Find Academic Supervisors

• Distributed Systems
• High Performance Computing
• Fault Tolerance
• +4 more

Aishwarya Ganesan is an Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign. Her research focuses on distributed systems, storage systems, and fault tolerance mechanisms, with emphasis on high-performance computing and datacenter infrastructure. She leads projects addressing challenges in replicated storage, consensus protocols, and system resilience. Her work explores fault tolerance in disaggregated datacenters, log abstractions for low-latency applications, and novel replication strategies for modern storage systems. She has developed frameworks like LazyLog and IONIA to improve system efficiency and reliability. Her research also extends to automatic reliability testing for cluster management controllers and analyzing distributed storage vulnerabilities. Key contributions include demonstrating how redundancy alone does not guarantee fault tolerance, and proposing consistency-aware durability mechanisms for storage systems. She received the NSF CAREER Award in 2024 for her research on storage-aware fault tolerance. Her work spans 21 peer-reviewed publications, with notable contributions in conferences like SOSP, EuroSys, and FAST. Current projects investigate fault tolerance in emerging memory technologies and system recovery protocols for consensus-based storage.

Olga VekslerView profile

Professor

• Computer Vision
• Machine Learning
• Deep Learning
• +6 more

Olga Veksler is a Professor at the University of Waterloo's Department of Computer Science, part of the Faculty of Mathematics. She holds a Ph.D. and M.Sc. from Cornell University (1999) and a B.A. from New York University (1995). Her research focuses on computer vision, machine learning, and discrete optimization, with notable contributions to image segmentation, graph algorithms, and deep learning integration. Her work emphasizes semantic segmentation, salient object detection, and efficient optimization techniques for graphical models. Education: Ph.D. in Computer Science, Cornell University, 1999 M.Sc. in Computer Science, Cornell University, 1999 B.A. in Computer Science, New York University, 1995 Her research explores intersections between machine learning and traditional computer vision challenges, particularly leveraging graph-based optimization and CRF models. Recent trends in her work include weakly supervised learning, sparse non-local CRF applications, and test-time adaptation strategies for salient object detection. She has pioneered methods for shape priors in multi-object segmentation and efficient graph-cut algorithms. Her advising and grant activities are foundational to her research, though specific grant details are not listed here. She maintains a lab focused on advancing computer vision through algorithmic innovation, with contributions to both theoretical frameworks and practical applications in medical imaging and scene understanding.

• Cancer Research
• Immunology
• Oncology
• +3 more

Dr. Karen Anderson is a Professor at Arizona State University (ASU), affiliated with the School of Life Sciences, the Biodesign Center for Personalized Diagnostics, and the College of Health Solutions. Her research focuses on tumor biology and immune system interactions in cancer, particularly developing biomarkers for early detection of cancers like breast, ovarian, pancreatic, and HPV-related cancers. She employs molecular techniques such as protein arrays, next-gen sequencing, and functional genomics to identify therapeutic targets and vaccine candidates. Education: Ph.D. in Microbiology and Immunology (Duke University), M.D. from Duke University School of Medicine, and B.A. in Chemistry (University of Virginia). Research interests include cancer immunotherapy, autoantibody profiling, and translational applications of proteomics. Key achievements include pioneering autoantibody-based biomarker assays and investigating HPV serology in head and neck cancers. Awards include the Health Care Heroes Award and recognition as one of Arizona's Most Influential Women. Teaching responsibilities include courses on research techniques and honors thesis supervision. Grants span biomarker validation, cancer genomics, and point-of-care diagnostics. Active in professional service, including roles in grant review panels and public health initiatives.

Gene CoopermanView profile

Professor

• High-Performance Computing
• Computer Systems
• Transparent Checkpointing
• +4 more

Gene Cooperman is a Professor at the Khoury College of Computer Sciences at Northeastern University, with an affiliation in the College of Engineering. His research focuses on high-performance computing (HPC), transparent checkpoint-restart systems, and model checking. He leads the High Performance Computing Laboratory, where he explores checkpointing technologies like DMTCP, MANA for MPI, and CRAC for CUDA, aiming to enhance HPC workflows on supercomputers such as NERSC's Perlmutter. His work bridges distributed computing, parallel algorithms, and system software to address challenges in fault tolerance, scalability, and resource management. Cooperman has advised 10 PhD students and co-authored over 125 refereed publications, contributing to projects like Geant4-MultiThreaded and Roomy for disk-based computation. His teaching includes courses on computer systems and HPC seminars. Education: Background in computational algebra and parallel computing, transitioning to HPC systems and checkpointing. Research Themes: Transparent checkpointing, MPI agnostic solutions, CUDA integration, and HPC resource optimization. Recent articles emphasize MPI checkpointing, reversible debugging (FReD), and CUDA support, reflecting trends in distributed and GPU-accelerated systems. His grants include NSF, NERSC/DOE, and MemVerge funding. Cooperman collaborates with institutions like CERN and NERSC, advancing applications in particle physics simulations and supercomputing. Current students include Aayushi Gautam, Jiajun Cao, Rohan Garg, and Twinkle Jain.

Matthias BarzView profile

Professor

• Polymer Science
• Biotherapeutic Delivery
• Nanoparticle Synthesis
• +7 more

Matthias Barz is a Professor of Biotherapeutic Delivery at the Leiden Academic Centre for Drug Research (LACDR) , Faculty of Science , Leiden University . He leads the Barz Lab , focusing on polymer science and biomedical applications of functional nanoparticles. Professor of Biotherapeutic Delivery (Leiden University) Head of the Division of BioTherapeutics Researcher in reactive polymer systems and nanocarrier design His research bridges polymer chemistry with biomedical applications, emphasizing polypept(o)ide-based nanocarriers for targeted drug delivery in cancer, inflammation, and neurodegenerative diseases. Key areas include: Stimuli-responsive polymer architectures Secondary structure-driven self-assembly Core-crosslinked micelles for controlled cargo release Redox-sensitive disulfide bonds for intracellular delivery Protein-repellent nanoparticle shells Riboflavin-functionalized nanocarriers for tumor targeting The lab's publications highlight advancements in polysarcosine-containing copolymers , orthogonal functional group utilization , and modular nanoparticle platforms with precise control over morphology and function. Current projects explore the clinical translation of these systems for immunotherapy and diagnostics. Scientific recognition includes: Dozentenpreis des Fonds der Chemischen Industrie (2018) PMSE Young Investigator Award (2018) Nachwuchswissenschaftlerstipendium der GDCh (2017) His team trains graduate students in polymer synthesis, nanoparticle characterization, and biomedical application testing. Collaborations span institutions like the University of Tokyo and Johannes Gutenberg University Mainz , with ongoing projects under the SFB 1066 initiative for malignant melanoma immunotherapy.

Donald RobertsonView profile

Professor

• Econometrics
• Applied Macroeconomics
• Financial Economics
• +3 more

Professor Donald Robertson is a faculty member at the University of Cambridge , holding the position of Professor of Economics and Director of Graduate Studies and PhD Programme within the Faculty of Economics . He is affiliated with Pembroke College and contributes to econometric research and graduate education. Research Interests : His work focuses on Econometrics , Applied Macroeconomics , and Financial Economics , with methodological expertise in Time Series Analysis , Panel Data Analysis , and Predictive Modeling . His publications address topics like cross-sectional dependence, unit root testing, and instrumental variable estimation. Teaching : He instructs modules such as Introduction to Probability and Statistics , Time Series Methods , and MPhil Prep Course - Statistics . Publications : Recent contributions include work on R² bounds for predictive models, factor residuals in panel data, and fiscal fatigue in debt ratios, reflecting his focus on econometric theory and macroeconomic applications. Contact : Email dr10011@cam.ac.uk or phone +44(0)1223 335270. Office hours by email appointment in Room 70.

• Cybersecurity
• Maritime Cyber Risk Assessment
• Dynamic Positioning Systems
• +12 more

Pelin Bolat is an Associate Professor in the Department of Fundamental Sciences at Istanbul Technical University (ITU), College of Maritime Studies. She is actively engaged in maritime cybersecurity, risk assessment, and maritime safety research. Her work is supported by multiple BAP and EU-funded projects, with ongoing research extending into 2025. Her research interests include cybersecurity in maritime navigation systems, dynamic positioning, port state control, and GHG emissions in the maritime sector. She applies advanced methodologies such as fuzzy FUCOM, CORAS framework, and association rule mining to analyze cyber and operational risks. Her recent publications (2023–2025) reflect a strong trend in maritime cybersecurity, focusing on ECDIS, RADAR, ransomware, and cyber hygiene. These works span high-impact journals in maritime engineering and technology, demonstrating interdisciplinary engagement with computer science, safety engineering, and policy analysis. She serves as a principal investigator on several key projects, including cyber risk assessment of bridge navigation equipment and system dynamic modeling of maritime GHG emission measures. She also mentors 15 theses in progress, indicating her active role in student supervision. Her collaborative network includes researchers like Gökhan Kayişoğlu and international partners. While no formal awards are listed, her leadership in EU and BAP projects underscores her academic prominence.

• Reliability Engineering
• Hardware Security
• Low-Power Design
• +4 more

Dr. Saqib Khursheed is an Assistant Professor in the Department of Electrical Engineering and Electronics at the University of Liverpool, UK. He holds a PhD in Electronics and Electrical Engineering from the University of Southampton (2010), where he later worked as a Senior Research Fellow on EPSRC-funded projects. His research focuses on reliability, testability, and hardware security of low-power/high-performance systems and 3D integrated circuits. He has served in leadership roles at major conferences such as IEEE DFT (General Co-Chair 2018) and ETS (Program Co-Chair 2017). Dr. Khursheed is a Senior Member of IEEE and Fellow of the Higher Education Academy. His professional activities include roles as Guest Editor for IEEE Design & Test (2016) and IET Computers & Digital Techniques (2018). He currently chairs the Examinations Officer committee in his department and serves on multiple university-level committees (Senate Progress, Quality Assurance). He has organized workshops like the Friday Workshop on 3D Integration (2012-2015) and reviews for top-tier journals/conferences in his field. Dr. Khursheed’s funded projects include the eFutures Sandpit Award (2018) for secure microelectronics design. His teaching responsibilities include coordinating modules like Advanced Low Power Computer Architecture (ELEC470) and Digital Electronics & Microprocessor Systems (ELEC211). His research has led to innovations in hardware security (e.g., PCB Trojan detection via machine learning), age estimation of ICs, and fault tolerance in 3D ICs.

Susan RobertsonView profile

Professor

• Sociology of Education
• Globalization and Education
• Education Governance
• +4 more

Susan Robertson holds the Chair in Sociology of Education at the Faculty of Education, University of Cambridge, where she serves as Director of the Doctoral Programme and Editor-in-Chief of Globalisation, Societies and Education . She joined Cambridge in 2016 after academic appointments at the University of Auckland and University of Bristol, bringing over three decades of international expertise in critical education studies. Her educational foundation includes doctoral research in Sociology/Policy at the University of Calgary (1990), preceded by professional experience in the Research Division of Western Australia's Ministry of Education. This trajectory established her cross-sectoral perspective on education systems and policy implementation. Robertson's research critically examines state-education relationships through governance frameworks that determine educational equity and outcomes. She investigates how global and regional actors mediate the social contract between states and citizens, with particular focus on geopolitical shifts, OECD influence, and neoliberal transformations in higher education. Her work bridges sociology, political economy, and decolonial perspectives to address social justice imperatives in education. Analysis of her 2024-2026 publications reveals sustained engagement with higher education geopolitics, digital transformation challenges, and global governance mechanisms. Key thematic clusters include critiques of OECD-driven policy frameworks, analyses of ordinal citizenship in education systems, and examinations of how digitalization reshapes university missions while exacerbating existing inequalities. As Director of the Doctoral Programme, Robertson oversees comprehensive PhD training while convening the Culture, Politics and Global Justice research cluster that fosters interdisciplinary collaboration on transnational education challenges. Her service on the ESRC funding council positions her at the nexus of research strategy and resource allocation in UK social sciences. The Culture, Politics and Global Justice cluster under her leadership functions as a dynamic hub for critical scholarship, hosting regular seminars and collaborative projects that connect Cambridge researchers with global partners to address emergent issues in education governance and social transformation.

Aybars TuncdoganView profile

Associate Professor

• Digital Innovation
• Information Security
• Marketing Strategy
• +3 more

Aybars Tuncdogan is a Reader in Digital Innovation and Information Security at King’s Business School, King’s College London. He holds affiliations with the King’s AI Institute, King’s Cybersecurity Centre (Informatics), and King’s Cybersecurity Group (War Studies). A Fellow of the Higher Education Academy, he also serves on the editorial review board of Industrial Marketing Management . Education : PhD in Management, Rotterdam School of Management, Erasmus University MPhil in Business Research (Distinction), Erasmus University Bachelor’s in Business Management & Computer Science (Honors), Earlham College Research Interests : His work focuses on three pillars of digital innovation: generation (crowdsourcing, AI), marketing (digital brand personality, sales ambidexterity), and protection (information security, corporate espionage). He integrates psychology (individual differences, social identity) and computer science (machine learning/AI) frameworks. Publications Trends : Recent work addresses cybersecurity challenges in retail, AI ethics in healthcare, and interdisciplinary innovation. He frequently publishes in top-tier journals like Journal of Management and Scientific American , blending academic rigor with practitioner impact. Awards & Contributions : 2015 Best Paper Award (shared) Edited books including Oxford Handbook of Individual Differences and Strategic Renewal Teaching & Pedagogy : Develops innovative teaching methods like inquiry-based learning to foster student creativity. Taught modules on digital marketing, consumer behavior, and research methods. Labs/Teams : Contributes to cybersecurity initiatives at King’s, focusing on AI-driven defense mechanisms and organizational cyber resilience strategies.

Hsueh-Chia ChangView profile

Professor

• Microfluidics
• Nanofluidics
• Electrokinetics
• +5 more

Hsueh-Chia Chang is the Bayer Professor of Chemical Engineering in the Department of Chemical and Biomolecular Engineering at the University of Notre Dame's College of Engineering. He also holds a concurrent faculty position in the Department of Aerospace and Mechanical Engineering. As Principal Investigator of the Chang Lab, he leads cutting-edge research in microfluidic and nanofluidic technologies for biomedical applications. Prof. Chang received his B.S. in Chemical Engineering from Caltech in 1976, followed by M.S. and Ph.D. degrees in Chemical Engineering from Princeton University in 1977 and 1980, respectively. His academic journey has established him as a leader in the field of microfluidics and biosensing technologies. Chang's research focuses on developing low-cost liquid biopsy nanotechnologies for cancer screening and therapy management. His lab specializes in microfluidic and nanofluidic research coupled with electrokinetics, optics, plasmonics and acoustics for biosensing applications. Key research areas include Electrokinetics & Biosensing, Optics & Plasmonics, Nanoelectrokinetics, and Droplet Microfluidics. The Chang Lab has developed innovative platforms that can isolate and sort tumor cells, exosomes, microvesicles, lipoproteins, and stress granules from blood samples, then lyse these structures to release RNA/protein biomarkers for detection and quantification. His recent publications reveal a strong focus on extracellular vesicle diagnostics, cancer biomarker detection, and point-of-care diagnostic technologies. The research spans multiple disciplines including oncology, cardiology, and neurology, with applications for pancreatic, liver, breast, ovarian, and lung cancers as well as myocardial infarction diagnosis. Fellow of American Institute of Medical and Biological Engineering (2025) Provost Research Achievement Award, Notre Dame (2024) Fellow of the National Academy of Inventors (2020) Lifetime Achievement Award, American Electrophoresis Society (2019) Fellow of the American Physical Society (1997) Presidential Young Investigator Award, NSF (1985) Prof. Chang has advised over 50 PhD students and postdocs who have gone on to prominent positions in academia and industry. His lab has secured significant funding and has commercialized several technologies through startups like Aopia Biosciences, which launched NanoEx at ISEV 2024. The Chang Lab maintains active collaborations with medical researchers for validating their diagnostic platforms against various cancers and cardiac conditions.

Konstantinos KarapiperisView profile

Assistant Professor

• Solid Mechanics
• Multiscale Modeling
• Data Science
• +7 more

Konstantinos Karapiperis is a Tenure Track Assistant Professor at EPFL's Laboratory of Multiscale Modeling of Materials (LMD), within the School of Architecture, Civil and Environmental Engineering (ENAC). His research integrates mechanics , multiscale modeling , and data science to study geomaterials and structural materials. PhD in Applied Mechanics (minor in Applied Mathematics), Caltech Postdoctoral Researcher & Lecturer, ETH Zürich (Marie Skłodowska-Curie Fellowship) Research focuses on granular materials , architected materials , and nonlocal modeling using techniques like Level-Set Discrete Element Method (LS-DEM) and machine learning . Recent work explores fracture control via graph neural networks and thermodynamics-informed models. Selected scientific award: Marie Skłodowska-Curie Fellowship Teaches courses in Soil Mechanics and Multiscale Modeling . PhD students include Thomas Henzel and Hrishikesh Gopakumar Menon. His Data-Driven Mechanics Laboratory (LMD) develops predictive tools for granular and structured material behavior.

• Cognitive Science
• Philosophy of Mind
• Distributed Cognition
• +3 more

Michael Wheeler is a Professor in Philosophy at the University of Stirling, focusing on cognitive science, phenomenology, and the philosophy of technology. His work bridges existentialist philosophy with modern AI ethics and embodied cognition. Key Research Themes: Extended mind, distributed cognition, and transparency in smart machines. Recent Projects: Explore the societal impact of AI, cognitive change in the arts, and the interplay between aging and cognition. Selected Articles (2024-2019): His publications span topics like creativity and contingency in the arts, transparency in AI, and the evolutionary psychology of reasoning. Notable Contributions: Advocates for integrating phenomenology into cognitive science and challenges representationalist frameworks in AI and robotics.

Behzad FatahiView profile

Professor

• Unsaturated Soil Mechanics
• Dynamic Soil-Structure Interaction
• Ground Improvement Techniques
• +6 more

Professor Behzad Fatahi is a distinguished academic in Civil and Environmental Engineering at the University of Technology Sydney (UTS), specializing in geotechnical engineering, railway infrastructure, and sustainable construction technologies. With a career spanning over 16 years at UTS, he has served as Deputy Head of School - Teaching and Learning (2024-present), Head of Discipline (2020-2024), and School Research Coordinator (2012-2017). His research focuses on unsaturated soil mechanics , dynamic soil-structure interaction , and green infrastructure solutions . Academic Appointments : Professor (2024-present), Associate Professor (2017-2024), Senior Lecturer (2011-2017), Lecturer (2008-2011) Research Leadership : Supervised 21 PhD students to completion, developed groundbreaking techniques for landfill waste reuse and tyre-derived aggregates in railway construction His work on seismic resilience of LNG tanks and bioengineered soil stabilization has received international recognition, including the 2023 Best Research Paper Award at the Australasian Association for Engineering Education conference. Professor Fatahi's industry experience includes geotechnical engineering roles at Coffey International and SES Engineering prior to academia. Key Research Contributions : Developed green corridor models for railway lines using coupled flow-deformation equations Pioneered AI-integrated teaching frameworks for civil engineering education Advanced machine learning techniques for intelligent compaction and structural buckling analysis As a Category 1 supervisor , he mentors graduate researchers in Civil Engineering , Geomechanics , and Earthquake Engineering . His peer-reviewed work (>240 publications) demonstrates technical excellence and innovation across multiple geotechnical domains.

• Data Systems for AI
• Retrieval-Augmented Generation (RAG)
• Database Systems
• +4 more

Yongjoo Park is an Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the Grainger College of Engineering. He leads research in data-intensive AI systems as a member of the Data and Information Systems (DAIS) lab, focusing on novel data systems that bridge database theory and practical AI applications. His work emphasizes open-source contributions through GitHub and direct societal impact. Research interests center on systems for data-intensive AI , particularly efficient Retrieval-Augmented Generation (RAG) systems for exploratory AI, data science versioning, and in-storage computing. Key projects include Kishu (the world's first undoable Jupyter notebook with time-travel capabilities), CARE (a causal-relational system for structured/unstructured data), and AirDB/AirIndex (serverless transactions and automatic index optimization). His group develops tools enabling scalable, optimized AI workflows from storage layers to LLM inference. Recent publications reveal a strong focus on interactive data systems (85% of recent work), with significant contributions to notebook environments (Kishu), vector databases (ISCA'25), and RAG optimization. Awards highlight technical innovation, including SIGMOD 2025 Best Demo Award and NSF CAREER funding. His open-source philosophy drives GitHub releases of all major systems. SIGMOD 2025 Best Demo Award (Kishu) NSF CAREER Award (Novel data science systems) SIGMOD'23 Best Artifact Award Honorable Mention (DeepOLA) IBM-Illinois Project Selection (VectorDB/RAG) Mentorship spans 12 current PhD/MS students and 6 graduated advisees, including Supawit Chockchowwat (now Postdoc at Google, future Assistant Professor at CMKL University). He teaches advanced courses like CS511 (Advanced Data Management) and recruits 1-2 new PhD students annually, prioritizing data systems research. His lab emphasizes diversity, individual respect, and concrete outcomes in a collaborative workspace.