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Jeannette M. WingView profile

Professor

Columbia UniversityUnited States

Jeannette M. Wing is the Executive Vice President for Research and Professor of Computer Science at Columbia Engineering, Columbia University. She joined Columbia in 2017 as the inaugural Avanessians Director of the Data Science Institute. She is also an Adjunct Professor of Computer Science at Carnegie Mellon University, where she had been a faculty member since 1985 and served twice as Head of the Computer Science Department. S.B., S.M., Ph.D. in Computer Science — Massachusetts Institute of Technology (MIT) Honorary Doctorate of Technology — Linköping University, Sweden Her research is centered on trustworthy AI , encompassing security and privacy , formal methods , specification and verification , distributed systems , and software engineering . She is renowned for foundational contributions to linearizability and behavioral subtyping, and her 2006 essay on Computational Thinking revolutionized the perception of computer science as a universal problem-solving paradigm. Wing has served in numerous leadership roles across academia, government, and industry, including Corporate Vice President at Microsoft Research (2013–2017) and Assistant Director at the National Science Foundation (2007–2010). She is a member of the National Academy of Engineering, the American Academy of Arts and Sciences, and holds fellowships from ACM, IEEE, AAAS, and the National Academy of Innovators. Selected Honors and Fellowships: CRA Distinguished Service Award (2011) ACM Distinguished Service Award (2014) Fellow, American Academy of Arts and Sciences Fellow, Association for Computing Machinery (ACM) Fellow, IEEE Fellow, AAAS Member, National Academy of Engineering Honorary Doctorate, Linköping University She has advised numerous national and institutional initiatives as a board or steering committee member of organizations including the Computing Research Association, American Academy for Arts and Sciences, AAU Senior Research Officers, Chan-Zuckerberg New York Biohub, and Empire AI. She has served on the editorial boards of 12 journals, including the Journal of the ACM and Communications of the ACM . Wing leads Columbia’s research vision and continues to influence data science and trustworthy AI through policy, research, and thought leadership. She is affiliated with Columbia’s Foundations of Data Science and Cybersecurity centers.

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Zvonimir ŠafrankoView profile

Assistant Professor

University of ZagrebCroatia

Zvonimir Šafranko is an Assistant Professor at the Faculty of Economics and Business , University of Zagreb, specializing in Business Law . Since 2019, he has taught Commercial Law and Law of International Trade at both the Faculty of Economics in Zagreb and the Faculty of Organization and Informatics in Varaždin. He earned his PhD in Legal Sciences (2016) from the University of Zagreb with a thesis on Legal Aspects of Electronic Transferable Records in Commercial Transactions . Research Focus: Electronic commerce law, contract classification, EU corporate law, and digital finance. External Engagement: Member of the Organization and Program Committees for the International Conference on European Company Law & Corporate Governance ; editorial board member of InterEULawEast Journal . Recent Publications (2016–2024): Analyze EU law harmonization, electronic commercial records, smart contracts, and digital trade frameworks. His work bridges Croatian law with EU standards, emphasizing legal certainty in e-commerce and corporate sustainability. Awards & Grants: No specific scientific awards listed in the provided texts.

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Christian WeberView profile

Senior Lecturer

Zurich University of Applied Sciences (ZHAW)Switzerland

Christian Weber serves as a Senior Lecturer & Researcher at the Institute of Business Information Technology within the Zurich University of Applied Sciences (ZHAW) School of Management and Law. He directs the CAS Cyber Security program and contributes to the ZHAW Digital Health Lab, focusing on sustainable digital ecosystems and security frameworks. His educational background includes an Executive MBA in General and Entrepreneurial Management from Johannes Gutenberg-Universität Mainz/McCombs School of Business and a Dipl.-Ing in Industrial Electronics & Electrical Power Engineering from RheinMain University of Applied Sciences. His continuing education spans numerous certifications in AI, sustainability, and digital health from institutions including Hasso Plattner Institute. Weber's research centers on sustainable smart solutions for digital ecosystems, including digital health, ambient assisted living, and smart environments. His work explores computer-supported cooperative working scenarios, applications of open source systems in SMEs, and data protection, cybersecurity, compliance, and forensics as enablers for digital ecosystems. His teaching portfolio spans multiple modules in IT Security, Emerging Technologies, IoT-Data Streaming & Analytics, and Digital Transformation across BSc and MSc Business Informatics programs. His recent publications demonstrate strong interdisciplinary connections between cybersecurity, digital health, and organizational transformation, with particular emphasis on practical applications in real-world settings. His work bridges technical implementations with organizational and societal impacts of digital technologies. Best Paper Award at SMART 2018 for "Citizens as Sensors" research "Educate to lead" award from Soroptimist International Europe for STEM outreach Weber's professional experience combines academic leadership with industry expertise, having served as Managing Director of the Cisco Networking Academy since 2012 and holding previous positions as Administrative Professor and Lecturer at University of Applied Sciences Braunschweig/Wolfenbüttel. His industry background includes executive roles as CIO/CTO and IT management consulting. He contributes to the ZHAW Digital Health Lab and has led projects including the ZHAW Digital Culture Assessment and Digital Health Hackathon, focusing on practical implementations of digital health solutions and organizational transformation.

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Sarra DAHMANIView profile

Assistant Professor

SKEMA Business SchoolFrance

Sarra DAHMANI is an Assistant Professor in Project Management at SKEMA Business School since 2017. She is also a Part-Time Lecturer in Management Sciences at École Centrale de Lyon. Her research focuses on Agile Transformation , Organizational Maturity , and Risk Management in servitization processes. Doctorate (2015) - École des Mines de Saint-Étienne, France Master in Enterprise Administration (2011) - University of Strasbourg, France National Master in Management Sciences (2010) - Institute of Advanced Commercial Studies of Carthage, Tunisia Her work explores Agile Management in uncertain environments, Product-Service Systems (PSS) , and Resilient Project Scheduling . Publications highlight trends in Organizational Agility , Institutional Theory , and Digital Transformation . Notable certifications include PRINCE2 (2017), PMP (2017), and P3O (2016). She is affiliated with the SKEMA Center for Analytics and Management Science and has contributed to journals like Supply Chain Forum and Business Process Management Journal .

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Dharanidhar DangView profile

Assistant Professor

University of Texas at San AntonioUnited States

Dharanidhar Dang serves as Assistant Professor in the Department of Computer Engineering at the College of AI, Cyber and Computing, The University of Texas at San Antonio (UTSA), where he advances hardware-centric artificial intelligence solutions through photonic and memristor technologies. Education Ph.D., Texas A&M University His research program bridges hardware innovation and biomedical applications, with primary focus on photonic computing architectures for real-time AI acceleration and memristor-based neuromorphic systems. He investigates critical challenges in hardware reliability (particularly degradation in memristor crossbars), energy efficiency in photonic accelerators, and co-design methodologies that optimize both algorithms and physical implementations. His biomedical work applies machine learning to macrophage biology, identifying predictive signatures for inflammatory diseases through computational immunology approaches. Analysis of his 2020-2025 publications reveals three dominant research trajectories: 1) Silicon photonic accelerators (P-ReTI, P-ReTiNA, SOFTONIC) targeting real-time and energy-efficient AI, 2) Memristor reliability frameworks addressing aging effects in deep learning hardware, and 3) Translational biomedical applications where machine learning deciphers macrophage behavior in inflammatory bowel disease and preterm infant lung conditions. This tripartite focus demonstrates exceptional versatility across hardware engineering and life sciences.

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Zijin ZhangView profile

Assistant Professor

University of Michigan-Ann ArborUnited States

Zijin Zhang is an Assistant Professor of Business Analytics at the Carroll School of Management, Boston College. She holds a Ph.D. in Technology & Operations from the University of Michigan's Ross School of Business and a B.S. in Mathematics and Statistics from Nanjing University. Her office is located in Fulton Hall 454B at Boston College. Her research centers on data-driven decision-making in operations management, organized around three pillars: Engineering value : Designing algorithms for real-time decisions under uncertainty Economic value : Optimizing data acquisition costs versus decision impact Social value : Examining ethical implications of data practices and technology regulation Applications span retail operations, AI markets, and public-sector resource allocation. Recent publications focus on algorithmic decision-making in operations management, with recurring themes of data optimization, fairness in resource allocation, and policy impact analysis. Methodologies combine optimization, game theory, and machine learning. Awards & Honors: Rackham Doctoral Intern Fellowship (2024) Michigan Ross China Research Award (2023) First Prize, National Olympiad Informatics (2013) Thomas William Leabo Fellowship (2022-2023) DSI Doctoral Research Showcase Finalist (2025) Teaching includes Operations Management (TO 313) at University of Michigan with a 4.9/5.0 evaluation score. She has received multiple research grants including Rackham Research Grant (2024) and Ross School Doctoral Grant (2022). Engages in academic service as INFORMS conference session co-chair (2024) and PhD program panels. Maintains industry connections through past internships at Oracle and CITIC Group.

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Jukka SihvonenView profile

Assistant Professor

Aalto UniversityFinland

Jukka Sihvonen is an Assistant Professor at the Department of Accounting, Aalto University School of Business. His expertise spans financial accounting, digital transformation, and artificial intelligence in finance. He teaches and supervises master’s and doctoral programs in financial accounting, Big Data, and business technologies, and contributes to executive education. PhD in Finance (University of Vaasa, 2013) Visiting scholar at Norwegian School of Economics, Copenhagen Business School, Umeå University, Goethe University, European Central Bank, and Bank of Finland His research interests focus on digital transformation in accounting, AI applications, climate risk disclosures, cybersecurity, and servitization in business models. Recent publications address rare earth investments, LGBTQ+ policies, audit digitalization, and supply chain leadership. His 15 most recent articles highlight interdisciplinary trends in AI-driven finance, ESG compliance, and digital risk management. Key journals include European Accounting Review, International Review of Financial Analysis, and Industrial Marketing Management. Scientific Awards: Researcher of the Year (2021) Teacher of the Year (2022) AFAANZ Best Paper Award (2022) EFA Outstanding Paper Award (2011)

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Zahra MohagheghView profile

Professor

University of Illinois Urbana-ChampaignUnited States

Zahra Mohaghegh is a Professor and Donald Biggar Willett Faculty Scholar in the Department of Nuclear, Plasma, and Radiological Engineering at the University of Illinois Urbana-Champaign. She directs the Socio-Technical Risk Analysis (SoTeRiA) Research Laboratory , focusing on advancing risk science for complex systems like nuclear power plants, advanced reactors, civil aviation, and oil industries. Her work integrates probabilistic risk assessment (PRA), probabilistic physics of failure, human-system reliability, AI trustworthiness, uncertainty analysis, and risk-informed policymaking, supported by grants from DOE, NSF, NRC, and IAEA. Academic Positions: Professor (2025–present), Associate Professor (2020–2025), Assistant Professor (2013–2020), Part-Time Faculty at Beckman Institute (2015–present) Her research explores socio-technical systems through hybrid models combining technical systems with organizational factors, earning awards like the NSF Mid-Career Achievement Award and American Nuclear Society's Mary Jane Oestmann Professional Women's Achievement Award. She has contributed to U.S. National Academies committees on transport airplane risk assessment and Coast Guard compliance programs. Recent publications focus on spatiotemporal risk modeling, fire PRA advancements, human-digital twin interactions, and AI integration in nuclear safety. Her work emphasizes reducing false negatives in screening analysis, validating simulation models, and connecting safety with financial performance through probabilistic physics of failure. She actively collaborates with academia, industry, and regulators, including DOE's Carbon Free Power Project and OECD-NEA's NEST SMR initiative. Scientific Awards: National Science Foundation Mid-Career Achievement Award Dean's Award for Excellence in Research (Assistant and Associate levels) George Apostolakis Award in risk assessment American Nuclear Society Mary Jane Oestmann Professional Women's Achievement Award She serves on the Board of Directors for the International Association for Probabilistic Safety Assessment and Management (IAPSAM) and acts as a technical advisor to the U.S. National Academies on risk assessment methodologies.

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Mahdi FazeliView profile

Associate Professor

Halmstad UniversitySweden

Mahdi Fazeli is an Associate Professor at the School of Information Technology, Halmstad University, Sweden, specializing in hardware security and trust, energy-efficient computing, and embedded and cyber-physical systems. His academic journey began with a Ph.D. in Computer Engineering from Sharif University of Technology, Iran, in 2011. His career progression includes positions as Associate Professor at Bogazici University (2019-2021) and Iran University of Science and Technology (2016-2019), and Assistant Professor at the same institution (2011-2016). His research interests focus on hardware security and trust, reliable VLSI circuits and systems, energy-efficient computing, and dependable embedded systems. His work bridges the gap between theoretical security concepts and practical implementations in real-world systems, particularly in IoT and embedded environments. He has established himself as a leading researcher in Physical Unclonable Functions (PUFs), hardware trojans detection, and energy-efficient security solutions for resource-constrained devices. His publication record shows a clear progression and deepening expertise in hardware security, with recent work focusing on cutting-edge applications in edge computing, vehicular networks, and IoT security. His 2023-2025 publications demonstrate significant contributions to magnetic memory-based security primitives, anomaly detection systems, and energy-efficient security mechanisms. Throughout his career, Fazeli has led multiple research initiatives including the Dependable Systems and Architecture Lab (DSA) and the Networked and Embedded Systems Lab at Iran University of Science and Technology. His leadership extends to heading the Hardware Group and serving as Vice Chair for Educational Affairs, demonstrating his commitment to both research excellence and academic administration.

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David BrownView profile

Professor

Nottingham Trent UniversityUnited Kingdom

David Brown is a Professor in Interactive Systems for Social Inclusion at Nottingham Trent University's School of Science & Technology, Department of Computer Science. He serves as Director of the Computing and Informatics Research Centre (CIRC) and Research Group Leader for the Interactive Systems Research Group (ISRG). Director, Computing and Informatics Research Centre Research Group Leader, Interactive Systems Research Group Governor, Oak Field School for students with severe learning disabilities Conference Chair, International Conference on Disability, Virtual Reality and Associated Technology (ICDVRAT21) Associate Editor, Frontiers: Virtual Reality in Medicine Professor Brown's research focuses on developing inclusive technologies for people with disabilities. His work spans accessibility for students with learning, physical and sensory impairments; virtual reality applications for rehabilitation; multimodal affect recognition systems; social robotics for education; accessible visual programming toolkits; and serious games for developing physical and cognitive skills. His research is characterized by strong interdisciplinary collaboration and practical application in educational and healthcare settings. His recent publications demonstrate a consistent focus on applying emerging technologies like virtual reality, machine learning, and social robotics to address real-world challenges in accessibility and inclusion. The research shows a clear trajectory toward increasingly sophisticated multimodal systems that can detect user states and adapt accordingly, with applications ranging from autism support to mental health interventions. Extensive EU-funded research projects including Horizon 2020, Erasmus+, and EPSRC grants Notable projects: DIVERSIA, MaTHiSiS, Pathway, AI-TOP, EDUROB, No One Left Behind, Real Life, RISE Professor Brown has supervised numerous PhD students and collaborates extensively with international partners across Europe and Asia. His work bridges computer science, psychology, education, and healthcare to create technologies that promote social inclusion and improve quality of life for people with disabilities.

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Arnab NandiView profile

Professor

University of Michigan-Ann ArborUnited States

Arnab Nandi is a Professor in the Department of Computer Science & Engineering at The Ohio State University. His work bridges human interaction with data infrastructure, focusing on database systems, LLM-augmented analytics, and immersive query interfaces. Education: PhD in Computer Science & Engineering from the University of Michigan Leadership: Co-founder of OHI/O Hackathon Program and STEAM Factory interdisciplinary network Research spans human-in-the-loop data analytics , vibe querying (natural language + gestural interfaces), LLM integration into education, and climate response systems . Key projects include Omni (multimodal exploration), GestureDB , and Icarus (clinical pipelines). Recent publications analyze LLM-driven query stacks (HILDA 2025), video analytics (SIGMOD 2022), and data sunglasses for cognitive limits (HILDA 2025). Awards include NSF CAREER Google Faculty Research Award IEEE TCDE Early Career Award ACM Distinguished Member Advises students in database innovation , with alumni at Amazon, AWS, Roblox, and Meta. Teaches CSE 3241 (Database Systems), CSE 5889 (Software Startups), and CSE 5242 (Advanced Databases).

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Charith MendisView profile

Assistant Professor

University of Illinois Urbana-ChampaignUnited States

Charith Mendis is an Assistant Professor in the Siebel School of Computing and Data Science at the University of Illinois at Urbana-Champaign, with joint appointments in the Department of Computer Science, Electrical and Computer Engineering, and the Coordinated Science Lab. His research focuses on the intersection of compilers, program optimization, and machine learning systems. Dr. Mendis received his educational background from prestigious institutions: Ph.D. in Computer Science from Massachusetts Institute of Technology (2020) S.M. in Computer Science from Massachusetts Institute of Technology (2015) B.Sc. in Electronics and Telecommunication Engineering from University of Moratuwa (2013) His primary research interests center around compiler technology and machine learning systems. Mendis leads the ADAPT lab at UIUC, where his team works on creating high-performance ML optimization techniques and automated compiler construction using machine learning and formal methods. His work bridges the gap between traditional compiler design and modern machine learning approaches, with applications in tensor compilers, graph neural networks, and sparse computation. He has developed novel frameworks for optimizing deep learning workloads, verification of compiler transformations, and performance modeling for emerging hardware architectures. Mendis has established himself as a leading researcher in compiler optimization for machine learning systems, with a particular focus on tensor compilers, graph neural networks, and performance modeling. His recent publications demonstrate increasing sophistication in combining formal methods with machine learning techniques to solve challenging problems in compiler optimization and verification, with multiple papers accepted at top-tier conferences including OOPSLA, PLDI, POPL, and SIGMOD. His notable scientific achievements include: Google ML and Systems Junior Faculty Award (2025) DARPA Young Faculty Award (2024) NSF CAREER Award (2024) Distinguished Paper Award at POPL (2025) William A. Martin Thesis Award for Outstanding SM thesis, MIT (2015) Multiple teaching excellence awards at UIUC (2021-2023) Dr. Mendis actively mentors students through the ADAPT lab, offering research opportunities for undergraduates, master's students, and PhD candidates interested in compiler technology and machine learning systems. His research is supported by significant funding from the ACE center (part of JUMP 2.0), National Science Foundation (NSF), DARPA, IIDAI, and industry partners including Google, Intel, Amazon, and Qualcomm. He teaches advanced courses in compiler construction and machine learning for compilers. He leads the ADAPT lab at UIUC, which focuses on developing advanced compiler technologies for modern machine learning workloads. The lab maintains active collaborations with industry partners and has established itself as a leading research group in compiler optimization for AI systems. Current projects include tensor compilers, graph neural network optimization, and automated verification of deep learning systems.

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Luciano Cavalcante SiebertView profile

Assistant Professor

Delft University of TechnologyNetherlands

Luciano Cavalcante Siebert is an Assistant Professor at the Interactive Intelligence Group within the Intelligent Systems department of the EEMCS faculty at Delft University of Technology. His research focuses on Responsible Artificial Intelligence, developing hybrid methods that combine machine learning and symbolic approaches to ensure AI systems remain under meaningful human control within sociotechnical contexts. His educational background includes: B.Sc. in Mechatronics from Pontifical Catholic University of Paraná (PUCPR) M.Sc. and Ph.D. in Electrical Engineering from the Federal University of Paraná (UFPR), Brazil During his Ph.D., he was a guest researcher at Eindhoven University of Technology (TU/e), and prior to his current position, he served as a postdoc at TU Delft's AiTech initiative. Professor Siebert's research program is structured around four pillars: (1) eliciting and aligning with human values and norms, (2) incorporating ethical principles into AI, (3) enabling interactive human control and responsibility mechanisms, and (4) adapting to emergent societal norms. His interdisciplinary work bridges computer science, ethics, and social sciences, with applications in robotics, optimization, and automation. With over eight years of research experience, he develops practical frameworks for human-centered AI that prioritize societal benefit and accountability. Based at TU Delft's campus in Delft, Netherlands, Siebert actively contributes to the Interactive Intelligence Group's mission of advancing intelligent systems that empower humans and enhance societal well-being through responsible innovation.

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Giorgia RamponiView profile

Assistant Professor

ETH ZurichSwitzerland

Giorgia Ramponi is an Assistant Professor with Tenure Track at the Faculty of Business, Economics and Informatics at the University of Zurich. She is also an affiliated professor at the ETH AI Center and the Data Science and AI, Computer Science and Engineering department at Chalmers University of Technology. Her educational background includes a Ph.D. in Information Technology from Politecnico di Milano (completed June 2021 with honors), advised by Marcello Restelli, and a Master of Science in Computer Science with Honours Programme (110/110 cum laude) from la Sapienza (July 2017), advised by Flavio Chierichetti and Alessandro Panconesi. Dr. Ramponi's research focuses on machine learning and mathematical modeling, with particular emphasis on reinforcement learning and multiagent learning. Her work bridges theoretical foundations with practical applications, exploring how learning algorithms can make optimal decisions in complex environments. She has made significant contributions to areas including inverse reinforcement learning, multi-agent systems, constrained Markov decision processes, and human-AI interaction through preference learning. Her recent publications demonstrate a strong trend toward addressing fundamental challenges in reinforcement learning, particularly in multi-agent settings, constrained optimization, and learning from human feedback. Her work combines theoretical rigor with practical applications across robotics, economics, and decision-making systems. Hassler Research Grant for "Unified Feedback Integration Framework for Reinforcement Learning" Dr. Ramponi actively contributes to the academic community through conference participation, invited lectures (including at the Mediterranean Machine Learning Summer School), and teaching. She designed and taught the "Data Science and Machine Learning" course for the ETH-Ashesi Master program. She is also a member of the ELLIS community, which connects excellence in AI research across Europe. Her research group focuses on developing frameworks for reinforcement learning with various feedback types, including preferences, rewards, and demonstrations. The group aims to advance the theoretical understanding of learning algorithms while addressing practical challenges in real-world applications.

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Walter RobertsView profile

Assistant Professor

Yale UniversityUnited States

Walter Roberts is an Assistant Professor in the Psychiatry Department at Yale School of Medicine with a secondary appointment in Biomedical Informatics & Data Science. A licensed clinical psychologist specializing in substance use treatment, particularly alcohol and tobacco use disorders, he combines clinical expertise with technological innovation in his research program. Dr. Roberts received his PhD in Clinical Psychology from the University of Kentucky in 2016. His research program employs multiple methodologies to identify the causes and consequences of substance use in humans, with a focus on developing mobile biosensor platforms that can passively detect and predict substance use behaviors. These systems, built using machine learning and informatics techniques, aim to improve assessment and targeted delivery of interventions in clinical and research settings. He also investigates risk factors for hazardous alcohol use using clinical and epidemiological data and maintains an active interest in research ethics related to substance use research. Dr. Roberts' publication record reveals a strong focus on alcohol use disorders, with increasing integration of digital phenotyping and AI technologies in recent years. His work spans from traditional clinical studies to cutting-edge investigations using wearable technology and machine learning. The research shows a clear trajectory toward developing objective, real-time assessment methods for substance use behaviors, with particular attention to sex and gender differences in alcohol-related outcomes. Recent publications demonstrate growing interest in ethical considerations surrounding digital technologies in substance use research. MD2K Training Institute Summer Scholar (2023) Early Career Scientist Award from CHADD (2015) Enoch Gordis Award Finalist from Research Society on Alcoholism (2013) Dr. Roberts serves as a Sub Investigator on multiple clinical trials related to alcohol addiction and mental health, including studies examining the effects of acute stress and inflammation on drinking behavior, combining varenicline and guanfacine for smoking cessation, and investigating whether propranolol attenuates stress-induced drinking. His collaborative network includes frequent co-authors such as Sherry McKee, Terril Luce, MacKenzie Peltier, Yasmin Zakiniaeiz, and Bubu Banini. His research has been featured in YaleNews, highlighting work on using smartwatches to better understand psychiatric illness.

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