Find Academic Supervisors

• Computer Science
• Artificial Intelligence
• Cybernetics
• +3 more

Dilip Sarkar serves as an Associate Professor in the Department of Computer Science at the College of Arts and Sciences, University of Miami. His academic profile demonstrates a strong research focus across multiple domains of computer science with particular emphasis on theoretical foundations and practical applications. Dr. Sarkar's research interests include: Artificial Intelligence and Cybernetics Parallel Algorithms and Programming Combinatorics Image Processing and Compression Internet of Things Security Machine Learning Applications in Healthcare Quantum Computing Approaches His publication record from 2018-2024 reveals a researcher engaged with cutting-edge computational challenges. Recent work spans quantum tensor networks for time series analysis, security frameworks for single sign-on systems, efficient computation in belief theoretic models, and machine learning applications for traumatic brain injury recovery prediction. His research demonstrates consistent integration of theoretical computer science with practical problem-solving across diverse application domains. As a member of CCS (Center for Computational Science) at the University of Miami, Dr. Sarkar participates in interdisciplinary research initiatives that bridge computational methods with scientific discovery across multiple fields. His technical expertise spans both theoretical frameworks and practical implementations, with notable contributions to image compression techniques, particularly for medical applications, and security protocols for modern web and IoT environments.

Leonard J. SchulmanView profile

Professor

• Algorithms
• Communication Protocols
• Combinatorics
• +6 more

Leonard J. Schulman is a Professor of Computer Science at the California Institute of Technology (Caltech), where he has been on the faculty since 2000. He is affiliated with the Caltech Center for the Mathematics of Information (which he directed from 2003 to 2017) and the Institute for Quantum Information and Matter. His academic appointments have included positions at UC Berkeley, the Weizmann Institute of Science, the Georgia Institute of Technology, and the Mathematical Sciences Research Institute. Schulman received his BSc in Mathematics in 1988 and his PhD in Applied Mathematics in 1992, both from the Massachusetts Institute of Technology (MIT). Schulman's research spans several overlapping areas in theoretical computer science and applied mathematics. His work focuses on algorithms and communication protocols , combinatorics and probability , coding and information theory , and quantum computation . More recently, his research has expanded into causal inference and machine learning , particularly in the areas of mixture models, causal discovery, and structure learning. His approach combines deep theoretical insights with practical applications across multiple domains. An analysis of Schulman's recent publications (2019-2025) reveals a strong focus on causal inference and machine learning, particularly in the areas of mixture models, causal discovery, and structure learning. His work bridges theoretical computer science with statistical learning, often developing novel algorithms with provable guarantees. He has also maintained his foundational work in coding theory, algorithms, and quantum computation, demonstrating remarkable breadth across theoretical computer science. IEEE Schelkunoff Prize (2004) ACM Notable Paper (2012) UAI Best Paper Award (2016) FOCS Test of Time Award (2022) S. A. Schelkunoff Transactions Prize Paper Award (2004) SIAM Fellow NSF CAREER award NSF mathematical sciences postdoctoral fellowship MIT Bucsela prize in mathematics Schulman has advised numerous PhD students and postdoctoral researchers who have gone on to successful careers in academia and industry. His former students and postdocs include notable researchers such as Ashwin Nayak, Yaoyun Shi, Sean Hallgren, Jie Gao, and Michael Langberg. He served as Editor-in-Chief of the SIAM Journal on Computing from 2013 through 2018 and has been on the editorial boards of several prestigious journals including the Journal of the ACM, ACM Transactions on Algorithms, and SIAM Journal on Discrete Mathematics. Schulman directs the Caltech Center for the Mathematics of Information, a research center focused on the mathematical foundations of information processing, communication, and computation. His work often involves interdisciplinary collaborations across computer science, mathematics, physics, and economics.

Elizabeth M.Y. LeeView profile

Assistant Professor

• Materials Science
• Quantum Technologies
• Energy Sustainability
• +3 more

Elizabeth (Liza) Lee is an Assistant Professor at the Samueli School of Engineering , University of California, Irvine (UCI), with joint appointments in Materials Science and Engineering and Chemical and Biomolecular Engineering . Her research program focuses on theory and computational modeling of materials formation, breakdown, and transport to design sustainable solutions for quantum and energy technologies. Ph.D. , MIT, Chemical Engineering M.S. , MIT, Chemical Engineering Practice B.S./B.A. , Johns Hopkins University, Chemical and Biomolecular Engineering and Chemistry Lee’s research bridges ab initio calculations , machine learning , and molecular simulations to study functional materials. Key areas include catalytic plastic waste deconstruction , quantum defects in semiconductors , and computational method development using statistical mechanics and machine learning. Her work has implications for sustainable synthesis , quantum information science , and energy technologies . Her recent publications (2025–2024) span nanostructure modeling , electrocatalysis , machine learning in materials science , and solid-state electrolytes , reflecting her interdisciplinary approach. Notable awards include the NSF CAREER Award , UCI Samueli Faculty Development Chair , and DOE ASCR Leadership Computing Challenge Award . NSF CAREER Award UCI Samueli Faculty Development Chair DOE ASCR Leadership Computing Challenge Award NSF Graduate Research Fellowship AIChE Electronics and Photonics Materials Award UCI Engineering Student Council’s Professor of the Year Award Maria Lastra Postdoctoral Mentor Award

• Nanoplasmonics
• Nano-optics
• Biochips
• +7 more

Li Yi is a Tenured Associate Professor at the School of Microelectronics, Southern University of Science and Technology (SUSTech) , with expertise in nanoplasmonics, nano-optics, and biochips. His career spans institutions including KU Leuven, Imperial College London, and Ludwig-Maximilians-Universität München. Education: Ph.D. (2015, KU Leuven & IMEC), M.S. (2010) and B.S. (2007) in Biomedical Engineering from Zhejiang University. Career: Associate Professor (2021–present) and Assistant Professor (2019–2020) at SUSTech; LMU Research Fellow (2018–2019); Research Associate (2015–2018) at Imperial College London. Research Interests focus on single-molecule biochips, DNA data storage, and nanopore sequencing. His work bridges nanotechnology with biomedical applications, including: Integrated circuit-compatible optical/electrical devices Computational lithography and nanoscale imaging Neural network training for biosensing Publications include >60 peer-reviewed articles with 25 H-index. His recent work emphasizes DNA-based data encryption, nanopore engineering, and portable biosensing systems. Key journals: Nature Communications, Nano Letters, ACS Nano. Scientific Awards : LMU Research Fellowship (Marie Curie COFUND) imec Excellent Scientific Award Shenzhen 'Peacock Plan' Category B Talent Outstanding Poster Award at Surface Plasmon Photonics 2017 Participation in Lindau Nobel Laureates Meeting (2019) Grants include Ministry of Science and Technology Key R&D Youth Program, NSFC General Program, and Guangdong Provincial Key Program. His lab develops: Fluidic nanopores for single-molecule sensing Optical antennas for enhanced detection Training programs in biochip design and nano-optics

David GoView profile

Professor

• Plasma Science
• Heat Transfer
• Fluid Dynamics
• +3 more

David Go is the Vice President and Associate Provost for Academic Strategy at the University of Notre Dame, where he also holds the Viola D. Hank Professorship in Aerospace and Mechanical Engineering. He oversees implementation of the University Strategic Framework and manages faculty appointment processes, with administrative oversight of institutes including the Lucy Institute for Data and Society and the Fitzgerald Institute for Real Estate. His research focuses on plasma science, heat transfer, fluid dynamics, and chemical analysis, with significant contributions to plasma-electrochemistry and sustainable chemical synthesis. Education: B.S. (2001) and M.S. (2004) from University of Notre Dame, Ph.D. (2008) from Purdue University His work explores plasma-liquid interfaces, solvated electron dynamics, and plasma-assisted catalysis, particularly for light hydrocarbon conversion. Recent publications highlight advancements in non-aqueous plasma electrolysis, machine learning-enhanced plasma sintering, and interfacial transport phenomena. Awards include the Air Force Young Investigator Award, NSF CAREER award, and multiple honors for teaching and innovation. Current research trends integrate plasma physics with chemical engineering and materials science, focusing on sustainable energy solutions and microscale manufacturing. Scientific recognitions include: Fellow of the American Society of Mechanical Engineers Senior Member of IEEE IEEE Early Achievement Award First-Source Bank Commercialization Award Go has supervised graduate studies and received patents for technologies in plasma-assisted synthesis and microfluidic diagnostics. His leadership roles involve committees addressing academic governance, risk management, and foreign influence in research.

Fadi AL-TURJMANView profile

Professor

• Artificial Intelligence of Things (AIoT)
• Wireless Sensor Networks
• Blockchain Applications
• +7 more

Prof. Dr. Fadi AL-TURJMAN serves as the founding Dean of the Faculty of AI and Informatics at Near East University (NEU), Cyprus. He holds multiple leadership roles including Head of the Software Engineering Department and Director of the AI and Robotics Institute and the International Research Center for AI and IoT. With a PhD in Computer Science from Queen’s University (2011), he specializes in AIoT systems, wireless networks, and blockchain integration. Affiliation: Near East University Leadership: Founding Dean for AI and Informatics, Director of AI & Robotics Institute Research Focus: His work bridges Artificial Intelligence of Things (AIoT) , Blockchain Applications , and Smart Networking . He explores cybersecurity frameworks for smart cities, quantum state optimization techniques, and novel AI-driven solutions for healthcare, agriculture, and energy systems. Key Article Trends: Recent publications emphasize Transformer models for environmental monitoring, blockchain-enabled security protocols , and evolutionary algorithms for resource optimization. His research spans interdisciplinary domains including medical diagnostics, vehicular networks, and sustainable infrastructure. Scientific Awards: Lifetime Golden Award of Dr. Suat Gunsel (2022) Multiple Best Research Awards at International Venues Labs & Teams: Directs the International Research Center for AI and IoT at NEU, leading multidisciplinary teams in developing advanced networking technologies and AI-driven solutions for global value chain applications.

Jonathan MamouView profile

Professor

• Quantitative Ultrasound Imaging
• Biomedical Engineering
• Medical Imaging
• +5 more

Jonathan Mamou is a Professor of Electrical Engineering in Radiology at Weill Cornell Medical College since 2024. His research focuses on quantitative ultrasound imaging, biomedical engineering, medical imaging, and acoustic microscopy. Ph.D., University of Illinois (2005) M.S., University of Illinois (2002) B.S., Telecom Paris (2000) His research bridges electrical engineering and radiology, developing advanced ultrasound techniques for medical diagnostics. Key areas include quantitative acoustic microscopy , biomechanical tissue analysis , and machine learning in ultrasound imaging . Recent work spans prostate cancer detection , placental microstructure characterization , and myopia-related scleral changes . His publications (2025–2023) highlight innovations in high-frequency ultrasound for ophthalmology, quantitative imaging for cancer diagnostics, and quantum-driven resolution enhancement in acoustic microscopy. Grants from the Melanoma Research Alliance , National Institute of Biomedical Imaging & Bioengineering , and Stand Up To Cancer support his work on pancreatic cancer screening , interstitial lung diseases , and radiotherapy toxicity assessment .

Nectarios KozirisView profile

Professor

• Parallel and Distributed Systems
• Computer Architecture
• Systems Software
• +10 more

Nectarios Koziris is a Professor at the Department of Computer Science , National Technical University of Athens (NTUA) , and former Dean of the School of Electrical and Computer Engineering . His research focuses on Parallel and Distributed Systems , Computer Architecture , and Cloud Computing . Key Research Themes: Compiler-OS-Architecture Interaction, Datacenter Hyperconvergence, Sparse Matrix Optimization, Quantum Computing, FPGA Virtualization Leadership: Founder of ~okeanos (Europe's largest public Cloud IaaS), Co-founder of GFOSS , Member of IEEE Computer Society Greece, Advisor to Arrikto Inc. His work has led to over 180 publications with 5800+ citations (h-index 33) , including two Best Paper Awards (IPDPS 2001, CCGRID 2013) and Intel Recognition (2015). He has supervised 12 PhD students and participated in 15+ EU projects as coordinator or consortium partner. Scientific Leadership: Program Co-Chair for Europar 2012 , Organizer for IPDPS , ICPP , SC conferences, and active member in Cloud Computing Expert Groups for the European Commission.

• Intelligent Systems and Control
• Cognitive Robotics
• Nano-robotics
• +9 more

Laxmidhar Behera is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur, specializing in Intelligent Systems and Control. With over two decades of academic experience at IIT Kanpur and international research experience at institutions including Fraunhofer Institute of Autonomous Intelligent Systems in Germany, ETH Zurich, and University of Ulster, he has established himself as a leading researcher in cognitive robotics and intelligent control systems. Dr. Behera's research spans multiple cutting-edge domains including Cognitive Robotics, Nano-robotics, Vision based Control, Soft Computing, Information Retrieval in music and language, Semantic Information Processing, Physics of Complex Systems, Cyber Physical Systems, Formation Control of UAVs, Brain-Computer Interface (BCI), and Sanskrit Computational Linguistics. His interdisciplinary approach bridges traditional control theory with modern computational intelligence techniques, creating innovative solutions for complex real-world problems. His extensive publication record in top-tier journals like IEEE Transactions demonstrates his leadership in areas such as brain-computer interfaces, visual servoing, multi-robot systems, and music information retrieval. Notably, his work on quantum neural networks for EEG filtering and multisatellite formation control has received significant attention in the research community. UKIERI Standard Research Award 2008 Best Paper at International Conf. on Intelligent Sensors and Information Processing (ICISIP-2004) Best Paper at WoSco,02, Int. Conf. High-Performance Computing (HiPC, 2002) AICTE career award for young teacher (1997) Senior Member IEEE Multiple IEEE top accessed articles (2009-2010) As an Associate Editor for Autosoft Journal and Technical Committee Member for Intelligent Control at IEEE Control System Society, Dr. Behera actively contributes to the academic community. His laboratory in the Western Lab - 212A of the Department of Electrical Engineering serves as a hub for research in intelligent systems, where he mentors students and collaborates with researchers worldwide on cutting-edge projects in robotics, control systems, and computational intelligence.

Carrie WeidnerView profile

Senior Lecturer

• Quantum Physics
• Quantum Engineering
• Atom Interferometry
• +3 more

Dr. Carrie Weidner is a Senior Lecturer at the University of Bristol, affiliated with both the School of Physics and the School of Electrical, Electronic and Mechanical Engineering. Her research spans quantum control, atom interferometry, and quantum technology education, with a focus on robust control techniques in optical lattices and spin networks. Principal Investigator for Quantum Positioning, Navigation, and Timing Hub (2024-2029) Lead on EPSRC-funded project EP/Y004728/1 for trapped ultracold atom interferometry (2023-2025) Her recent work includes energy landscape shaping for quantum systems, deterministic generation of squeezed states, and innovative educational tools like the Quantum Composer. Publications analyze robustness metrics, control algorithms, and quantum-classical system comparisons. Collaborations span international institutions in quantum physics and engineering domains. She contributes to quantum outreach through gamification and interactive platforms, targeting improved education and community inclusivity. Current research trends emphasize precision measurement, error mitigation, and AI integration in quantum control systems.

Nicholas WrightView profile

Researcher

• High Performance Computing (HPC)
• Computer Architecture
• Performance Analysis
• +5 more

Nicholas Wright serves as the NERSC Chief Architect and Advanced Technologies Group Lead at Lawrence Berkeley National Laboratory's National Energy Research Scientific Computing Center (NERSC) since 2009. He holds a PhD in Chemistry from the University of Durham, United Kingdom. Role: Focuses on evaluating emerging technologies for scientific computing Key Contributions: Chief architect for NERSC-10 procurement (2026), optimized Perlmutter machine architecture His research explores performance analysis of HPC applications and architectural evaluation for future technologies. Recent publications address: GPU frequency optimization using DNN-based models FPGA acceleration for HPC workloads Quantum computing cost scaling Disaggregated memory system evaluation Scientific workflow characterization Scientific awards include: Co-investigator on SDCI HPC Improvement grant (2007-2012) His work bridges computer architecture and energy-efficient computing through rigorous performance modeling and technology evaluation for NERSC's diverse scientific users.

Yoann AltmannView profile

Professor

• Statistical signal processing
• Image processing
• Bayesian inverse problems
• +5 more

Yoann Altmann is Professor in the School of Engineering & Physical Sciences at Heriot-Watt University and a member of the Institute of Sensors, Signals & Systems. Since 2024 he holds the Chair in Electrical, Electronic & Computer Engineering (EECE), directing a research programme that bridges statistical signal processing, computational imaging and quantum & neuromorphic sensing. Education & career: 2010 – Eng. degree (Electrical Engineering), ENSEEIHT, Toulouse, France 2010 – M.Sc. (Signal Processing), National Polytechnic Institute of Toulouse 2013 – Ph.D. (Signal & Communications), IRIT Laboratory, Toulouse 2014-2017 – Post-doctoral Research Fellow, Heriot-Watt University 2017 – Royal Academy of Engineering Research Fellow & Assistant Professor, HWU 2024 – promoted to Professor, School of Engineering & Physical Sciences, HWU Research interests: Prof. Altmann develops mathematical and algorithmic tools for Bayesian inverse problems, with emphasis on single-photon LiDAR, low-illumination imaging, neuromorphic computational sensing, variational inference and sparse reconstruction. His work combines principled statistical modelling with efficient computational schemes to enable imaging in extreme scenarios such as underwater scattering, photon-starved environments, quantum metrology and real-time 3-D scene reconstruction. Publication trends: Across 160 outputs (2011-2025) his recent articles reveal a clear trajectory toward integrating modern machine-learning paradigms—variational autoencoders, diffusion generative models, spiking neural networks—with rigorous physics-based forward models. Applications span quantum parameter estimation, multimode-fiber endoscopy, hyperspectral & Compton imaging, nuclear safeguards and cultural-heritage spectroscopy, demonstrating both methodological breadth and high-impact interdisciplinary deployment. Honours & recognition: Royal Academy of Engineering Research Fellowship – competitively awarded (2017) Grants & datasets: He has generated four open datasets supporting reproducible research in quantum sensing, variational autoencoders, underwater single-photon LiDAR and multispectral fluorescence imaging, reflecting sustained funding and commitment to open science. Continuous peer-review service for IEEE and Elsevier journals since 2013 underlines his standing within the signal-processing community. Labs & teams: He leads the Bayesian Imaging & Sensing Computing (BISC) group ( https://bisc.site.hw.ac.uk ) which hosts post-docs, PhD researchers and international visitors working on statistical machine-learning for imaging, sensing and quantum technologies.

Renaud PacaletView profile

Researcher

• Hardware Security
• Side-Channel Attacks
• Embedded Systems
• +7 more

Renaud Pacalet is a Researcher at Institut Mines-Télécom – Télécom Paris , affiliated with the Communications and Electronics (Comelec) Department and the System on Chip (LabSoc) research team under the Information Processing and Communication Laboratory (LTCI). His work spans hardware security, embedded systems, and software-defined radio (SDR) architectures. Current Research: Hardware security, side-channel attacks (power, timing, fault injection), RISC-V security analysis using gem5, FPGA scheduling for cloud data centers, and model-driven design methodologies. Past Research: Hardware acceleration for ray tracing, SDR front-end processing, SoC security, and memory bus protection (SecBus project). Teaching: Courses on Digital Systems, Computer Architecture, and Hardware Security at EURECOM, including lab sessions on side-channel attacks and fault analysis. Email: renaud.pacalet@telecom-paris.fr Contact: Télécom ParisTech, Campus SophiaTech, 450 route des Chappes 06410 Biot, France

• Machine Learning
• Statistical Learning Theory
• Algorithmic Fairness
• +12 more

Massi Pontil is a part-time Professor of Computational Statistics & Machine Learning in the Department of Computer Science at University College London (UCL). He joined UCL as a lecturer in 2003 and was promoted to Professor in 2010. Since 2016, his primary appointment has been at the Istituto Italiano di Tecnologia (IIT), where he leads the CSML research group. His work bridges theoretical machine learning with practical applications in physical sciences. His research interests span a wide range of topics in machine learning theory and algorithms: Machine Learning Theory and Statistical Learning Algorithmic Fairness and Ethical AI Kernel Methods and Reproducing Kernel Hilbert Spaces Transfer Learning, Multitask Learning, and Meta-Learning Operator Learning and Dynamical Systems Sparsity Regularization and Optimization Pontil's recent work focuses on the intersection of machine learning with numerical simulations of physical systems, particularly in molecular dynamics and climate science. His publications demonstrate a strong emphasis on theoretical foundations while addressing practical challenges in high-dimensional systems, symmetry-aware learning, and uncertainty quantification. Among his notable honors are: Best Paper Runner Up Award from ICML 2013 EPSRC Advanced Research Fellowship (2006-2011) Edoardo R. Caianiello Award for the Best Italian PhD Thesis on Connectionism (2002) Professor Pontil has served on program committees for major machine learning conferences (COLT, ICML, NeurIPS) and on editorial boards of prestigious journals including Machine Learning Journal, Statistics and Computing, and JMLR. He teaches Advanced Topics in Machine Learning at UCL, with a focus on convex optimization and statistical learning theory.

Nicolás QuesadaView profile

Associate Professor

• Quantum Information
• Quantum Computing
• Quantum Optics
• +7 more

Nicolás Quesada is an Associate Professor in the Department of Engineering Physics at Polytechnique Montréal, where he holds the MEI Chair in Quantum Photonics. He serves as Director of COPL (Centre d'optique, photonique et laser) and is a member of INTRIQ (Institut transdisciplinaire d'informatique quantique). His research program focuses on quantum information, quantum computing, and quantum optics, with particular emphasis on photonic implementations of quantum technologies. Dr. Quesada earned his B.Sc. in Physics from Universidad de Antioquia in 2010, followed by M.Sc. and Ph.D. degrees in Physics from the University of Toronto. During his doctoral studies, he was awarded both Vanier and Stoicheff scholarships. Prior to joining Polytechnique Montréal, he worked at Xanadu Quantum Technologies as lead developer of the Strawberry Fields and The Walrus software libraries, where he led theoretical efforts demonstrating photonic quantum advantage. His research interests span quantum photonics, quantum computing, and quantum optics, with specific focus on Gaussian Boson Sampling, squeezed light generation, non-Gaussian light sources, and quantum benchmarking techniques. His group develops theoretical frameworks and computational tools for next-generation quantum light sources needed for fault-tolerant quantum computers, quantum communication networks, and quantum sensors. His work bridges theoretical quantum information science with practical photonic implementations. Analysis of his recent publications reveals a strong focus on advancing Gaussian Boson Sampling as a platform for quantum advantage, developing mathematical frameworks for quantum optics, and engineering practical photonic quantum devices. His work spans from fundamental quantum optics to applied quantum computing, with increasing emphasis on verification and benchmarking of quantum computational advantage. Dr. Quesada has received notable recognition including the Vanier Canada Graduate Scholarship and the Stoicheff Scholarship during his doctoral studies. His research has attracted significant funding, including a $6 million grant for quantum projects at Polytechnique Montréal announced in January 2025 and involvement in a $1.91 million NSERC quantum sensing project led by Professor Denis Seletskiy. He has supervised two Master's students to completion in 2024: Dalbec-Constant, N. who worked on photon counting from transition-edge sensors, and Zhao, J. who researched optimal pumps for spontaneous parametric down-conversion. His research group collaborates extensively with both academic and industry partners in the quantum technology sector. As Director of COPL, he oversees one of Canada's leading photonics research centers, facilitating interdisciplinary research across quantum optics, classical optics, and laser technologies.