading multi-million EU-funded projects. His work bridges academic research with practical applications in fintech regulation and cyber threat mitigation. Labs/Teams: Core member of Aston's Cyber Security Innovation Centre and collaborates internationally on projects like TRACE, focusing on AI-based solutions for financial crime prevention.
Luke Dosiek is a Professor in the Department of Electrical and Computer Engineering at Union College. He holds a Ph.D. from the University of Wyoming, with previous positions including Research Engineer at Assured Information Security and postdoctoral research at Wyoming. His research focuses on power system dynamics, signal processing applications in energy grids, and innovative educational methods for engineering. Key interests include synchrophasor-based detection of electromechanical modes and forced oscillations, low-cost measurement units, and auditory interfaces for grid monitoring. His teaching encompasses alternative energy, electromagnetics, circuits, and power systems. Research methodologies include time-series analysis, algorithm development, and experimental validation across diverse grid scenarios. Article analysis reveals consistent themes: advanced algorithms for oscillation detection, educational pedagogy in power engineering, and signal processing innovations. Temporal trends show increasing focus on real-time monitoring techniques and grid resilience. Awards include the 2021 Curtis W. McGraw Research Award. Professional experience spans industry research and academic roles across multiple institutions. Laboratory work includes developing synchrophasor applications and low-cost measurement tools. Future directions involve integrating machine learning for grid anomaly prediction and expanding educational outreach.
Mary Christ is an Associate Professor in the Department of Accounting at the University of Northern Iowa since 2007. She served as Department Head during the 2014-2016 academic years while maintaining her academic rank. Her work bridges accounting education and auditing research, with a focus on improving pedagogical methods and advancing audit decision-making frameworks. Her research interests include financial reporting transparency, auditing methodologies, team-based learning in business education, and cross-cultural assessment strategies. She has contributed to understanding how presentation formats influence auditor judgment and how collaborative classroom environments enhance student outcomes. Mary’s publications span topics from corporate governance practices to innovative teaching approaches. Her work on audit planning problem representations and team dynamics reflects a dual commitment to advancing both academic rigor and practical educational strategies.
Evangelos Spiliotis is an Assistant Professor at the National Technical University of Athens (NTUA) , affiliated with the School of Electrical and Computer Engineering and the Division of Industrial Electric Devices and Decision Systems . He serves as the Coordinator of the Forecasting & Strategy Unit at the Decision Support Systems Laboratory. Dr. Spiliotis earned both his Diploma–MSc (2013) and PhD (2017) from NTUA, specializing in Forecasting Systems. His research centers on forecasting methodologies , decision support systems , and energy optimization , with applied work in smart grids, retail, and sustainable infrastructure. Key interests include: Machine learning for time-series forecasting Energy management in buildings and microgrids Optimization of electric vehicle infrastructure Statistical and computational trade-offs in model design He has contributed to 80+ publications (cited 7,000+ times) and leads international forecasting competitions (M4, M5, M6). Editorial responsibilities include roles at the International Journal of Forecasting and Foresight: The International Journal of Applied Forecasting . Dr. Spiliotis teaches undergraduate courses: Decision Support Systems Forecasting Techniques Energy Management and Environmental Policy Management Game He has participated in multiple European/national R&D projects as a researcher and technical manager.
Dr. Tiago Mendes Ferreira is a Research Fellow at the Institute of Physics within the Faculty of Natural Sciences II at Martin Luther University Halle-Wittenberg. His research focuses on biophysics, molecular dynamics, lipid membranes, and solid-state NMR. He utilizes computational and experimental methods to study complex biological systems, contributing to advancements in medical imaging and material science. Research interests include: Molecular dynamics simulations of lipid membranes Solid-state NMR techniques for biomolecular analysis Computational modeling of membrane proteins Biophysical properties of cellular structures Advanced imaging for medical diagnostics His recent publications emphasize deep learning applications in ophthalmology and biomechanics, reflecting interdisciplinary collaborations. Article trends show strong focus on medical AI, universal design in web interfaces, and sports analytics.
Dr. Abey Kuruvilla is a Professor in the Department of Business at the University of Wisconsin-Parkside. He holds a Doctorate from the University of Louisville (2005) and has been teaching Operations Management since 2008. His research focuses on Ambulance Diversion in Emergency Medical Systems, Sustainable Tourism Management, and Cross-cultural Communication in Virtual Projects. He has published widely in journals like European Journal of Business Research and International Journal of Information Systems in the Service Sector. Dr. Kuruvilla has taught at multiple institutions including adjunct roles at Oakland University and Lawrence Tech University. He currently contributes to the UW's Sustainable Management program and holds visiting positions at Mikkeli University of Applied Sciences (Finland) and Italian universities. His consulting work with Aperian Global supports global companies like Kohler and Michelin on cross-cultural productivity issues. Research collaborations with students have led to over 150 community projects aiding local businesses. Awards include the 2013 Community Based Learning Award and 2011 Exceptional Teaching Award. He actively serves on institutional committees like the Chancellor's HR Task Force and chairs the International Initiatives Foundation Board. His service also includes roles in UW System Strategic Planning and the King County Healthcare Coalition's Scientific Advisory Board. Education: Ph.D., University of Louisville, 2005 Key Research Areas: Healthcare Systems Optimization, Sustainable Tourism, Intercultural Virtual Teams Consulting Clients: Kohler, Navistar, John Deere, Accenture, Michelin Service Roles: Chairperson of International Initiatives Foundation Board, UW System Global Planning Committee Member
Dr. William E. Spangler serves as the Department Chair of Accounting, Information Systems and Technology, and Supply Chain Management at Duquesne University's Palumbo-Donahue School of Business, where he is also a Professor of Information Systems and Technology. He holds a Ph.D. from the University of Pittsburgh, an M.B.A. from the University of Hawaii, and a B.A. from the University of South Florida. His teaching focuses on information systems auditing, control, and security, alongside international programs involving study abroad trips across multiple continents. Dr. Spangler's research interests span computational modeling for decision support in complex systems, machine learning, data mining, and the ethical implications of technology in healthcare, sustainability, and privacy. Notable areas include surgical scheduling optimization, RFID privacy, and cross-cultural adoption of online social networks. His work has been published in top journals like Management Science and IEEE Transactions on Knowledge and Data Engineering. He has received several accolades, including the Creative Teaching Award, Apple Polishing Award, and Kurt Rethwisch Outstanding Teaching Award. Beyond academia, his industry experience includes roles at Fortune 500 companies like Unisys and Westinghouse, as well as teaching at West Virginia University. Dr. Spangler actively explores the intersection of technology and societal impact, emphasizing sustainability, ethical data practices, and global collaboration. His current projects investigate the role of online social networks in charitable behavior and technology-driven corporate sustainability strategies.
Dr. John Friedlan is an Associate Professor of Accounting at Ontario Tech University’s Faculty of Business and Information Technology, where he also serves as Program Director, Commerce. With over 20 years of experience, he has taught at York University’s Schulich School of Business and holds a PhD from the University of Washington. His research focuses on critical analysis of financial reporting, managerial accounting, and the integration of business analytics into decision-making. Dr. Friedlan has been recognized for his teaching excellence, including the Educator of the Year Award (1992) and the Seymour Schulich Award for Teaching Excellence (2000). His educational background includes a Bachelor of Science from McGill University, an MBA from York University, and a PhD from the University of Washington. Prior to academia, he worked at Nabisco Brands and served on the Board of Examiners at the Canadian Institute of Chartered Accountants, qualifying as a Chartered Accountant in 1980. Dr. Friedlan’s research explores topics such as supply chain resilience, risk-averse decision-making, and disruption management. His work bridges theoretical frameworks with practical applications, leveraging computational methods in operations research and analytics. Recent articles address challenges in electric vehicle infrastructure planning, supply chain recovery strategies, and environmental disclosure practices. He actively contributes to practitioner journals like CGA Magazine and CA Magazine , emphasizing real-world relevance. His scientific contributions include over 15 peer-reviewed articles, with a focus on optimizing complex systems under uncertainty. Beyond research, Dr. Friedlan advocates for experiential learning, integrating industry partnerships to prepare students for data-driven business environments.
Amanda Coston is an Assistant Professor in the Department of Statistics at the University of California, Berkeley. Her research focuses on addressing challenges in algorithmic decision support systems and data-driven policy-making, emphasizing equity, validity, and reliability. She earned her PhD in Machine Learning and Public Policy from Carnegie Mellon University, advised by Alexandra Chouldechova and Edward H. Kennedy, and completed a postdoc at Microsoft Research's Machine Learning and Statistics Team. Her work spans causal inference, machine learning, and nonparametric statistics, with applications in criminal justice, healthcare, and public policy. Education: PhD in Machine Learning and Public Policy, Carnegie Mellon University (2019-2022) MS in Machine Learning, Carnegie Mellon University (2019) Bachelor of Science in Computer Science, Princeton University (2013) Research Interests: Her research investigates how algorithms and data systems can perpetuate or mitigate disparities in high-stakes domains. Key areas include counterfactual audits of racial bias in policing, fairness in predictive models, and validity in algorithmic decision-making. She develops methodologies to ensure equitable outcomes in applications like healthcare resource allocation and criminal justice risk assessments. Awards & Honors: 2024 Schmidt Sciences AI 2050 Early Career Fellowship 2023 FAccT Best Paper Award (Counterfactual Prediction Under Outcome Measurement Error) 2023 SaTML Best Paper Award (A Validity Perspective on Evaluating the Justified Use of Algorithms) 2022 Meta Research PhD Fellowship Teaching & Mentorship: She teaches Causal Inference (STAT 156/256) at Berkeley and has mentored students through programs like AI4ALL. Her teaching emphasizes ethics, fairness, and societal impacts of AI. Service: Referee for journals including Nature Human Behaviour, JASA, and Transactions on Machine Learning Research Steering Committee Member for ML4D Workshop (NeurIPS) Program Committee Member for FAccT and AAAI Labs & Collaborations: Amanda collaborates with interdisciplinary teams on projects involving policy design, algorithmic fairness, and healthcare equity. She co-organized the ML4D workshops at NeurIPS 2018-2019 and leads the FEAT reading group at CMU.
Professor Burkhard Schafer holds the Personal Chair of Computational Legal Theory at the School of Law, University of Edinburgh . He is also a Fellow of the Higher Education Academy (FHEA) and co-founder of the SCRIPT Centre for IT and IP Law , where he serves as Director. Additionally, he co-directs the Joseph Bell Centre for Legal Reasoning and Forensic Statistics . His research focuses on the intersection of law, computer science, and legal theory , particularly examining computational representations of legal thought, AI ethics, and the impact of technology on legal concepts like responsibility and liability. Notably, he contributes to the Ethics Framework for Legal Technology as chair of the AI4People working group and as a member of the Turing Institute's Data Ethics Group . Recent publications explore topics such as AI transparency , NFTs as digital property , and EU AI Act compliance . His work extends to projects like Creative Informatics and collaborations on autonomous vehicle liability and data ethics in creative industries . He also serves on the Law Society of Scotland's Legal Technologist Accreditation Panel .
Rebecca Eynon is a Professor of Education, the Internet, and Society at the University of Oxford, with a joint appointment between the Oxford Internet Institute (OII) and the Department of Education. Her research focuses on digital education, inequalities, and the intersection of technology with societal structures. She leads projects such as 'Towards Equity Focused Approaches to EdTech' and contributes to initiatives like the ARC Centre for the Digital Child. Her work explores EdTech's political economy, AI's role in education, and digital exclusion. She teaches on the MSc in Social Science of the Internet and supervises doctoral students in digital education and social justice. Funded by organizations like the British Academy and ESRC, her research emphasizes critical perspectives on technology’s societal impact. Recent projects analyze venture capital's influence on education and the ethics of AI in learning systems. Her research interests span the sociology of education, digital divides, computational social science, and the role of technology in everyday learning. She co-edited Learning, Media and Technology and serves on editorial boards for journals like Information and Learning Sciences . She advises policy bodies and non-profits globally, advocating for equitable tech integration in education. Current students include Liam Bekirsky (digital communities), Amanda Curtis (video games and creativity), and Anne Ploin (AI and cultural production). Past advisees have contributed to studies on healthcare IT, microwork in global gig economies, and digital detox practices. Her work highlights the need for critical frameworks to address technology-driven inequities in education systems worldwide.
Abrahim Ladha is a Lecturer at the Georgia Institute of Technology, affiliated with the School of Computing Instruction within the College of Computing. His work focuses on blockchain technology, cryptography, and secure computation, with notable contributions to private computation via MPC and Ethereum-based systems. He has also explored game theory through the lens of combinatorial mathematics in his earlier research. Research Interests: Blockchain and decentralized systems Cryptography and privacy-preserving technologies Multi-Party Computation (MPC) Ethereum smart contracts and autonomous bots Algorithmic game theory Publications highlight his exploration of auditable private computation, GABLE blockchain frameworks, and foundational game theory problems. No scientific awards or grants are explicitly listed in the provided information. Advising roles or student mentorship details are not available in the current data.
Dr. Agnieszka Lemanska is a Senior Lecturer in Health Data Science at the University of Surrey's School of Health Sciences within the Faculty of Health and Medical Sciences. She holds a joint appointment as a Senior Scientist at the National Physical Laboratory's Department of Data Science, where she contributes to improving healthcare data quality. Her research focuses on cancer-related studies using routinely collected healthcare data, with particular emphasis on early diagnosis and post-treatment outcomes. Dr. Lemanska earned her MSc in Pharmacy from the Medical University of Warsaw in 2005 and completed her PhD in Statistics and Machine Learning at the University of Bristol with GlaxoSmithKline funding. Her educational background bridges clinical pharmacy and advanced data science, creating a unique interdisciplinary perspective for her research. Her primary research interests center on routinely collected healthcare data, electronic healthcare records (EHRs), cancer-related primary care research, and data-driven early cancer diagnosis. She specializes in analyzing large databases of patient records including CPRD, ORCHID, and OpenSAFELY, with particular focus on pancreatic and prostate cancers. Her work addresses critical healthcare challenges including cancer diagnosis delays, treatment side effects, and healthcare system disruptions during the pandemic. Analysis of her recent publications reveals a strong focus on cancer epidemiology using large-scale electronic health records, with significant contributions to understanding pandemic impacts on cancer care. Her work demonstrates consistent methodological rigor across observational studies, systematic reviews, and clinical audits, with particular attention to real-world data applications in improving cancer diagnosis and treatment pathways. Dr. Lemanska actively contributes to multiple significant research projects including NPL Explorer's award for validating pancreatic cancer prediction algorithms, MRC Fellowship research on pandemic effects on cancer care, and EPSRC-funded PhD studentships investigating primary care data for early pancreatic cancer diagnosis. She has led important national audits on pancreatic enzyme prescribing and prostate cancer diagnosis disruptions during the pandemic. As an educator, she provides PhD, MSc, and BSc supervision while teaching across various healthcare programs including pharmacy, nursing, and physician associate curricula. Her international engagement includes serving as International Lead and Erasmus Coordinator for the School of Health Sciences, facilitating global academic collaborations and student exchanges.
Emily Black is Assistant Professor of Computer Science and Engineering at NYU Tandon and Data Science at NYU CDS. Her research develops methods for fairness and accountability in AI systems, focusing on high-stakes domains like government and law. Key research areas: Legal implications of model multiplicity and less discriminatory algorithms Pipeline-aware fairness across ML development lifecycle Consistent predictions and counterfactuals for reliable AI Algorithmic fairness in tax auditing and public policy Her interdisciplinary approach bridges computer science, law, and policy to prevent algorithmic harm. Current projects examine how model instability creates unfair outcomes and how pipeline interventions can mitigate bias while maintaining utility.
