Find Academic Supervisors

• Building Performance Analysis
• Energy Efficiency in Buildings
• Climate Resilience of Building Stock
• +3 more

Daniel Godoy Shimizu serves as a Lecturer in Building Performance Analysis at the UCL Energy Institute within The Bartlett Faculty of the Built Environment, University College London. His academic appointment focuses on building physics modeling and energy performance analysis, with active research contributions through 2024 publications. His research centers on energy use in the built environment, specializing in building stock modeling, climate resilience, and net zero transitions. Key focus areas include: School building overheating and climate adaptation London building stock energy modeling (M25 region) Residential retrofit pathways for social housing Integration of renewable energy in educational facilities Spatiotemporal analysis of building energy consumption His publication portfolio demonstrates consistent output in high-impact journals including Building and Cities, Energy and Buildings, and Building Services Engineering Research and Technology. Recent work shows increasing emphasis on climate risk assessment for educational infrastructure, with significant contributions to understanding school building overheating and developing net zero pathways for English school stocks. His research methodology combines empirical data analysis with advanced stock modeling techniques. Daniel previously worked as an Associate at Cambridge Architectural Research (CAR) Ltd, contributing to the Household Electricity Survey analysis and Housing Energy Factfile development. His industry experience as a building services engineer provides practical grounding for his academic work, particularly in sizing building services and conducting environmental analyses for international projects. Current research initiatives include membership in the London Buildings Stock Model team, developing detailed disaggregate models of every M25 building, and investigating high-rise building energy implications. His work aligns with UN Sustainable Development Goals 7 (Affordable and Clean Energy), 12 (Responsible Consumption), and 13 (Climate Action).

Muaaz Gul AwanView profile

Researcher

• High Performance Computing
• Bioinformatics
• GPU Computing
• +7 more

Muaaz Gul Awan is a Computer Systems Engineer 4 at the National Energy Research Scientific Computing Center (NERSC) under the Science Engagement & Workflows Dept. His work focuses on high-performance computing (HPC) with specialization in bioinformatics software development, GPU porting, and performance optimization for large-scale scientific applications.

Mario BaldiView profile

Associate Professor

• Programmable data planes
• Software-defined networking
• Network security
• +5 more

Mario Baldi is an Associate Professor (on leave) of Information Processing Systems at the Department of Control and Computer Engineering , Politecnico di Torino , and concurrently a Fellow in the Office of the CTO, Adaptive and Embedded Computing Group, at AMD, San Jose, CA. His career blends deep academic research with extensive industry R&D leadership. Education M.Sc. (Summa Cum Laude) in Electrical Engineering, Politecnico di Torino, 1993 Ph.D. in Computer and System Engineering, Politecnico di Torino, 1998 Research Focus Baldi’s research spans programmable data planes, software-defined networking, big-data analytics for network management, network security, high-performance switching architectures, optical networking, QoS mechanisms, and multimedia/voice-over-IP systems . He is especially known for pioneering work on P4 -based programmable networks and SmartNIC architectures. Publication & Patent Impact Across 150+ refereed papers and 35+ US patents (plus European filings), his recent output concentrates on machine-learning-driven network data-plane functions , disaggregated stateful network services , and cloud-grade DPUs . The 2021–2024 articles emphasize real-time inference directly in the network data plane and modular SDN programming. Awards & Honors Best Paper Award, IEEE ICC 2007 Best Paper Award, IEEE ISCC 2008 Best Paper Award, IEEE GreenComm 2009 Best Paper Award, ACM/IEEE WI/IAT 2014 Grants & Projects Baldi has served as Principal Investigator or Scientific Coordinator on numerous EU Framework and Italian national projects (PRIN, FAR), leading consortia on energy-efficient packet networks, trusted software execution, wireless mesh architectures, and streaming media delivery. Teaching & Mentoring He has taught graduate courses on Enterprise Network Technologies, Computer Network Technologies and Services, Networks/Cloud/Application Security at Politecnico di Torino since 2003. He has also supervised PhD collegi for the Computer and Systems Engineering doctoral program (cycles 19–23) and held visiting/adjunct positions across four continents. Labs & Teams Previously headed the NetGroup (Computer Networks Group) at Politecnico di Torino (2001–2007) and co-chairs the p4.org Architecture Workgroup , driving open standards for programmable networking.

Ashraf AboulnagaView profile

Professor

• Database Systems
• Cloud Computing
• Big Data
• +3 more

Ashraf Aboulnaga is a Professor in the Department of Computer Science and Engineering at the University of Texas at Arlington (UTA). He holds a Ph.D. in Computer Science from the University of Wisconsin-Madison and has held prior roles as Chief Scientist at the Qatar Computing Research Institute, Associate Professor at the University of Waterloo, and Research Staff Member at IBM Almaden Research Center. His research focuses on database systems, cloud computing, and graph analytics, with recent emphasis on cloud-native database architectures and scalable graph processing. Education: Ph.D. (2002), M.S. (1999) from University of Wisconsin-Madison; B.S./M.S. (1993/1996) from Alexandria University. Affiliations: ACM Distinguished Scientist (2015), IEEE Senior Member (2009). Research interests include cloud database systems, distributed transaction processing, and knowledge graph integration. He has authored over 100 publications in top venues like SIGMOD, VLDB, and ICDE, and received Best Paper Awards at SoCC 2015 and VLDB 2011. Grants: Current funding includes NSF travel support for ICDE 2024 and a $1.4M NSF MRI grant for DiscourseLab (2025). Past grants include DOE support for soil microbiome data integration. Service: Associate Editor for VLDB Journal, PVLDB, and Distributed and Parallel Databases. Served as Program Committee member for SIGMOD, ICDE, and EDBT. Industry collaborations include advising on cloud DBMS architectures and distributed systems.

Michal FriedmanView profile

Assistant Professor

• Systems
• Concurrent Computing
• Programming Languages
• +3 more

Michal Friedman is an Assistant Professor at the Department of Computer Science, ETH Zurich, specializing in systems, concurrent computing, programming languages, and sustainable computing. He leads research on designing system fundamentals across software and hardware to enhance performance and efficiency in next-generation computing platforms. Prior to ETH, he completed a postdoc at the same institution and earned his Ph.D. from the Technion under Prof. Erez Petrank, focusing on concurrent data structures for non-volatile memories. Education: Ph.D. in Computer Science (Technion, advised by Erez Petrank), BSc Summa Cum Laude (Technion). Awards include the Eric and Wendy Schmidt Postdoctoral Award (2022), Blavatnik Prize (2021), and Azrieli Fellowship (2018–2021). His work spans persistent memory systems, concurrent algorithms, and energy-efficient computing. Key contributions include PCcheck (ML checkpointing), Dirigent (serverless orchestration), and foundational research on non-volatile memory correctness conditions. He has authored over 15 papers in top conferences like ASPLOS, SOSP, and VLDB, and serves on program committees for systems and programming languages venues.

• Distributed Systems
• Network Function Virtualization
• Systems Correctness
• +4 more

Aurojit Panda is an Assistant Professor of Computer Science at New York University's Faculty of Arts and Science. His research focuses on lightweight mechanisms for system correctness, network function virtualization, and distributed systems. He holds a Ph.D. from UC Berkeley and a B.S. from Brown University. Education: Ph.D., Computer Science, UC Berkeley (2017) B.S., Math-Computer Science, Brown University (2008) Research Interests: Network Function Virtualization (NFV) Distributed Systems Correctness Machine Learning Tooling and Optimization Operating Systems and SmartNIC Offloading Recent work includes designing distributed shared logs for datacenters, analyzing straggler effects in large model training, and developing tools like NNSmith for deep learning compiler testing. Teaching includes courses on distributed systems, operating systems, and big data/machine learning. He is actively involved in research teams such as NetSys Lab and contributes to open-source projects like NetBricks and BESS.

Michael FreedmanView profile

Professor

• Distributed Systems
• Networking
• Security
• +4 more

Michael J. Freedman is the Robert E. Kahn Professor of Computer Science at Princeton University, leading research in distributed systems, networking, and security. He co-founded Timescale, a cloud platform for time-series data, and previously co-founded Illuminics Systems (acquired by Neustar). His work includes Ethane (basis for OpenFlow/SDN), CoralCDN, and contributions to blockchain-based systems like Blockstack. Education: Ph.D., Computer Science, New York University (Courant Institute), 2007 M.Eng. and S.B., MIT Research Interests: Freedman’s research spans distributed systems, cloud infrastructure, time-series databases, privacy-enhancing technologies, and software-defined networking. He emphasizes practical, scalable solutions for real-world challenges in networking and storage. Article Trends: Recent work focuses on time-series database optimizations (e.g., tiered storage, compression), cloud platform efficiency, GPU acceleration, and blockchain applications. His publications address fault tolerance, query optimization, and resource management in distributed systems. Awards: ACM Grace Murray Hopper Award, PECASE (2010), Sloan Fellowship, multiple best-paper awards at SIGCOMM, ICFP, and TCC. Advising & Grants: Technical advisor to Blockstack and recipient of grants from NSF, ONR, and DARPA. His research has been commercialized through startups like Timescale and Illuminics. Affiliations: Member of Princeton’s Center for Information Technology Policy (CITP), exploring societal impacts of technology.

Wyatt LloydView profile

Professor

• Distributed Systems
• Networking
• Cloud Computing
• +7 more

Wyatt Lloyd is a Professor in the Computer Science department at Princeton University, leading the S* Network Systems (SNS) group with Mike Freedman, Amit Levy, and Mae Milano. His research focuses on distributed systems, networking, and cloud computing, emphasizing consistency models, geo-replication, and fault tolerance. He holds a PhD from Princeton (2013), followed by a postdoc at Facebook and an assistant professorship at the University of Southern California before returning to Princeton in 2017. Education : PhD, Computer Science, Princeton University, 2013 Postdoctoral Researcher, Facebook, 2013–2014 Assistant Professor, University of Southern California, 2014–2017 Research Interests : Lloyd’s work addresses tradeoffs between consistency guarantees and system performance in large-scale systems. Notable projects include TurboDB (NSDI ’24) for skewed workloads, Gryff (NSDI ’20) for consensus-unified storage, and Tectonic (FAST ’21), Facebook’s exabyte-scale filesystem. His group explores causal consistency, read-optimized transactions, and geo-distributed storage solutions. Publications : Recent work spans concurrency control (Natural Concurrency Control, OSDI ’23), caching optimizations (Learning Relaxed Belady, NSDI ’20), and fault-tolerant systems (Speculative Recovery, ATC ’22). These contributions balance strong consistency with high performance. Grants & Recognition : Supported by NSF grants (e.g., CNS Core, CISE), his work addresses modern distributed system challenges. Over 30 students have been advised, contributing to influential projects like Eiger, COPS, and Janus. Labs/Teams : The SNS group at Princeton focuses on systems research, collaborating on projects like the S* Network Systems initiative. Tools developed include Eiger (Apache Cassandra fork) and frameworks for causal consistency and distributed transactions.

Hind CASTEL SAMOVARView profile

Professor

• Computational Statistics
• Multimedia Data Engineering
• E-Health
• +6 more

Prof. Hind CASTEL is a Professor at Telecom SudParis affiliated with the SAMOVAR Lab (formerly UMR 5157). Her research focuses on computational statistics, multimedia engineering, e-health, and distributed systems. She contributes to projects involving optical technologies, cybersecurity, and IoT networks. She participates in academic events such as the SOP Seminar on June 12, 2023, discussing advanced mathematical methods for optimization and boundary problems. Her work addresses challenges in memory management (disaggregated systems), high-speed optical communication (III-V-on-SOI lasers), and natural language interfaces for process data. Part of the NeSS group Active in doctoral student mentoring through Samovar's annual PhD Day events Recent publications explore garbage collection in distributed systems, laser-based optical networking, and AI-driven query interfaces for business processes.

• Environmental Economics
• Input-Output Analysis
• Social Accounting Matrices (SAM)
• +3 more

Alfredo Jose Mainar Causape is a researcher affiliated with the Department of Economics, Quantitative Methods, and Economic History at the University of Zaragoza. His work focuses on environmental economics, bioeconomy, and multisectoral modeling using Social Accounting Matrices (SAM) and Input-Output frameworks. Doctorate (2010): PhD in Economics from the University of Zaragoza, with a thesis on consumption patterns and CO2 emissions via Input-Output analysis. Research interests span bioeconomic modeling, climate policy, agricultural development in Africa, and SAM-based economic impact assessments. He has contributed to databases like BioSAMs and Kenya SAM 2014, analyzing policy reforms in fertilizer use, trade liberalization, and rural job creation. Article trends emphasize policy evaluation in developing countries (Kenya, Ethiopia, Senegal), environmental accounting of productive sectors, and multisectoral interactions within the EU bioeconomy. His methodological focus includes SAM disaggregation, CGE modeling, and mixed multiplier analyses. He has collaborated on projects like the JRC DEMETRA CGE model and the STAGE_DEV framework for developing countries. His work bridges economic theory with practical policy tools for sustainability and development.

Boon Thau LooView profile

Professor

• Distributed Systems
• Networking
• Blockchain
• +2 more

Boon Thau Loo is the RCA Professor in the Department of Computer and Information Science at the University of Pennsylvania , with a secondary appointment in Electrical and Systems Engineering . He leads the NetDB@Penn research group and is an active member of the Distributed Systems Lab and the Penn database group . As the Senior Associate Dean for Graduate Education and Global Initiatives , he oversees academic programs and international collaborations. PhD in Computer Science (2006, UC Berkeley) M.S. in Computer Science (2000, Stanford University) B.S. in Computer Science with highest honors (1999, UC Berkeley) Boon Thau Loo's research spans Distributed Systems , Blockchain , and Networking . Key areas include Byzantine Fault Tolerance , Smart Contracts , Network Provenance , and Cloud Infrastructure . His work addresses challenges in Internet-scale Query Processing , Data Management in Disaggregated Environments , and Security for Distributed Systems . Recent publications focus on Adaptive Blockchain Systems , BFT Consensus , Smart Contract Optimization , and Distributed Transaction Processing . He explores Reinforcement Learning for Consensus , Data-dependent Order-Fairness , and Practical Declarative Networking to enhance scalability and security. His accolades include the Lindback Award for Distinguished Teaching (2022), Spira Award for Excellence in Teaching (2021), and Best Paper at EDBT (2020). He has been recognized for NSDI Outstanding Paper (2024) and International Student Advocate of the Year (2024). Boon Thau Loo has mentored 17 PhD students , 5 of whom have won dissertation awards . He co-founded two startups: Gencore Systems (Netsil) , acquired by Nutanix Inc. (2018), and Termaxia , acquired by Frontiir (2020). He oversees Penn Engineering's 6,000 graduate students and has launched initiatives like MCIT Online , MSE-DS Online , and MSE-AI Online .

Michela QuadriniView profile

Assistant Professor

• Bioinformatics
• Computational Biology
• RNA Secondary Structures
• +3 more

Michela Quadrini is an Assistant Professor at the University of Camerino with expertise spanning Bioinformatics , Computational Biology , and Graph Neural Networks . Her academic work focuses on RNA structure analysis, human activity recognition, and formal methods for collective adaptive systems. Research Interests include: RNA pseudoknots comparison and classification Machine learning applications in biomedical signal processing Spatial logics for complex system modeling Protein-protein interaction site prediction Ontology-based frameworks for activity recognition Publications demonstrate methodological innovation across: RNA structure alignment and translation tools (TARNAS) Graph neural network programming languages (μG) Stress detection from wearable sensor data Formal verification of collective systems Immunoinformatics feature engineering Technical Expertise combines computational biology with advanced machine learning techniques, evidenced by contributions to: Topological data analysis for RNA structures Convolutional neural network architectures Semantic ontologies in mechatronic systems Integral equation numerical methods

Andrew SontaView profile

Assistant Professor

• Human-building interaction
• Building energy
• Occupant behavior
• +6 more

Andrew Sonta is a Tenure Track Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL), leading the ETHOS Lab (Engineering and Technology for Human Oriented Sustainability). He also serves as Head of the Diversity Office at the School of Architecture, Civil and Environmental Engineering (ENAC). His expertise spans human-building interaction, sustainable design, and data-driven urban analysis. Sonta holds a PhD from Stanford University and conducted postdoctoral research at Columbia University's Data Science Institute. Education BS in Civil and Environmental Engineering, Northwestern University (2015) MS and PhD in Civil Engineering, Stanford University (2017, 2020) Research Focus Sonta’s work integrates computational tools with sustainability goals, addressing urban form, energy efficiency, and occupant behavior. Key areas include: - Data-driven building design for energy optimization - Machine learning for occupant behavior modeling - Social-environmental analysis of urban systems. His lab, ETHOS, emphasizes interdisciplinary solutions for societal and ecological challenges. Publications Recent work explores topics like walkability’s impact on social cohesion, occupant-centric energy systems, and global behavior databases. His research bridges urban informatics with machine learning to advance human-centric sustainability. Advising & Leadership He advises four PhD students and oversees the Diversity Office, promoting inclusivity in ENAC. Courses taught include sustainability frameworks, computational systems thinking, and energy-occupant dynamics in buildings. Labs & Teams Directs the ETHOS Lab, which collaborates on projects like the Global Building Occupant Behavior Database and smart energy systems. Engages with industry and academia to translate research into actionable sustainability strategies.

Helen SaibilView profile

Professor

• Structural Biology
• Molecular Biology
• Protein Folding
• +5 more

Prof. Helen Saibil is the Bernal Professor of Structural Biology at the School of Natural Sciences, Birkbeck, University of London. She holds academic affiliations in structural biology and molecular biophysics. Her research focuses on understanding molecular machinery involved in protein folding, chaperone systems, and host-pathogen interactions using advanced techniques like cryo-electron microscopy (Cryo-EM). Education: Bachelor’s degree from McGill University, Canada PhD from King’s College London Postdoctoral research at CEA Grenoble and University of Oxford Research Interests: Her work spans structural biology, protein homeostasis, and disease-related protein aggregation. Key areas include: Mechanisms of chaperonin-assisted protein folding Structural basis of amyloid fibril formation and disassembly Host cell interactions with pathogens like Plasmodium falciparum (malaria) and prions Development of Cryo-EM methodologies for high-resolution molecular imaging Recent Research Trends: Her articles highlight advancements in understanding disaggregase machinery (e.g., Hsp70 systems), prion fibril structures, and malaria parasite egress mechanisms. She also contributes to standardizing biological imaging metadata (REMBI initiative). Awards: Fellow of the Royal Society (UK) Fellow of the Academy of Medical Sciences Honorary Membership in British Biophysical Society and Royal Microscopical Society Advising & Labs: Supervised 5 doctoral students since 2013, with recent theses on topics like α-synuclein aggregation and chaperonin mechanisms. Her lab utilizes cutting-edge Cryo-EM facilities, including the UK’s Electron Bio-Imaging Centre (eBIC).

Ricardo Gonçalves MacedoView profile

Assistant Professor

• Storage Systems
• Operating Systems
• High-Performance Computing (HPC)
• +3 more

Ricardo Gonçalves Macedo is an Invited Assistant Professor at the University of Minho and a Researcher at INESC TEC's Distributed Storage Research (DSR) team since 2016. He holds a PhD in Computer Science (2023) from the MAP-i program at Universities of Minho, Aveiro, and Porto, focusing on user-level software-defined storage data planes. His research emphasizes storage systems and operating systems, addressing performance, reliability, and energy efficiency in large-scale I/O infrastructures. Key areas include kernel-bypass storage stacks, disaggregated resources, and HPC storage challenges. Recent work includes tools like LAZYFS for fault injection and PADLL for metadata QoS control. He leads projects like DisaggregatedHPC (energy-efficient resource disaggregation) and CDMS (healthcare data management). Ricardo has supervised over 10 theses at the University of Minho and contributes to open-source projects in storage optimization. His work is published in top venues like VLDB, IEEE Cluster, and FAST.