Find Academic Supervisors

Jongguen LeeView profile

Professor

• Combustion Engineering
• Aerospace Propulsion
• Fluid Dynamics
• +3 more

Professor Jongguen Lee is a faculty member at the University of Cincinnati, specializing in combustion and propulsion systems. His research focuses on combustion dynamics in gas turbines, ramjets, and rocket propulsion, with expertise in laser-based diagnostics, supersonic combustion, and combustion control. He collaborates with major industries like GE Aviation, Pratt & Whitney, and NASA. His work addresses challenges in combustion instability, fuel-air mixing, and multi-phase combustion processes. Recent projects include studies on O2-CO2 combustion for carbon capture and satellite data analysis for riverine phosphorus quantification using machine learning. He has secured federal and industry grants totaling over $140,000, including roles as PI in programs like the Aerospace Propulsion Outreach Program (APOP). His publications span journals such as Flow, Turbulence and Combustion and Atomization and Sprays , with a focus on jet dynamics, spray characterization, and combustion diagnostics. Notable collaborations include AFRL-Wright Patterson, NASA-GRC, and DOE NETL. His research bridges theoretical models and practical applications in aerospace propulsion and environmental sustainability.

• Superfluidity
• Condensed Matter Physics
• Quantum Physics
• +3 more

Lev Levitin is a Senior Research Fellow in the Department of Physics at Royal Holloway, University of London. His work focuses on superfluidity, quantum fluids, and low-temperature physics. He has contributed to major projects like SquBa (Quantum fluid Bath noise reduction) and the European Microkelvin Platform (EMP). Recent research includes studies on chiral superfluid helium-3, cosmological phase transitions, and nanofluidic confinement effects. Key projects include: SquBa (2024-2027) : Silencing quantum circuit noise using quantum fluids. EMP (2019-2023) : Collaborative European platform for ultra-low temperature physics. Levitin’s datasets include groundbreaking work on superfluid 3He surface states (2021) and quasi-two-dimensional chiral superfluidity (2024). His research has been featured in over 30 news outlets and widely shared on academic platforms like Mendeley.

Kevin W. CasselView profile

Professor

• Thermo-Fluid Sciences
• Computational Fluid Dynamics
• Boundary Layer Theory
• +6 more

Kevin W. Cassel is a Professor of Mechanical and Aerospace Engineering and Applied Mathematics at Illinois Institute of Technology, and serves as Vice Provost for Academic Affairs. He holds dual appointments in the Armour College of Engineering and the College of Computing. Education: Ph.D. Mechanical Engineering (Lehigh University, 1993), M.S. Mechanical Engineering (Lehigh University, 1990), B.S. Mechanical Engineering (Messiah College, 1988). Research focuses on analytical and computational solutions to partial differential equations, numerical algorithms for fluid flows, boundary-layer instabilities, and bio-fluid dynamics. His work spans unsteady separation, supersonic/hypersonic flows, and heat transfer in complex systems. He has contributed to advancements in physics-informed machine learning for fluid mechanics and vascular hemodynamics modeling. Major awards include Fellow of the American Society of Mechanical Engineers (2020), MMAE Excellence in Teaching Award (2015), and Army Research Office Young Investigator Award (1998-2001). His research has been supported by grants from federal agencies and industry. Publications include two textbooks: Matrix, Numerical, and Optimization Methods in Science and Engineering (2021) and Variational Methods with Applications in Science and Engineering (2013). He actively collaborates on interdisciplinary projects in computational fluid dynamics, bioengineering, and mathematical modeling.

Yogendra P. ChaubeyView profile

Professor

• Sampling
• Distribution Theory
• Survival Analysis
• +3 more

Dr. Yogendra P. Chaubey is a Professor in the Department of Mathematics and Statistics at Concordia University, Montréal, Canada. Holding a Ph.D. from the University of Rochester (1977), his research focuses on statistical methodology with emphasis on sampling theory, distribution modeling, and survival analysis. Education: Ph.D., University of Rochester (1977) His work spans nonparametric density estimation for circular and non-negative data, wavelet-based noise reduction in biological imaging, entropy estimation, left-censored spatial modeling (e.g., arsenic contamination), and inverse Gaussian distributions. Recent collaborations include applications in protein classification and public health. Dr. Chaubey has published extensively on statistical theory and methodology, including corrections and extensions to classical estimators. His teaching includes advanced courses in sample survey theory and applications.

• Machine Learning
• Theoretical Computer Science
• Algorithms
• +3 more

Christos Tzamos is an Associate Professor at the National and Kapodistrian University of Athens. His research focuses on the intersection of machine learning, theoretical computer science, and algorithmic game theory. He has made significant contributions to topics like online learning, optimization under noise, and mechanism design. His work often bridges foundational theory with practical algorithmic solutions. Position: Associate Professor Affiliation: National and Kapodistrian University of Athens Key research interests include: Machine Learning (e.g., robust classification, active learning) Algorithms (e.g., optimization, approximation algorithms) Computational Economics (e.g., auction design, Pandora’s box problems) His most recent articles (2023–2025) explore advanced topics such as statistical query hardness, noise-robust learning frameworks, and optimized mechanisms for multi-item markets. Notable trends in his work include developing algorithms resilient to adversarial noise and designing efficient learning strategies under constraints. No scientific awards are explicitly listed in the provided texts, though his prolific publication record reflects strong academic standing. Labs, teams, or collaborations are not detailed here, but his research often involves interdisciplinary collaborations with leading institutions.

Luke DosiekView profile

Professor

• Power Systems
• Signal Processing
• Synchrophasor Technology
• +3 more

Luke Dosiek is a Professor in the Department of Electrical and Computer Engineering at Union College. He holds a Ph.D. from the University of Wyoming, with previous positions including Research Engineer at Assured Information Security and postdoctoral research at Wyoming. His research focuses on power system dynamics, signal processing applications in energy grids, and innovative educational methods for engineering. Key interests include synchrophasor-based detection of electromechanical modes and forced oscillations, low-cost measurement units, and auditory interfaces for grid monitoring. His teaching encompasses alternative energy, electromagnetics, circuits, and power systems. Research methodologies include time-series analysis, algorithm development, and experimental validation across diverse grid scenarios. Article analysis reveals consistent themes: advanced algorithms for oscillation detection, educational pedagogy in power engineering, and signal processing innovations. Temporal trends show increasing focus on real-time monitoring techniques and grid resilience. Awards include the 2021 Curtis W. McGraw Research Award. Professional experience spans industry research and academic roles across multiple institutions. Laboratory work includes developing synchrophasor applications and low-cost measurement tools. Future directions involve integrating machine learning for grid anomaly prediction and expanding educational outreach.

• Material Flow Management
• Automated Transport Systems
• Warehousing
• +2 more

Dr. Anna Lewandowska-Ciszek serves as Assistant Professor at the Department of Logistics, Poznań University of Economics and Business. Her expertise encompasses material flow optimization, automated internal transport systems, and warehouse management within production environments. Key research areas include: Lean Industry 4.0 implementations Complexity analysis in industrial automation Warehouse process optimization PRINCE2 project management applications Recent publications highlight her focus on resilience engineering through process simulation, lean-automation integration, and distribution center operations, with theoretical frameworks frequently validated through industrial case studies.

Nahid JamshidiView profile

Researcher

• Stochastic Differential Equations
• Numerical Analysis
• Fractional Brownian Motion
• +3 more

Nahid Jamshidi is a Researcher at the Institute of Mathematics within the Faculty of Natural Sciences II (Chemistry, Physics and Mathematics) at Martin Luther University Halle-Wittenberg, specializing in applied stochastics with emphasis on numerical methods for stochastic systems. Her research focuses on: Stochastic Differential Equations driven by fractional Brownian motion Numerical analysis of stiff and unstable systems Model order reduction techniques including Gramian-based and sampling methods Convergence and stability analysis of Euler, Milstein, and exponential integrators Computational challenges in high-dimensional stochastic modeling Long-range dependence phenomena in fractional noise processes Analysis of her 7 publications (2017-2024) reveals consistent advancement in numerical schemes for fractional SDEs, with recent work (2023-2024) addressing exponential integrators for stiff systems and empirical Gramian applications. Her research bridges theoretical stochastic analysis with practical computational solutions for complex noise-driven dynamics. No scientific awards are documented in available sources. The provided information contains no records of student supervision, grant funding, laboratory affiliations, or research team memberships.

• Nonlinear Systems and Control Theory
• Passivity-Based Control
• Sampled-Data Systems
• +4 more

Alessio Moreschini is a Research Associate at the Department of Electrical and Electronic Engineering, Imperial College London, within the Faculty of Engineering. He holds a dual Ph.D. in Automatica (University of Rome "La Sapienza") and Systems and Control (Université Paris-Saclay), both awarded in 2021. His research focuses on nonlinear systems and control theory, with expertise in passivity-based control, sampled-data systems, and model order reduction. Moreschini is affiliated with the Control and Power Research Group at Imperial College. He previously served as a Postdoctoral Fellow at the University of Rome from 2021–2022. His academic roles include Associate Editorships for Automatica and the EUCA Conference Editorial Board, as well as membership in the IEEE CSS Technical Committee on Nonlinear Systems and Control, and the IFAC Technical Committee on Nonlinear Control Systems. Research interests span advanced control methodologies, including passivity theory, model reduction techniques, and their applications to electrical networks and robotics. His recent work emphasizes data-driven approaches, nonlinear system interpolation, and stabilization strategies for sampled-data systems.

• Control Systems
• Model Reduction
• Nonlinear Dynamics
• +3 more

Giordano Scarciotti is a Senior Lecturer in the Department of Electrical and Electronic Engineering at Imperial College London, within the Faculty of Engineering. His research focuses on control systems, model reduction, and nonlinear dynamics, with applications in energy systems such as wave energy converters. He leads the Control and Power Research Group and has affiliations with organizations like EPSRC and MINES ParisTech. Scarciotti has received notable awards, including the IEEE Transactions on Control Systems Technology Outstanding Paper Award and the President's Award for Excellence in Teaching Innovation. His work emphasizes data-driven methods and stochastic control, addressing challenges in large-scale systems like wind farms and differential-algebraic systems. Research Interests: Nonlinear and stochastic control theory Model reduction techniques (moment matching, data-driven approaches) Energy systems optimization (wave energy, wind farms) Control of complex systems with constraints Awards: IEEE Transactions on Control Systems Technology Outstanding Paper Award IET Control & Automation PhD Award President's Award for Excellence in Teaching Innovation Grants & Collaborations: EPSRC-funded research on model reduction Affiliations with MINES ParisTech and the Italian Embassy in London Scarciotti's recent publications emphasize innovative methods for system modeling and control, including energy-maximizing strategies for wave energy systems and hybrid observer-based approaches for output regulation.

• Algorithmic Fairness
• Machine Learning
• Computational Social Choice
• +3 more

Benjamin Fish is a Professor in the Department of Computer Science and Engineering (CSE), focusing on fairness in algorithms, computational social choice, and theoretical computer science. His research addresses issues of equity in hiring markets, bias in machine learning, and ethical implications of technology. He is actively involved in mentoring PhD students, emphasizing personalized advising, regular one-on-one meetings, and fostering independence in research. Research Interests: Dr. Fish explores algorithmic fairness, graph neural networks, and the ethical design of computational systems. He investigates how social dynamics and institutional structures impact algorithmic outcomes, particularly in contexts like hiring and data-driven markets. His work often bridges theoretical analysis with practical applications in policy and technology governance. Education and Mentorship: While his formal education details are not explicitly listed, his mentorship philosophy prioritizes student autonomy and growth. Weekly meetings and flexible group sessions focus on research progress, writing, and professional development. He encourages internships, conference participation (with funding support), and teaching opportunities as part of a well-rounded academic experience. Advising and Grants: Students are expected to take ownership of their research projects, with authorship determined by contribution. Authorship order typically places student leads as first authors and the advisor as last. Regular feedback is provided through weekly meetings and annual reviews, balancing progress tracking with student well-being. Conferences and Funding: Conference attendance is supported for paper authors; additional travel funds are available for one annual conference per student. Funding depends on project grants and workshop submissions.

Christophe DuwigView profile

Professor

• Process Simulation
• Fluid Mechanics
• Heat Transfer
• +7 more

Christophe Duwig is a Professor at the Department of Chemical Engineering, KTH Royal Institute of Technology. He serves as Vice-Director of the KTH Energy Platform and coordinates strategic initiatives like the KTH Nuclear Next and Battery Initiative. His research focuses on process simulation, fluid mechanics, heat transfer, and clean energy technologies. He leads projects addressing carbon capture, renewable heat systems, and clean air solutions through collaborations with institutions like Stockholm University and RISE Research Institutes of Sweden. Research Interests: His work integrates high-fidelity computational fluid dynamics (CFD), including LES and CFD simulations of reacting flows, with advanced post-processing tools like machine learning and proper orthogonal decomposition. Key areas include CO2 capture, hydrogen combustion optimization, and waste heat recovery. He emphasizes translating research into practical solutions for decarbonization and clean air through initiatives like C3Air®. Publications: Recent articles highlight innovations in CO2 capture efficiency, hydrogen-fueled combustion dynamics, and heat transfer optimization in electronic cooling systems. His work often bridges fundamental fluid mechanics with industrial applications, addressing global challenges in energy sustainability and climate action. Grants & Leadership: Coordinates multi-disciplinary research efforts under SDG 7 (Clean Energy) and SDG 13 (Climate Action). Leads teams in projects such as C3Air® and the KTH Climate Action Centre, fostering international collaborations to tackle air pollution and carbon removal. Supervises PhD and MSc students in computational engineering and sustainable technologies. Labs & Teams: Active in the Division of Process Technology and KTH’s Energy and Environmental initiatives. His lab develops novel heat exchangers, combustion models, and smart energy management systems for buildings and industrial processes.

Isaac SkogView profile

Associate Professor

• Underwater Surveillance
• Signal Processing
• Navigation Systems
• +5 more

Isaac Skog is an Associate Professor in Communication Systems at KTH Royal Institute of Technology, part of the Digital Futures Faculty. He also holds adjunct positions at Linköping University (Automatic Control) and the FOI Swedish Defence Research Agency. His research focuses on underwater surveillance, signal processing, navigation systems, and sensor fusion, with a particular emphasis on autonomous systems and acoustic environments. Education: BSc and MSc in Electrical Engineering, KTH Royal Institute of Technology (2003, 2005) PhD in Signal Processing, KTH Royal Institute of Technology (2010) Research Interests: Underwater acoustic surveillance and tracking Navigation systems using magnetic fields and inertial sensors Autonomous underwater vehicles and multi-agent systems Sensor calibration and fusion techniques Machine learning for sensor data analysis Recent Projects: COAST Project: Complex Acoustic Surveillance and Tracking Joint Sensing, Localization, and Communication for Next-Gen Autonomous Underwater Systems (WASP-funded) Tensor-Field Based Localization Electromagnetic Navigation for Smaller Unmanned Underwater Vehicles Grants & Collaborations: Funded by CENIIT, WASP Sweden, Swedish Research Council, Vinnova, and industry partners like Saab Dynamics. Active collaborations with FOI, Lund University, and Indian Institute of Science. Technical Demonstrators: Lyra platform for elevator condition monitoring OpenShoe experimental platform for foot-mounted inertial navigation Tactical Locator (TOR) for first-responder tracking Movelo AB spin-off for smartphone-based traffic monitoring

Fraida FundView profile

Assistant Professor

• Networking
• Telecommunications
• Wireless Communication
• +7 more

Fraida Fund is a Research Assistant Professor at the NYU Tandon School of Engineering, specializing in the Electrical and Computer Engineering Department. She is affiliated with the Center for Advanced Technology in Telecommunications (CATT) and NYU WIRELESS, which focus on 6G and mmWave technologies. Her research explores low-latency networking, congestion control, wireless systems, and reproducibility in computer science education. She teaches courses on machine learning systems, networking protocols, and computer engineering design. Her work emphasizes practical applications of wireless and edge computing, particularly in agriculture and connected vehicles. Recent studies include evaluating latency in mmWave networks and analyzing the adoption of BBR and L4S congestion control protocols. Fund has contributed to open-source platforms like PrairieLearn for algorithmic question generation in education. She was recognized by AFAR for her academic achievements. Fund’s research integrates economic analysis with engineering, such as modeling cellular infrastructure sharing and pricing strategies for video delivery. She actively uses public testbeds for reproducible experiments and advocates for improving reproducibility in computer science curricula. Her interdisciplinary approach bridges theoretical research with real-world deployment challenges in telecommunications.

Herschel KnappView profile

Associate Clinical Professor

• HIV Testing Implementation
• Telehealth Consultations
• Evidence-Based Nursing Practices
• +5 more

Herschel Knapp is a Clinical Associate Professor in the Department of Social Work at Yeshiva University. He holds a Ph.D. in Social Welfare from UCLA (2001), M.S.S.W. from the University of Texas at Austin (1995), and B.A. in Psychology from California State University, Northridge (1988). His clinical work focuses on psychosocial services in ER, ICU, Oncology, and Code Blue Team settings. Research emphasizes HIV testing implementation, telehealth innovations, and evidence-based nursing practices. He teaches statistics, research methods, and clinical communication at both MSW and doctoral levels. Knapp has published extensively on HIV testing protocols, healthcare quality improvement, and educational interventions. He chairs the Student Appeals Committee and serves on the D.S.W. Committee. His work includes developing the ECHO Model for VA healthcare consultations and evaluating Meducation® for medication adherence. He has contributed to over 40 peer-reviewed articles and authored multiple textbooks on statistics and therapeutic communication. Key projects include nurse-initiated HIV testing in VA settings, human trafficking clinician training, and transgender veteran care curricula. His research spans healthcare technology evaluation, clinical assessment tools, and interdisciplinary education programs. Knapp’s work balances academic contributions with direct clinical impact, addressing critical gaps in healthcare access and quality.