Find Academic Supervisors

• Programming Languages
• Logic Programming
• Constraint Programming
• +4 more

Ulrich Neumerkel is an Assistant Professor in the Department of Compilers and Languages at Technische Universität Wien (TU Wien). He holds academic titles of Dipl.-Ing. (FH) and Dr.techn. His primary research focuses on programming languages, logic programming, and constraint programming, with significant contributions to Prolog optimization, garbage collection, and formal methods. He is also actively involved in educational initiatives, developing declarative programming tools and curricula. Neumerkel teaches courses such as Logic Programming and Constraints, Advanced Logic Programming, and Programming 2. He leads research in formal semantics of Prolog, constraint solver design, and memory management techniques. His work includes contributions to ISO/IEC Prolog standards and the development of tools like the Vienna Abstract Machine (VAM) and the GUPU environment for Prolog education. His research interests span compiler design, termination analysis, and program transformation. He has supervised students, including M. Seidl, on diploma theses related to virtual machine comparison and other topics. Neumerkel's affiliations include the Compilers and Languages group within TU Wien's Institute for Information Systems Engineering.

Rajibul IslamView profile

Associate Professor

• Quantum Computing
• Quantum Simulation
• Trapped Ion Physics
• +3 more

Rajibul Islam is an Associate Professor at the University of Waterloo, affiliated with the Institute for Quantum Computing (IQC) and the Department of Physics and Astronomy. His research focuses on quantum computing and quantum simulation using trapped ions, with contributions to quantum control, spin systems, and optical engineering. He leads the Quantum Information Technology and Ion Trapping (QITI) group. His work bridges theoretical models with experimental implementations in ion trap systems. Key areas of research include programmable spin simulations, qubit preservation, and quantum error correction. He has developed novel techniques for ion trap fabrication and optical addressing systems to enhance scalability. His experimental setups often involve hybrid optical cavities and advanced laser systems to achieve precise quantum control. Rajibul's recent work emphasizes scalable quantum architectures, leveraging machine learning for system optimization and holographic methods for high-precision control. His contributions span both foundational quantum physics and applied technologies for quantum information processing.

Christopher TermanView profile

Senior Lecturer

• Digital Communication
• VLSI Design
• DSP
• +3 more

Christopher Terman is a Senior Lecturer (Emeritus) at the Massachusetts Institute of Technology (MIT), affiliated with the School of Engineering and the Department of Electrical Engineering and Computer Science (EECS). He holds office in 32-G790 and can be reached at cjt@mit.edu. His research interests span digital communication systems, VLSI design methodologies, and educational technology innovations in engineering education. Terman has contributed extensively to the development of simulation tools for digital integrated circuits and has pioneered interactive learning environments for VLSI design education. His work integrates theoretical advancements with practical applications in both industry and academia. Over his career, Terman has authored influential papers on topics ranging from multiprocessor architectures to compiler optimization techniques, reflecting his interdisciplinary expertise in electrical engineering and computer science. His educational contributions include the design of MIT's 6.004 Computation Structures course, emphasizing scalable and learner-centered pedagogical strategies. Terman's publications demonstrate a sustained focus on bridging computational theory with real-world implementation challenges, particularly in the realms of digital signal processing and embedded systems. While no formal scientific awards are listed, his long-term academic leadership and contributions to foundational engineering education have had lasting impacts on both the field and MIT's curriculum. His work continues to inform modern approaches to integrating simulation, design automation, and collaborative learning in technical disciplines.

Marcin CopikView profile

Researcher

• Parallel Computing
• High-Performance Computing (HPC)
• Serverless Systems
• +3 more

Dr. Marcin Copik is a Researcher in the Professorship for Scalable Parallel Computing at ETH Zürich, focusing on advancing high-performance computing (HPC), serverless systems, and cloud computing. His work emphasizes optimizing resource utilization, improving scalability, and enhancing performance in distributed and parallel environments. His research interests span parallel computing architectures, serverless benchmarking (e.g., SeBS suite), and sustainable HPC practices. He explores techniques like automatic loop scheduling, acceleration-as-a-service models, and fault-tolerant distributed systems (e.g., FaaSKeeper). His contributions address challenges in cloud elasticity, stateful services, and energy-efficient computing. Recent publications highlight innovations in serverless workflows, AI reasoning frameworks, and hardware-accelerated protocols. His work bridges theoretical foundations with practical implementations, such as Cppless for high-performance serverless programming and XaaS for HPC-cloud integration. While no formal awards or grants are listed, his contributions to open-source projects like STEllAR-GROUP/hpx and Extrapeak demonstrate active engagement in the HPC community. He collaborates closely with academic and industry partners to advance scalable computing solutions.

Mark HorowitzView profile

Professor

• High-Performance Digital Systems
• VLSI Circuit Design
• Microprocessor Architecture
• +7 more

Mark Horowitz holds the Fortinet Founders Chair in Electrical Engineering and is the Yahoo! Founders Professor in Stanford University's School of Engineering. He also serves as Professor of Computer Science. His career spans over four decades, with foundational contributions to microprocessor design, high-speed link architectures, and computational photography innovations like the Lytro camera. Education: PhD in Electrical Engineering, Stanford University (1984) MS in Electrical Engineering, MIT (1978) BS in Electrical Engineering, MIT (1978) Research Interests: His work bridges EE and CS with interdisciplinary focus on: Agile hardware design methodologies for VLSI systems High-speed signaling and memory interfaces (e.g., Rambus technology) Reconfigurable computing architectures (e.g., CGRA-based accelerators) Applications in computational biology and molecular systems Recent Directions: Recent publications emphasize energy-efficient accelerators for machine learning, memory subsystem innovations, and compiler-driven hardware design frameworks like AHA! His work on Onyx and Opal architectures demonstrates leadership in sparse tensor computation hardware. Labs & Teams: Leads the Stanford VLSI Research Group and AHA! initiative. Collaborations include work with Prof. Marc Levoy on computational imaging and partnerships with industry on memory interface standards.

• Parallel Computing
• Distributed Systems
• High-Performance Computing (HPC)
• +5 more

Torsten Hoefler is a Professor affiliated with ETH Zurich, leading research in parallel computing, distributed systems, and high-performance computing (HPC). His work bridges theoretical foundations and practical implementations, focusing on optimizing algorithms, network topologies, and hardware-software co-design. Research Interests: His primary areas include parallel algorithms, distributed systems, machine learning infrastructure, and network architectures. He emphasizes scalable solutions for large-scale applications, particularly in data-centric computing and serverless environments. Publications: Recent work highlights include innovations in network topologies (e.g., HammingMesh), serverless benchmarking frameworks (SeBS), and optimizations for large language models (LLMs). His publications often address performance bottlenecks and energy efficiency in HPC and cloud systems. Awards & Grants: While no specific awards are listed here, his prolific publication record and leadership in HPC indicates significant recognition in the field. Active in grant-funded projects related to exascale computing and AI infrastructure. Labs & Teams: Leads the Communication Systems Lab at ETH Zurich, collaborating with industry partners like NVIDIA and IBM on hardware-accelerated computing and cloud-native systems.

Cheng TanView profile

Assistant Professor

• Computer Systems
• Machine Learning Verification
• Concurrent Systems
• +3 more

Cheng Tan is an Assistant Professor at the Khoury College of Computer Sciences, Northeastern University, and a member of the Systems Research Group. His research focuses on computer systems, with an emphasis on verifying outsourced services, including ML systems, concurrent systems, and execution on untrusted servers. Ph.D. in Computer Science from Courant Institute, NYU (2020), advised by Michael Walfish. M.S. and B.E. from Fudan University and Nanjing University, respectively. Cheng Tan's research explores verification mechanisms for systems relying on machine learning and untrusted environments. Key areas include ML system robustness , consistency models , and secure execution . His work addresses challenges in trusted computing, such as adversarial attacks, encrypted databases, and decentralized services. His recent publications span conferences like SOSP, ASPLOS, NeurIPS, and EuroSys. Common themes include neural network verification , secure systems , and concurrency control . These studies often leverage formal methods to ensure correctness in complex environments. Scientific Awards : MSR Asia StarTrack Scholar (2024), ASPLOS Distinguished Artifact Award (2023), NSF CAREER Award (2023), NYU Janet Fabri Prize (2021), SOSP Best Paper Award (2017). Cheng Tan advises PhD students Jian Zhang, Brent Zhao, Shuyi Lin, and Zikai Wang. He has taught courses such as LLM systems (CS7670), Operating Systems Implementation (CS6640), and Computer Systems (CS3650, CS5600). He also serves on program committees for conferences like OSDI, MLSys, and ATC.

Daniel GratzerView profile

Assistant Professor

• Theoretical Computer Science
• Programming Languages
• Type Theory
• +4 more

Daniel Gratzer is an Assistant Professor at the Department of Computer Science, Aarhus University. His research focuses on theoretical computer science, particularly in type theory, modal logic, and programming language semantics. He has contributed to foundational work in multimodal type theory, cubical type systems, and separation logic frameworks like Iris. His work often bridges categorical logic, homotopy type theory, and formal verification techniques. Gratzer's research interests include: Dependent and modal type theories Formal verification of concurrent systems Semantics of programming languages Proof assistants and logical frameworks His recent publications explore topics such as idempotent resources in separation logic, univalent reference types, and proof systems for multimodal logics. Gratzer collaborates on projects like the mitten proof assistant and has developed syntactic/semantic frameworks for categorical type theories. His work emphasizes foundational formalizations, with contributions to both theoretical results (e.g., normalization proofs, categorical semantics) and practical tools (e.g., Iris implementations).

Magnus MadsenView profile

Associate Professor

• Programming Languages
• Compilers
• Type Systems
• +4 more

Magnus Madsen is an Associate Professor at the Department of Computer Science, Aarhus University. He specializes in programming language design, compilers, and type and effect systems, and is the lead developer of the Flix programming language. His research focuses on advancing static analysis techniques and declarative language constructs for effectful and data-driven programming. Research Interests : - Programming language design - Type systems and effect systems - Static program analysis - Datalog and declarative programming - Compiler optimization and implementation Awards & Grants : - 2023: Sapere Aude Grant (Independent Research Fund Denmark) - 2022: Dahl-Nygaard (Junior) Prize (ECOOP) - 2022: STEM Grant (Stibo Foundation) - 2021: Amazon Research Award (collaboration with Jaco van de Pol) - 2020: DFF Project One (Independent Research Fund Denmark) Advising & Collaboration : - Supervises four current PhD students (listed above). - Active in academic service: PC member for ECOOP, OOPSLA, PLDI, and other conferences. - Collaborates with industry (e.g., Google, Systematic) and academia on tool development and language research. Labs & Projects : - Core contributor to the Flix programming language and the CASA (Center for Advanced Software Analysis) initiative. - Involved in interdisciplinary projects combining declarative programming with domain-specific applications.

Peter MilderView profile

Associate Professor

• Hardware Design
• FPGA Acceleration
• Signal Processing
• +7 more

Peter Milder is an Associate Professor in the Department of Electrical and Computer Engineering at Stony Brook University. His research focuses on hardware acceleration, FPGA-based systems, and domain-specific compilers for applications in machine learning, signal processing, and networking. He leads projects on automatic hardware generation tools like Argus for CNNs and FFT Gen for signal processing transforms. Education details are not explicitly provided in the text, but his work spans multiple interdisciplinary areas including formal verification (e.g., model checking on FPGAs), wireless edge computing (OPSEL protocol), and high-performance sorting algorithms. He has advised numerous PhD students and collaborates with researchers across academia and industry. Research Highlights: Developed voltage-scaling techniques for DNN accelerators. Created Waverunner, an FPGA-accelerated state machine replication system. Organized IEEE Transactions special issues and NSF-funded projects on edge computing and machine learning hardware. Awards: ACM TODAES Best Paper Award (2014). NSF grants for sparse transformer acceleration and FPGA-based spectrum sensing. Grants & Funding: NSF XPS Program (2015): Cloud FPGA deep learning. NSF ECCS (2020): Sparsity-aware NLP hardware. Lab/Collaborations: Collaborates with Professors Michael Ferdman, Fan Ye, and others on FPGA, edge computing, and embedded systems. His work often bridges hardware design with software frameworks.

Magnus MyreenView profile

Professor

• Program Verification
• Interactive Theorem Proving
• Formal Methods
• +8 more

Magnus Myreen is a Professor in the Department of Computer Science and Engineering at Chalmers University of Technology, where he leads research in program verification, interactive theorem proving, and verified software systems. He previously held a prestigious Royal Society University Research Fellowship at the University of Cambridge. Chalmers University of Technology — Professor (2023–present), Associate Professor (2015–2023) University of Cambridge — Royal Society Research Fellow (2012–2018) His research focuses on making formal verification practical and scalable, particularly through the CakeML project—a fully verified ML-style language with a bootstrapped compiler. He develops techniques in decompilation into logic, proof-producing synthesis, and verified runtimes for theorem provers like Milawa and HOL Light. His recent publications span top venues such as POPL, PLDI, ITP, and CAV, with a strong emphasis on verified compilation, compiler optimizations, and connecting verified components into larger systems (e.g., seL4 + CakeML). The work consistently targets real-world applicability and reduction of trusted computing bases. ACM SIGPLAN Most Influential POPL Paper Award (2014) BCS Distinguished Dissertation Competition Winner (2010) Amazon Research Award (2023) Royal Society University Research Fellowship Magnus has advised several PhD students including Oskar Abrahamsson, Alejandro Gomez, and Andreas Loow. His research has been funded by the Swedish Research Council and EPSRC. He is currently chair of the ITP steering committee and frequently serves on program committees for ITP, CPP, PLDI, and related conferences. He has led major collaborative efforts to connect verified systems, such as extending the seL4 microkernel verification down to machine code and proving the soundness of the Milawa theorem prover down to x86 machine code. He also works on verified synthesis of hardware and formal semantics of multiprocessor architectures.

• Circular Economy
• System Dynamics
• Rebound Effects
• +7 more

Daniel Guzzo is a Researcher at the Department of Civil and Mechanical Engineering, Technical University of Denmark (DTU), based at DTU Construct. He specializes in Design for Sustainability, with a focus on Circular Economy transitions, rebound effects, and System Dynamics modeling. His work contributes to UN Sustainable Development Goals related to sustainable consumption and production. PhD in Industrial Engineering, Technical University of Denmark, 2020 Doctoral research: 'A systems view on Circular Economy transitions: examining the deceleration of resource flows' Daniel Guzzo's research centers on understanding and mitigating unintended consequences in sustainability initiatives, particularly rebound effects—where efficiency gains lead to increased consumption. He employs System Dynamics to model complex interactions in product-service systems (PSS) and socio-technical systems. His work integrates design science, behavioral economics, and industrial ecology to support systemic sustainability transitions. He actively contributes to both qualitative and quantitative modeling approaches, emphasizing feedback structures and causal mechanisms. His recent publications (2023–2025) reveal a strong trend toward policy-relevant research, simulation-based modeling of rebound dynamics, and the development of practical tools for identifying and preventing rebound effects. These works span environmental management, policy briefs, and design science, often in collaboration with leading researchers like Daniela C. A. Pigosso and Timothy C. McAloone. The research consistently addresses circular economy implementation challenges in industrial and societal contexts. Scientific recognition includes: Reviewer's Favourite Award, May 2024 Daniel Guzzo is involved in advising PhD students and contributes to major research projects such as REBOUNDLESS (ERC Consolidator Grant) and PhD projects on simulation model configuration and circularity in industrial systems. He collaborates extensively with industry and international partners. He has also contributed to open science by publishing datasets on rebound mechanisms and behavioral design tools. He is a core member of the Design for Sustainability research group at DTU Construct, which focuses on systemic approaches to sustainable product and service design, ecodesign, and absolute sustainability. The group leverages interdisciplinary methods including systems thinking, behavioral modeling, and decision analysis to address complex sustainability challenges.

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

Lecturer Ben at Northeastern University's College of Engineering has taught diverse computer science courses from 2012 to 2025, including CS 7396: Seminar: Types, Inference, and Proof Search , CS 4470: Compilers , and CS 6110/5110: Software Verification . His work emphasizes programming language design, verification tools, and human factors in software systems. Research trends include: Language support for tabular data Curry-Howard isomorphism applications Compiler implementation techniques He has mentored students through courses like CS 3520/6520: Programming Languages and co-taught CS 4500: Software Development with Matthew Flatt. Ben's teaching philosophy incorporates hands-on projects, collaborative coding (e.g., pair programming), and cultural experiences like Zardoz screenings during his TA tenure at Cornell.

Utu IlieView profile

Associate Professor

• Power Systems Engineering
• Energy Transition
• Electrical Networks
• +4 more

Utu Ilie is an Associate Professor and currently serves as Dean of the Faculty of Mechanical and Electrical Engineering at the University of Petroşani. His academic role is centered within the Department of Automation, Computers, Electrical and Power Engineering. His research focuses on power systems engineering, energy transition strategies, grid resilience, and industrial energy efficiency. Key areas include optimizing power transmission, integrating renewable energy sources, and addressing occupational safety in critical infrastructure. Recent articles highlight work on power substation stability, smart grid technologies, and decarbonization. His publications emphasize practical solutions for energy security, grid modernization, and compliance with EU sustainability targets. Ilie has also contributed to educational materials on electrical machines and automation systems. His work underscores the importance of bridging theoretical research with industrial applications, particularly in Romania's energy sector. No specific awards or grants are explicitly mentioned in the provided texts, though his extensive publication record reflects active engagement in both academic and applied research.

Sam Tobin-HochstadtView profile

Assistant Professor

• Programming Languages
• Gradual Typing
• Functional Programming
• +5 more

Sam Tobin-Hochstadt is an Assistant Professor at the School of Informatics & Computing, Indiana University, with a focus on programming languages and systems. He is affiliated with the Department of Computer Science and actively contributes to the Racket and JavaScript language ecosystems. Research: Design and implementation of programming systems, particularly languages enabling software evolution (e.g., Racket, Typed Racket, JavaScript). Teaching: Courses like C211, P632, and honors sections of CS 2510. Collaborations: Mozilla Research, Sun Labs Programming Language Research Group. His research spans gradual typing , DSL implementation , compiler design , and parallel programming , with recent work on build systems and probabilistic programming. While specific scientific awards aren't listed, his contributions to PLDI, POPL, and other program committees highlight his field prominence. He mentors Ph.D. students at Indiana University and has organized academic events like IFL 2014. Personal interests include Ultimate and outdoor activities, alongside his wife Katie Edmonds' post-doc work in chemistry.