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Cornelius HempelView profile

Research Fellow

• Quantum Computing
• Trapped Ion Systems
• Quantum Simulation
• +4 more

Dr. Cornelius Hempel is a Research Fellow at the Paul Scherrer Institute (PSI) in Switzerland, leading the Ion Trap Quantum Computation group at the PSI Quantum Computing Hub since April 2021. He previously served as a Principal Investigator at the University of Sydney's Quantum Control Laboratory and was promoted to Senior Research Fellow in 2020. His academic training includes physics studies at Martin Luther University and the University of Michigan, followed by a PhD at the University of Innsbruck under Prof. Rainer Blatt and Dr. Christian Roos. Key Affiliations: Paul Scherrer Institute (PSI) – Group Head, Ion Trap Quantum Computing University of Sydney – Senior Research Fellow, Quantum Control Laboratory Institut for Quantum Optics and Quantum Information (IQOQI) – Postdoctoral Researcher Research Focus: Hempel specializes in quantum computing using trapped ion systems , with emphasis on analog quantum simulation, error correction, and laser-based quantum control. His work bridges quantum information science and chemical dynamics , enabling quantum simulations of molecular processes. Publications Trends: Recent articles highlight advancements in trapped ion quantum computing, including 3D laser fabrication of ion traps, geometric phase interference studies, and software tools for error suppression. His work combines quantum simulation , quantum control , and quantum chemistry to enhance quantum hardware capabilities. Laboratory Leadership: Hempel leads the Ion Trap Quantum Computation group at the PSI Quantum Computing Hub , focusing on scalable quantum systems and practical implementations of quantum algorithms.

• Computer Science
• Machine Learning
• Health Monitoring Systems
• +7 more

Muhammad Waqas is a researcher affiliated with COMSATS University Islamabad , where he holds a position in the Department of Meteorology under the School of Applied Sciences and Humanities . His academic collaborations span institutions like Bahria University, National University of Technology, and University of Bahrain, indicating a multidisciplinary approach. Research interests include Mechanisms for integrating fuzzy logic and machine learning in health monitoring Application of deep learning to medical imaging and clinical diagnostics Development of smart sensors for wearable technology in biomechanics Analysis of social media data for public health surveillance and sentiment analysis Investigation of digital citizenship and ICT leadership in educational contexts Trends in his 15 most recent publications (2025-2024) reveal a focus on medical diagnostics (e.g., monkeypox, breast cancer), smart infrastructure (e.g., sensor placement, structural health monitoring), and social media analytics for health and behavioral insights. These works leverage machine learning , fuzzy systems , and multi-objective optimization .

• Artificial Intelligence (AI)
• Unmanned Aerial Vehicles (UAVs)
• Fuzzy Logic Systems
• +7 more

Dr. Kelly Cohen is a Professor and Brian H. Rowe Endowed Chair in the Department of Aerospace Engineering and Engineering Mechanics at the University of Cincinnati's College of Engineering and Applied Science. His career spans over two decades, marked by significant contributions in AI, UAV systems, and aerospace engineering. He has led numerous research initiatives, secured grants from agencies like NSF, NIH, and NASA, and developed innovative solutions in autonomous robotics and medical AI applications. Dr. Cohen is also recognized for his teaching excellence and mentorship, having advised 12 PhD and 33 MS students. Education: Ph.D. in Aerospace Engineering, Technion, Israel Institute of Technology (1999) M.Sc. in Aerospace Engineering, Technion (1991) B.Sc. in Aeronautical Engineering, Technion (1986) Research Interests: Focus on AI-driven systems for aerospace and biomedical applications, including trustworthy AI, UAV control, optimization, and safety-critical systems. Current projects involve assured autonomy, medical phenotypic plasticity modeling, and advanced air mobility. Scientific Awards: Over 20 awards, including the UC Dolly Cohen Award, AIAA Technical Contribution Award, and Greater Cincinnati Consortium Excellence in Teaching Award. Grants and Advising: Principal Investigator on over 100 grants totaling millions, including projects on UAV traffic systems, AI safety, and medical AI. His labs include the AI Bio Lab and collaborations with NASA, FAA, and industry partners.

Baibhab ChatterjeeView profile

Assistant Professor

• Biomedical IoT
• Wireless Implants
• Low-Power Circuits
• +2 more

Baibhab Chatterjee is an Assistant Professor in Electrical and Computer Engineering at the University of Florida. His research focuses on developing energy-efficient integrated circuits and systems for biomedical IoT applications, neural implants, and secure body area networks. Research interests include ultra-low power circuits for biomedical sensors, novel wireless communication techniques through human tissues, brain-computer interfaces, and hardware security for implantable devices. His lab develops innovative solutions for next-generation healthcare monitoring and intervention systems. Recent publications demonstrate expertise in wireless power transfer for implants, in-memory computing architectures, and communication techniques optimized for the human body environment. The work consistently addresses challenges of miniaturization, power efficiency, and reliability in biomedical systems. Best 3-Minute Thesis Award, IEEE Microwave Week 2020 Best Paper Awards at IEEE CICC and HOST conferences Bilsland and Andrews Fellowships

Ahmedullah AzizView profile

Assistant Professor

• Mixed-Signal VLSI Circuits
• Non-Volatile Memory
• Beyond CMOS Device Design
• +4 more

Ahmedullah Aziz is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville, within the Tickle College of Engineering. He earned his Ph.D. in Electrical and Computer Engineering from Purdue University (2019), an M.S. from Pennsylvania State University (2016), and a B.S. from Bangladesh University of Engineering & Technology (2013). His research focuses on mixed-signal VLSI circuits, non-volatile memory, and beyond-CMOS device design, emphasizing emerging technologies like ferroelectrics and spintronics. He leads the NorDIC Lab and has published over 60 articles in journals, conferences, and patents. Education: PhD, Electrical & Computer Engineering, Purdue University, 2019 MS, Electrical Engineering, Pennsylvania State University, 2016 BS, Electrical & Electronic Engineering, BUET, 2013 Research Interests: Aziz explores device-circuit-system co-design techniques, particularly in cryogenic neuromorphic systems, superconducting memory, and ferroelectric-based circuits. His work bridges material innovation with practical applications, aiming to advance energy-efficient and high-performance computing. Awards: EDAA Outstanding Dissertation Award (2019/2020) Outstanding Graduate Student Research Award (Purdue, 2019) Samsung 'Icon' Award (2013) Best Publication Awards (SRC-DARPA STARnet, 2015/2016) Advising & Grants: While specific grants are not detailed, his research has been supported by prestigious institutions. He has advised/co-advised projects in emerging technologies but no listed students. His work extends to reviewing IEEE journals, conference TPC roles, and editorial contributions. Labs & Teams: He directs the NorDIC Lab, focusing on next-generation computing and device innovation.

Alexei VernitskiView profile

Senior Lecturer

• Artificial Intelligence
• Knot Theory
• Algebra
• +3 more

Dr. Alexei Vernitski is a Senior Lecturer in the School of Mathematics, Statistics and Actuarial Science (SMSAS) at the University of Essex. His research focuses on applying artificial intelligence (including reinforcement learning and deep learning) to mathematical problems in knot theory, algebra (e.g., braid theory), and universal algebra. He also explores mathematics education, particularly enhancing student motivation. Previously, he worked in the financial sector as a programmer and as a computer science lecturer. His research interests span AI-driven knot theory, algebraic structures (semigroups, groups), and mathematics education. Notable areas include the application of neural networks to braid untangling, automated reasoning in knot diagrams, and cognitive studies on math anxiety using EEG. He has supervised PhD students in mathematics education, universal algebra, and computer science applications of mathematics. His recent work demonstrates trends in combining machine learning with topological and algebraic problems, emphasizing practical AI solutions for abstract mathematical challenges. His articles reflect interdisciplinary approaches, merging computer science techniques with pure mathematics. Dr. Vernitski has advised multiple PhD students, contributing to diverse fields from knot theory to educational technology. His work bridges theoretical mathematics with real-world applications, such as optimizing data transmission and enhancing learning systems through neuroadaptive methods.

Tej ChajedView profile

Assistant Professor

• Formal Verification
• Systems Software
• Programming Languages
• +4 more

Tej Chajed is an Assistant Professor in the Department of Computer Sciences at the University of Wisconsin-Madison, focusing on formal verification of systems software. His research bridges theoretical foundations and practical implementations to ensure software correctness in concurrent and crash-safe systems. Research interests include formal verification, concurrency, crash safety, and programming languages, particularly using Coq, Perennial, and Goose frameworks. He has contributed to systems like DaisyNFS, a verified file system with sequential reasoning, and Verus, a foundation for systems verification. His work appears in top venues like SOSP, OSDI, and PLDI. 2025: Dafny PC Member 2024: PLDI Committee Member, CoqPL Co-chair 2023: CoqPL Co-chair, POPL Program Committee He actively mentors students and develops tools for systems verification education, including extensive Coq-based course materials.

• Bioinformatics
• Computational Biology
• Pharmaceutical Drug Discovery & Development
• +13 more

Leonard Wesley is an Associate Professor in the Department of Computer Science at the College Of Science, San Jose State University. His research spans interdisciplinary domains at the intersection of Bioinformatics , Computational Biology , and Machine Learning , with specific applications in Pharmaceutical Drug Discovery , Genomic Data Analysis , and Autonomous Robotics . Education: Ph.D. in Computer Science, University of Massachusetts M.S. in Computer Science, University of Massachusetts B.A. in Physics and Math, Northeastern University Research Interests include Approximate Reasoning (probabilistic, evidential, and fuzzy logic), Agent-Oriented Systems , and Sensor Fusion . His work applies these methodologies to Drug Portfolio Management , Protein Structure Scoring , and Medical Diagnostics . Publication Trends show a consistent focus on Computational Biology , Robotics , and Uncertainty Quantification over four decades. Early work in Computer Vision evolved into modern applications in Pharmaceutical Analytics and AI in Aerospace . Key Projects include SVM-based drug affinity prediction, evidence-driven decision support systems for biopharma, and real-time agent development frameworks like ROADS. He has contributed to CFD code control and Mobile Network Congestion solutions. Collaborations with institutions like NASA, Los Alamos National Laboratory, and international conferences (WMSCI, ICINCO, AIAA) highlight his cross-disciplinary impact. His teaching includes Artificial Intelligence and Bioinformatics courses.

• Artificial Intelligence
• Healthcare Technologies
• Assistive and Rehabilitation Technologies
• +5 more

Professor Dorothy Monekosso holds a PhD in Spacecraft Engineering from the University of Surrey and is currently a Professor of Computer Science at Durham University. She also serves as Chief Technical Officer (CTO) at More Life UK Ltd, a health-focused company contracted with NHS England. Her research focuses on applying AI and machine learning to healthcare technologies, including assistive and rehabilitation systems. Notable projects include the Virtual Physiotherapist for stroke recovery and the Digital Health Hub. Education: PhD (2000) in Spacecraft Engineering (University of Surrey), Master’s in Satellite Engineering, Bachelor in Electronic Engineering. Research Interests: Behavior Analytics, Digital Twin Computing, Anomaly detection, Medical Image Analysis, Smart Environments, and Wearables. Her work bridges robotics, AI, and healthcare to improve independent living and clinical decision support. Awards: Royal Academy of Engineering Foresight Award (2000), Honorary Fellowship of the British Computer Society (2020). Grants/Projects: Innovate UK-funded weight management programs, MRC-funded Virtual Physiotherapist studies, collaborations with NHS and Assisted Living Leeds. Labs/Teams: Leads development of assistive technologies through Durham’s Computer Science department and industry partnerships. Current supervision includes Strahinja Klem.

• Artificial Intelligence and Law
• Computational Argumentation
• Legal Reasoning
• +5 more

Professor Henry Prakken is a leading researcher in Artificial Intelligence and Law at Utrecht University's Department of Computer Science. He holds a prominent position in the Responsible AI research group and has been instrumental in advancing computational models of legal argumentation. With an extensive publication record spanning over three decades, Prakken has established himself as a central figure in the intersection of law and artificial intelligence. Prakken's research interests focus on computational models of argumentation, legal reasoning systems, and the application of AI to legal domains. His work bridges theoretical foundations with practical applications, particularly in case-based reasoning, Bayesian networks for legal evidence, and formal argumentation frameworks. He has made significant contributions to understanding how computational models can represent and analyze legal reasoning processes, with particular attention to precedent-based reasoning and argument strength. His publication record demonstrates consistent research productivity with numerous high-impact papers in venues like Artificial Intelligence, Artificial Intelligence and Law, and proceedings of major conferences including ICAIL and COMMA. Recent work has expanded into evaluating generative AI's legal reasoning capabilities and developing more sophisticated models of argument strength and acceptability. Past president of the International Association for AI & Law (IAAIL) Past president of the JURIX Foundation for Legal Knowledge-Based Systems Past president of the steering committee of the COMMA conferences on Computational Models of Argument Editorial board member of Artificial Intelligence and Law Associate editor of Artificial Intelligence (2017-2022) Prakken has played a significant role in mentoring and shaping the field through his leadership positions and editorial work. His research has influenced both theoretical developments in computational argumentation and practical applications in legal technology, contributing to the growing field of responsible AI in legal contexts.

Po-Shen HsinView profile

Lecturer

• Theoretical Physics
• Quantum Field Theory
• Strongly Interacting Systems
• +3 more

Po-Shen Hsin is a Lecturer in the Department of Mathematics at King’s College London. He holds a BSc in Physics from National Taiwan University (2012), an MA in Physics from Princeton University (2016), and a PhD in Physics from Princeton University (2018). His research focuses on theoretical physics, particularly quantum field theory, strongly interacting systems, topological phases of matter, and the interplay of symmetries and anomalies. He explores topics such as non-invertible symmetries, higher-form anomalies, and their implications for topological phases and condensed matter systems. His work spans theoretical frameworks like gauge theories, topological defects, and quantum error correction codes, with applications to understanding exotic phenomena in materials and high-energy physics. Notable themes include symmetry-enriched topological phases, anomaly detection, and the classification of logical gates in quantum codes via cohomology operations. His research group at King’s College is part of the broader efforts in supersymmetry, string theory, and related areas within the Faculty of Natural, Mathematical & Engineering Sciences. His contributions bridge fundamental theoretical insights with potential applications in quantum technologies and condensed matter systems.

David MillerView profile

Professor

• Philosophy of Science
• Critical Rationalism
• Epistemology
• +3 more

David Miller is a prominent philosopher known for his work in the philosophy of science, critical rationalism, and epistemology. He was an assistant to Karl Popper and collaborated with him extensively. Miller taught at the University of Warwick and held academic positions globally. His research focuses on logical foundations, probability theory, and the critique of inductive reasoning. He authored influential books like Critical Rationalism: A Restatement & Defence (1994) and Out of Error (2006). Miller's work challenges traditional justificationist approaches and advocates for critical rationalism as a framework for scientific and philosophical inquiry. His publications span journals such as Philosophical Transactions of the Royal Society and Philosophia Scientiæ . He has also engaged in editorial roles, including co-editing Karl Popper: A Centenary Assessment (2006). Miller’s contributions address topics like falsificationism, propensities in probability, and deductivist decision-making. His recent work includes critiques of postmodernism and defenses of Popper’s legacy. He remains active in international academic discussions, contributing to conferences and symposia on critical rationalism.

Matt AmyView profile

Assistant Professor

• Quantum Computing
• Programming Languages
• Compilers
• +3 more

Dr. Matt Amy is an Assistant Professor in the School of Computing Science at Simon Fraser University (SFU), holding the Canada Research Chair in Quantum Computing. His research focuses on quantum compilers, programming languages, and formal verification of quantum programs. He also explores quantum circuit optimization and models of quantum computation. Education: PhD in Computer Science (University of Waterloo, 2019), M.Math in Quantum Information (2013), and B.Math in Computer Science (2011), all from the University of Waterloo. Research Interests: Quantum compilers and languages, circuit optimization, formal verification, and quantum computation models. His work bridges theoretical foundations with practical implementations, emphasizing efficient quantum software development. Recent research trends include advancing quantum compilation techniques, exploring NP-hard optimization problems in quantum circuits, and developing formal methods for quantum program analysis. His work on symbolic synthesis and equational theories for quantum circuits demonstrates a focus on foundational algorithmic challenges. Scientific Awards: Canada Research Chair (2025–present) Advising and Grants: While no current advisees are listed, his research is supported by grants focused on quantum computing and formal methods. He collaborates with industry through SFU’s School of Computing Science. Labs and Teams: Involved with the Tangent Lab, a research group exploring quantum algorithms and software systems at SFU.

• Databases
• Data Management
• Provenance Analysis
• +6 more

Val Tannen is a Professor at the University of Pennsylvania, specializing in database systems, provenance analysis, and programming languages. His research focuses on data management, query languages, and systems like DBSP and ORCHESTRA. Collaborations include work with co-authors such as Zachary Ives, Susan Davidson, and Todd Green. Key research interests include provenance for databases, incremental view maintenance, and data integration. His work bridges theoretical foundations and practical applications in systems like DBSP for stream processing and ORCHESTRA for collaborative data sharing. Publications span provenance frameworks, query optimization, and distributed systems. While no awards are explicitly listed, his contributions to database theory and systems are widely recognized.

Richard MolyetView profile

Senior Lecturer

• Automatic Control
• Robotics
• Sensor Development
• +7 more

Dr. Richard Molyet is a Senior Lecturer and Undergraduate Director in the Department of Electrical Engineering and Computer Science at the University of Toledo's College of Engineering. After retiring as Associate Professor in 2002, he returned to academia in 2005 as Visiting Professor and transitioned to Associate Lecturer in 2008. Education: Ph.D. in Engineering Science (1981) from University of Toledo His research spans Automatic Control , Robotics , Smart-Grid Systems , and Biomedical Applications . Recent publications focus on deep learning for medical diagnostics and hybrid power network optimization , while earlier work explored repetitive control algorithms and microprocessor-based motion analysis . Scientific Recognition: IEEE Third Millennium Medal (2000) IEEE-USA Professional Achievement Award (2002) University of Toledo Outstanding Teacher Award (2016) Currently advising 3 PhD students and multiple Master’s candidates, Dr. Molyet has served on numerous academic committees since the 1980s. He maintains an active role in IEEE Toledo Section's executive board for 39 years .