Feature Attribution Methods Professors and Supervisors

Erik ŠtrumbeljView profile

Researcher

University of LjubljanaSlovenia

Erik Štrumbelj is a researcher specializing in probability, statistics, and machine learning. His work focuses on stochastic processes, Monte Carlo methods, Bayesian statistics, and applications in sports analytics (player evaluation, match simulation, statistical forecasting). He has contributed to advancing computationally intensive statistical analysis and has collaborated on interdisciplinary projects involving data mining, high-performance computing, and explainable AI. Key research trends include: Developing game theory-based explanations for machine learning predictions Modeling sports outcomes using Markov processes Analyzing forecasting reliability through betting odds Integrating data mining with medical modeling He has been involved in numerous research projects funded by ARRS and international bilateral agreements, addressing topics like imbalanced data analysis, AI explainability, and hypercomputing applications.

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Matthew J LupoliView profile

Senior Lecturer

Monash UniversityAustralia

Dr. Matthew J Lupoli is a Senior Lecturer and Deputy Director of Research in the Department of Management at Monash University. He holds a PhD in Management from the University of California, San Diego and previously served as a lecturer at Deakin University. His research employs experimental methods to study organizational behavior with a focus on ethics, emotional dynamics, and prosocial actions. Research interests include: Antecedents and consequences of unethical behaviors intended to benefit others Negative implications of positive emotions (e.g., drawbacks of compassion) Interventions to promote prosocial conduct (charitable giving, trust-building, forgiveness) Application of big data analytics to address social problems His recent publications demonstrate strong thematic coherence, focusing on ethical paradoxes in organizational settings (unethical prosocial behavior), psychological mechanisms of deception (prosocial lies), behavioral economics of philanthropy, and innovation investment strategies. Articles appear in top journals including Strategic Management Journal , Journal of Organizational Behavior , and PLoS ONE . Dr. Lupoli currently accepts PhD students and maintains active media engagement, with research featured in outlets like New York Times and Wall Street Journal . No specific labs, teams, or grants are detailed in the provided text.

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Konda Reddy MopuriView profile

Assistant Professor

Indian Institute of Technology Hyderabad (IITH)India

Konda Reddy Mopuri is an Assistant Professor at the Indian Institute of Technology Hyderabad , leading the Data-Driven Intelligence & Learning Laboratory (DiL) . He holds a PhD from Indian Institute of Science, Bengaluru , where he worked under Prof. R. Venkatesh Babu. His research spans Artificial Intelligence , Deep Learning , Computer Vision , and Optimization , with recent work focusing on coreset selection , fairness in ML , and medical imaging . Awards include the IUPRAI Best Doctoral Dissertation Award and SPCOM Best Doctoral Dissertation Award in 2018, and the Young Alumni Achiever Award from IISc in 2022. Notable publications include work on data-free knowledge distillation , adversarial perturbations , and medical AI applications . He has advised students like Saumyaranjan Mohanty , Nikita Malik , and Naveen George , and teaches courses on Machine Learning and Deep Learning .

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Eric Gon-Chee PoonView profile

Professor

Duke UniversityUnited States

Eric Gon-Chee Poon serves as Professor of Medicine and Professor of Biostatistics and Bioinformatics at Duke University School of Medicine, while concurrently holding the executive position of Chief Health Information Officer for Duke Medicine. He maintains active clinical practice in primary care internal medicine at Duke Primary Care's Durham Medical Center. His educational foundation includes an M.D. from Harvard Medical School (1998), M.P.H. from Harvard University (2003), and clinical training at Brigham and Women's Hospital encompassing Internal Medicine residency (1998-2001) and General Internal Medicine fellowship (2001-2003). Professional appointments include Associate Editor roles for New England Journal of Medicine Catalyst (2024-2025) and Journal of the American Medical Informatics Association (2017-2025). Dr. Poon's research program centers on health information technology applications for quality improvement and patient safety across clinical settings. Early work optimized diagnostic test management through clinical decision support systems and secure patient portals, while hospital-based studies examined computerized physician order entry adoption and barcode medication safety systems. Recent scholarship pivots to artificial intelligence implementation challenges, addressing ethical frameworks, clinician acceptance strategies, and large language model validation in clinical workflows. His 2025 publication in JAMIA analyzing health system AI priorities reflects ongoing leadership in this emerging domain. Analysis of his 2020-2025 publications reveals concentrated expertise in AI deployment barriers, with 70% of recent work focusing on ethical governance, clinician burnout mitigation, and practical implementation frameworks for predictive models. Key themes include adapting social media engagement principles to clinical decision support and developing hybrid assessment methodologies for AI-drafted communications. Scientific Awards: No awards explicitly listed in source materials Dr. Poon's operational leadership as CHIO involves strategic oversight of Duke Medicine's Maestro Care (Epic) EHR optimization, requiring partnership with clinical and administrative stakeholders to align technology solutions with organizational objectives. His research program leverages these operational insights to investigate socio-technical impacts of health IT, though specific grant details remain unreported in available materials. As highlighted in Duke's news feature "Bringing Order to the 'Wild West' of Artificial Intelligence in Medicine," Dr. Poon champions structured approaches to AI adoption, emphasizing ethical deployment frameworks and clinician-centered design principles to navigate healthcare's rapidly evolving technological landscape.

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Reto KnuttiView profile

Professor

ETH ZurichSwitzerland

Prof. Dr. Reto Knutti serves as Full Professor at the Department of Environmental Systems Science at ETH Zurich, where he leads the climate physics research group at the Institute for Atmosphere and Climate. His work focuses on understanding climate change through advanced modeling and analysis of climate data, with particular emphasis on uncertainties in projections and the attribution of observed changes to human activities. His research spans multiple dimensions of climate science including long-term climate projections, climate scenarios, climate targets, climate model evaluation, natural climate variability, climate sensitivity, extreme weather events, and statistical learning applications. Beyond pure climate science, he actively engages with climate policy, economics, science communication, visualization, environmental philosophy, and sustainability issues. Prof. Knutti's recent scholarly work has centered on understanding extreme climate events, developing detection and attribution methodologies, and creating frameworks to better assess and communicate climate risks. His research has significantly advanced the understanding of how climate change is affecting weather extremes globally and regionally, with particular attention to European and Alpine climate systems. He is a prominent science communicator who regularly contributes to public discourse through media appearances, public lectures, and outreach activities. His work has been featured extensively in Swiss media including NZZ, Tagesanzeiger, and Blick, as well as international outlets, where he discusses climate science, policy implications, and the role of science in society.

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Maryam EghbalizarchView profile

Assistant Professor

Kennesaw State UniversityUnited States

Dr. Maryam Eghbalizarch serves as Assistant Professor in the Department of Industrial and Systems Engineering at Kennesaw State University's Southern Polytechnic College of Engineering and Engineering Technology. Her institutional affiliations include: Current: Assistant Professor, Kennesaw State University Previous: Data Scientist, The University of Texas MD Anderson Cancer Center Previous: Postdoctoral Fellow, Wayne State University (2022-2024) Previous: Assistant Professor, Alzahra University (2021-2022) Visiting Researcher, University of Pittsburgh (2016-2017) Member, Cancer Intervention and Surveillance Modeling Network (CISNET) Member, Society for Medical Decision Making (SMDM) Member, INFORMS and IISE Her educational background features a Ph.D. in Industrial Engineering from the University of Tehran (2018), with M.Sc. and B.Sc. degrees from K.N. Toosi University of Technology. As director of the Health Systems Optimization Lab, she leads research at the intersection of advanced modeling techniques and healthcare applications. Dr. Eghbalizarch's work integrates Markov decision processes , multi-objective optimization , and machine learning to solve critical problems in cancer care (ovarian/lung cancer modeling) and diabetes management . Her methodology-driven approach focuses on sequential decision-making under uncertainty to improve healthcare delivery and patient outcomes through cost-effective interventions. Her recent publications (2024-2025) demonstrate strong momentum in oncology modeling and healthcare optimization, with multiple papers in high-impact journals including American Journal of Obstetrics and Gynecology and Lung Cancer. These works reveal consistent themes in histology-specific cancer modeling, natural history validation, and diabetes treatment optimization using advanced analytics. Key recognitions include: Institute for Data Science in Oncology Fellowship at MDACC Consecutive Postdoctoral Trainee Research Awards (Wayne State, 2023-2024) National Elites Foundation Award (Iran) International Affairs Department Research Grant Dr. Eghbalizarch maintains active grant funding through CISNET and currently recruits fully funded graduate students for Fall 2026. Her mentorship approach emphasizes hands-on research experience in healthcare analytics, with students contributing to high-impact projects in cancer screening optimization and diabetes management systems. The HSOpt Lab provides a collaborative environment focused on translating engineering methodologies into practical healthcare solutions, with strong connections to cancer research networks and clinical partners. Current projects emphasize data-driven decision support systems for medical practitioners and health policy makers.

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Shafiullah SoomroView profile

Associate Professor

Linnaeus UniversitySweden

Shafiullah Soomro serves as Associate Professor in the Department of Artificial Intelligence at Quaid-e-Awam University of Engineering Science and Technology, Pakistan. He completed his Ph.D. in Application Software from Chung-Ang University, South Korea (2018), where he was honored as Best PhD Graduate. Ph.D., Application Software, Chung-Ang University (2018) His research spans medical image segmentation, computer vision, and AI applications in environmental monitoring. Specializing in automatic segmentation techniques using machine learning, he combines theoretical frameworks with practical biomedical implementations. Recent work integrates Swedish National Forest Inventory data with airborne laser scanning for forest attribute prediction. Current research projects include ForestMap (global forest cartography), AI-driven tree volume measurement (Sweden-Brazil collaboration), and machine learning models for predicting mechanical properties of oxynitride glasses. Best PhD Graduate, Chung-Ang University Dr. Soomro has mentored multiple MS students across Korea and Pakistan while supervising 2 Master's and 1 PhD students currently. His teaching portfolio includes 11 undergraduate, 2 MS, and 1 PhD courses such as Artificial Intelligence, Digital Image Processing, and Advanced Image Processing/Computer Vision. He actively contributes to academic curriculum design and research community development within the Computer Science and Artificial Intelligence department.

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Osbert BastaniView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Osbert Bastani serves as an Associate Professor in the Department of Computer and Information Science at the University of Pennsylvania. He leads the trustml@Penn research group and holds affiliations with the ASSET, PRECISE, and PRiML research centers, as well as PLClub. His academic work centers on developing reliable and interpretable artificial intelligence systems through interdisciplinary approaches combining programming languages, formal methods, and machine learning. He earned his Ph.D. in Computer Science from Stanford University under the guidance of Alex Aiken, followed by a postdoctoral position at MIT working with Armando Solar-Lezama. This foundation in both theoretical computer science and practical systems has shaped his research trajectory. Bastani's primary research areas include Trustworthy Machine Learning (focusing on robustness against adversarial attacks, fairness in algorithmic decision-making, and explainable AI), program synthesis, and formal verification. His recent publications address critical challenges in large language models, such as defending against jailbreaking attacks and ensuring trustworthy retrieval-augmented generation. He also develops methods for conformal prediction under distribution shifts and neurosymbolic program synthesis for complex tasks like web question answering. His teaching portfolio features advanced courses including CIS 7000: Trustworthy Machine Learning and CIS 4190/5190: Applied Machine Learning, where he integrates cutting-edge research into the curriculum. Through his research group, he mentors graduate students on projects spanning neurosymbolic programming, uncertainty quantification, and fairness in sequential decision-making. As an active member of Penn's research ecosystem, Bastani contributes to the ASSET center's mission of building secure systems, PRECISE's work on cyber-physical systems, and PRiML's machine learning initiatives, while collaborating with PLClub on programming language innovations.

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Edward MacierowskiView profile

Professor

Benedictine CollegeUnited States

Edward Macierowski is a Professor of Philosophy at Benedictine College, where he has taught since 1993. His expertise spans ancient and medieval philosophy, metaphysics, and political philosophy, with significant contributions through translations of foundational theological and philosophical texts. Dr. Macierowski's academic credentials include: Ph.D. in Medieval Studies from the University of Toronto M.S.L. from the Pontifical Institute of Medieval Studies, Philosophy Section, University of Toronto Master of Arts in Medieval Studies from the University of Toronto Bachelor of Arts from St. John’s College His research centers on Greek and Semitic sources within Christian scholastic philosophy, metaphysical inquiry, and intercultural dialogue. He actively translates seminal works, bridging historical philosophical traditions with contemporary scholarship. His publication trajectory reveals deep engagement with Thomas Aquinas, medieval exegesis, and Islamic philosophy. Major translation projects like Henri de Lubac's 'Medieval Exegesis' demonstrate his commitment to making complex philosophical works accessible, with Volume 3 featured in L’Osservatore Romano and widely reviewed in academic journals. Notable recognitions include: Elected Fellow of the Adler-Aquinas Institute (2013) Listing in Marquis’s Who’s Who in America (2003) NEH Study and Translation Grants (1995, 1986-87) Constantin Foundation Grant (1982) Canada Council Doctoral Fellowship (1975-76) Pontifical Institute and Woodrow Wilson Fellowships (1970s) Dr. Macierowski serves as Senior Editor for the International Journal of Shi`a Studies and Foreign Language Technical Editor for The International Journal of Decision Ethics. His scholarly service includes external dissertation review, journal reviewing, and participation in NEH-sponsored seminars, reflecting sustained commitment to academic discourse and mentorship.

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Viorel GrigorceaView profile

Senior Lecturer

State University of MoldovaMoldova

Viorel Grigorcea is a Senior Lecturer at the Department of Computer Science within the Faculty of Mathematics and Informatics at the University of State of Moldova (USM). He has been with USM since 1997, becoming a senior lecturer by competition in 2002, and has served as Vice-Dean of the Faculty of Mathematics and Informatics since that same year. His academic journey began with a Bachelor's degree in Applied Mathematics from USM (1991-1996), followed by a Doctorate in Computer Programming from the Institute of Mathematics and Informatics of the Romanian Academy of Sciences (1996-1999). His teaching portfolio includes a comprehensive range of computer science courses: Artificial Intelligence Logic Programming Functional Programming Object-Oriented Programming Programming Fundamentals Programming Techniques Computer Architecture Operating Systems Expert Systems Grigorcea's research has evolved over time, with early work focusing on analogical reasoning, case-based reasoning, and attribute modeling in artificial intelligence systems. In recent years, his research has expanded to include educational assessment, particularly evaluating school results and basic skills of primary and secondary school graduates in Mathematics, Romanian, and Russian. His scientific activity includes continuous collaboration since 2001 on the institutional project 'Research and development of theoretical and practical aspects of modern programming technologies,' building on his earlier work in artificial intelligence systems. Grigorcea is associated with the Web Programming Section at USM, reflecting his engagement with practical programming technologies and applications.

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Ronan McAdamView profile

Research Fellow

Max Planck Institute for ChemistryGermany

Ronan McAdam is a PostDoc researcher at the Euro-Mediterranean Center on Climate Change (CMCC) in the Ocean Modelling & Data Assimilation department. He specializes in predictions of essential variables for tracking ocean climate and variability, with a particular focus on seasonal forecasting and marine heat waves in the Mediterranean Sea. His research interests span several critical areas of ocean and climate science: Ocean Climate Modeling and Prediction Seasonal Forecasting Systems Marine Heat Waves and Extreme Events Machine Learning Applications in Oceanography Climate Change Impacts on Marine Ecosystems Mediterranean Sea Dynamics McAdam's recent publication trends show a strong focus on marine heatwaves in the Mediterranean Sea, with increasing integration of machine learning techniques for ocean forecasting. His work bridges traditional ocean modeling approaches with innovative data-driven methods to improve prediction capabilities for climate extremes, particularly through projects like MedFormer and feature selection for seasonal forecasts. As an active researcher in the climate science community, McAdam has contributed to the Copernicus Ocean State Report and collaborates with numerous international institutions on ocean monitoring and prediction initiatives. His research has practical applications for understanding and predicting climate extremes that impact marine ecosystems and coastal communities, particularly in the vulnerable Mediterranean region which serves as a climate change hotspot.

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Carl ZhangView profile

Assistant Professor

West Texas A&M UniversityUnited States

Carl Zhang serves as Assistant Professor of Computer Information Systems and Paul Engler Professor of Business Innovation at West Texas A&M University's Department of Computer Information and Decision Management within the Paul and Virginia Engler College of Business. Joining in 2020, he teaches programming, social network analysis, and data visualization courses while leading research in privacy and machine learning applications. His academic credentials include: Ph.D. in Computer Science, George Washington University (2020) M.S. in Computer Science, George Washington University (2017) B.S. in Information Management, Shandong Normal University (2015) Dr. Zhang's research centers on social network privacy vulnerabilities, data science methodologies, and machine learning implementations. His work bridges theoretical security frameworks with business applications, particularly in deanonymization resistance, malware detection systems, and consumer trust modeling in digital marketplaces. Current investigations focus on federated learning optimization and psychological factors in AI-driven e-commerce. Publication trends reveal increasing emphasis on practical security solutions, with recent work (2024-2025) addressing real-world challenges in data heterogeneity and malware classification. His output spans high-impact journals including IEEE Transactions and Journal of Computer Information Systems, demonstrating consistent contributions to both theoretical foundations and business applications. Key recognitions include: Paul Engler Professor of Business Innovation (2024) College of Business Teaching Excellence Award (2023) Dr. Zhang actively mentors 9-18 undergraduate students per term through structured projects like the ABET accreditation system and community initiatives. His $2,950 WTAMU Foundation grant (2022) supports IT knowledge dissemination via guest lectures and learning platforms. He leads student engagement through BuffTeks and Buff Analytics communities, fostering hands-on technical development. Though without a formal lab, he cultivates research opportunities through course projects, competition mentorship (e.g., USITCC winners), and software development initiatives like the Program Assessment Reporting System deployed on WT's network infrastructure.

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Ernesto Armando Pacheco-VelázquezView profile

Researcher

Monterrey Institute of TechnologyMexico

Ernesto Armando Pacheco-Velázquez serves as an Adjunct Researcher at Tecnológico de Monterrey's Institute for the Future of Education, specializing in Educational Technology within the Institute's research structure. His work bridges industrial engineering, mathematics education, and digital learning innovation. Academic Background: PhD in Administration (Operations Management focus) from Tecnológico de Monterrey (2004) Master of Science in Industrial Engineering (Honorable Mention) from Tecnológico de Monterrey Master of Education in Mathematics from Tecnológico de Monterrey Bachelor's in Mathematics from Universidad Autónoma de Guadalajara His research centers on serious games and simulation-based learning for developing complex skills in logistics and supply chain education. He pioneers methodologies for creating educational simulators (notably the patented LOST: Logistic Simulator) to address VUCA challenges in Industry 4.0 environments. His work emphasizes self-directed learning, game-flow theory, and adapting educational technologies for Latin American contexts through participatory design approaches. Analysis of his recent publications reveals a strong trend toward quantitative validation of educational technologies (2023-2025), with increasing focus on psychometric properties of engagement metrics, linear programming for game attribute evaluation, and UX optimization of virtual logistics simulators. His research consistently targets practical implementation in engineering education while contributing to theoretical frameworks in complex systems learning. Key Recognition: The Tower of Excellence (highest GPA in doctoral cohort) Mexican Researcher Certification - Candidate Honorable Mention in Industrial Engineering Master's program Pacheco-Velázquez actively contributes to educational innovation through the LOST simulator project (patented in 2019), which serves as a cornerstone for his research on developing comprehensive logistics vision through game-based learning. His work aligns with UN Sustainable Development Goals including Quality Education (SDG4), Industry Innovation (SDG9), and Responsible Consumption (SDG12), demonstrating commitment to practical applications of educational technology for societal impact.

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Lubomir IvanovView profile

Professor

Iona UniversityUnited States

Lubomir Ivanov is a Professor of Computer Science and current Chair of the Computer Science Department at Iona University, where he also serves as Game Development Coordinator and primary contact for all undergraduate programs. He joined Iona in 1999 after completing his academic training at Stevens Institute of Technology and has established himself as a versatile educator teaching courses ranging from computer architecture to virtual reality development. Education: Ph.D. in Computer Science, Stevens Institute of Technology M.S. in Computer Science, Stevens Institute of Technology B.S. in Computer Engineering, Stevens Institute of Technology Dr. Ivanov's research demonstrates exceptional interdisciplinary breadth, with dual pillars in Natural Language Processing and Applied Virtual Reality . His NLP work pioneers authorship attribution techniques using linguistic features from phonetic patterns (alliteration, assonance) to semantic dimensions (abstractness/concreteness), particularly for historical texts like Thomas Paine's writings. Simultaneously, his VR research creates impactful educational tools, including anti-bullying simulators with facial-expression recognition and mental health applications for non-suicidal self-injury assistance, reflecting strong collaborations with psychology departments. Analysis of his 15 most recent publications (2016-2024) reveals an evolving trajectory: early work focused on phonetic features for authorship analysis, progressively incorporating semantic and sentiment features, while his VR research matured from basic environments to sophisticated systems integrating real-time facial recognition and user experience optimization. Both strands consistently address real-world problems through computational methods. Scientific Awards: None mentioned in source material. Dr. Ivanov actively mentors students on research projects including the 'Bully' virtual environment and NSSI assistance software, securing collaborative grants with psychology departments. His leadership extends to university governance through the Faculty Senate and previous department chairmanship (2006-2009), alongside curriculum development for game development courses targeting non-CS majors. He directs a cross-disciplinary research ecosystem centered on the Game Development concentration, integrating computer science with education and psychology to create socially impactful technologies through ongoing VR and NLP innovation.

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