جست‌وجوی استاد و پژوهشگر

Petros Voulgarisمشاهده پروفایل

استاد

• Control Systems
• Autonomous Systems
• Cybersecurity
• +۵ مورد دیگر

Petros Voulgaris is the Victor LaMar Lockhart Professor and Chair of the Mechanical Engineering Department at the University of Nevada, Reno (UNR), where he also directs the Founding Aerospace Program. He is affiliated with the College of Engineering and leads the Learning Autonomy and Control Systems Laboratory. His work focuses on advanced control methodologies for engineering systems, including autonomous vehicles, cyber-physical systems, and resilient networks. Research Interests: Optimal, robust, and distributed control; networked control systems; autonomous systems cybersecurity; and applications in aerospace, robotics, and power systems. His lab explores cutting-edge solutions for challenges like adversarial attacks on autonomous systems and GPS-denied navigation. Prospective Students: Openings for Ph.D. candidates and postdocs with control systems or decision-making expertise. Contact via pvoulgaris@unr.edu for application details. Labs: Learning Autonomy and Control Systems Laboratory Contact: PE Building 204C | (775) 682-5725

Olivier Canévetمشاهده پروفایل

مدرس

• Computer Vision
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Olivier Canévet is a Lecturer at EPFL, affiliated with both the School of Engineering (STI) and the School of Life Sciences (VPA-AVP-DLE) divisions. He holds a dual role as a Research Engineer at the Idiap Research Institute and serves as a Lecturer in the Department of Electrical Engineering (IEM) and the EDEE-ENS teaching unit. His primary affiliations include the Learning and Information Systems Laboratory (LIDIAP) at EPFL. Education: PhD in Electrical Engineering from EPFL (2012–2016), supervised by Dr. François Fleuret. Engineering diploma from Télécom Bretagne (2007–2012). Additional experiences include a CNES internship on satellite imagery and CERN projects on Invenio ranking systems. He also spent a year managing geophysical observatories in the French Southern and Antarctic Lands. Research Interests: Focuses on Computer Vision, Machine Learning, and Deep Learning applications in human-robot interaction, security systems, and real-time perception. Specializes in depth-based networks for human pose estimation, multi-person tracking, and socially intelligent robotic systems. Article Trends: Recent work emphasizes real-time CNN architectures for depth-based human pose estimation, multi-party human-robot interaction datasets (MuMMER), and security systems leveraging depth maps (UNICITY database). Prior contributions include efficient sample mining techniques and domain adaptation methods. Grants & Funding: His PhD was funded by the Swiss National Science Foundation (DASH project). Current research benefits from EPFL's interdisciplinary infrastructure and Idiap's resources in machine learning and robotics. Labs & Teams: Leads projects at LIDIAP lab (EPFL) focusing on computer vision applications, collaborates with Idiap on security systems, and contributes to teaching initiatives in the EDEE-ENS unit.

• Causal Inference
• Statistical Modeling
• Machine Learning
• +۳ مورد دیگر

M.Sc. David Strieder is a researcher at the Technical University of Munich (TUM), affiliated with the Chair of Mathematical Statistics led by Prof. Drton. His work focuses on causal inference, particularly addressing structure uncertainty in linear causal models. He develops methodologies to rigorously account for uncertainties in causal discovery through frameworks like dual likelihood and test inversion. His research integrates statistical theory with machine learning to improve confidence in causal effect estimation. David's academic activities include contributions to the TUM's Department of Mathematics, where he collaborates on projects related to causal structure learning and uncertainty quantification. His publications address foundational challenges in causal discovery, including the combination of structure learning with effect inference. He maintains an active presence in academic conferences, presenting at events such as the Conference on Uncertainty in Artificial Intelligence and the Conference on Causal Learning and Reasoning. Key contributions include advancing dual likelihood approaches for causal inference under structural ambiguity and refining statistical testing techniques for linear models. His work emphasizes practical implementations that balance theoretical rigor with algorithmic efficiency.

• Robotics
• Unmanned Aerial Vehicles (UAVs)
• Control Systems
• +۱۲ مورد دیگر

Markus Ryll is a Professor at the Technical University of Munich (TUM) , affiliated with the TUM School of Engineering and Design . His research focuses on autonomous aerial systems, particularly in the fields of robotics, UAVs, and control systems. University: Technical University of Munich School: TUM School of Engineering and Design Rank: Professor Ryll’s work spans motion planning, SLAM (Simultaneous Localization and Mapping), geometric control, and energy-efficient trajectory generation. He has pioneered advancements in dual quaternion control, aerial manipulation with cable-suspended loads, and reactive navigation for UAVs in dynamic environments. His recent publications highlight trends in differentiable motion planning , neural MPC (Model Predictive Control) , and collision-free trajectory generation . These studies emphasize real-time optimization, geometric modeling, and sensor fusion for agile robotic systems. Ryll’s research also integrates machine learning with classical control frameworks, enabling data-driven optimization for quadrotors and multirotor platforms. His work includes hardware/software architectures, morphing UAV designs, and fail-safe robustness in rotor failure scenarios. While no specific awards or student advisories are listed here, Ryll’s contributions to autonomous aerial systems and compliant rover navigation underscore his leadership in robotics and aerospace engineering.

• Combustion
• Alternative Fuels
• Internal Combustion Engines
• +۲ مورد دیگر

Dr. Balazs Alexis Ihracska is a Senior Teaching Fellow in the Department of Mechanical Engineering within Imperial College London's Faculty of Engineering. He is based at the City and Guilds Building on the South Kensington Campus, with contact details including work phone (+44 20 7594 7060) and institutional email. His primary research explores combustion systems and sustainable energy solutions, with specialized interests in: Experimental characterization of alternative fuels (hydrogen, emulsions, biofuels) Optical diagnostics for engine combustion processes Fluid dynamics of fuel injection and atomization Emission reduction strategies in internal combustion engines Advanced metrology for mechanical systems Publications from 2011-2017 demonstrate consistent focus on combustion optimization using optical techniques. Recent work emphasizes hydraulic behavior of fuel emulsions and high-pressure opto-mechanical systems, while earlier studies established foundations in flame propagation analysis and dual-fuel engine performance.

Negareh Ghasemiمشاهده پروفایل

پژوهشگر ارشد

• Power Electronics
• Pulsed Power Systems
• Ultrasound Technology
• +۳ مورد دیگر

Dr. Negareh Ghasemi is an Adjunct Research Fellow at the University of Queensland's School of Electrical Engineering and Computer Science. She holds a PhD in Power Electronics from Queensland University of Technology (2013), where she also earned her BSc and MSc degrees in Electronic and Electrical Engineering (2003 and 2007). Her research focuses on Power Electronics and Control, Pulsed Power Systems, Ultrasound Technology, and their applications in food processing, environmental engineering, and structural health monitoring. She is an active member of IEEE Women in Engineering and serves on the editorial board of the International Journal of Power Electronics . Dr. Ghasemi’s work spans pulsed electric field (PEF) technologies for food sterilization, nanosecond pulse systems for microbial inactivation, and ultrasound-based wastewater treatment. Her contributions include advancements in converter design for piezoelectric transducers and control strategies for power electronics systems. She has collaborated internationally with institutions in Japan and Germany and holds the 2013 Outstanding Thesis Award from QUT. Key research trends in her articles include optimizing PEF for food safety, developing eco-friendly pollution removal methods, and enhancing power converter stability. Her work bridges electrical engineering with interdisciplinary applications in agriculture, medicine, and environmental science. Awards include the 2013 Outstanding Thesis Award, highlighting her impactful contributions to power electronics and food processing. Dr. Ghasemi’s research also addresses structural health monitoring via ultrasonic techniques and educational strategies for engineering pedagogy. Her projects, such as the Rio Tinto kimberlite dewatering report, demonstrate industrial collaboration. She actively publishes across journals like Physics of Life Reviews and IEEE Transactions , contributing to both theoretical and applied engineering domains.

Jane Hugginsمشاهده پروفایل

عضو هیئت علمی

• Neural Engineering
• Rehabilitation Engineering
• Brain-Computer Interfaces (BCIs)
• +۶ مورد دیگر

Jane Huggins, Ph.D., is a Research Associate Professor at the University of Michigan, holding dual appointments in the Department of Physical Medicine & Rehabilitation and the Department of Biomedical Engineering. Her work focuses on developing EEG-based brain-computer interfaces (BCIs) as clinical tools for individuals with physical impairments. Key research areas include improving BCI usability, addressing signal processing challenges, and overcoming barriers to in-home BCI implementation. She leads the Direct Brain Interface Lab and has collaborated on numerous grants, including projects funded by the NIH, NSF, and industry partners like General Motors. Her research emphasizes practical applications of BCIs for communication, cognitive assessment, and assistive technology. Notable projects include optimizing BCI systems for users with cerebral palsy and spinal cord injuries, enhancing BCI-AAC system integration, and advancing user-centered design principles. Dr. Huggins has also contributed to ethical frameworks for neurotechnology and participated in international BCI conferences. Recent scholarly activities include Bayesian inference methods for GLASS BCI systems and studies on P300-based speller performance. She has mentored undergraduate and graduate researchers in areas like BCI calibration, signal processing, and clinical trial design. Her lab’s work aligns with broader goals of improving accessibility and quality of life for individuals with severe physical disabilities. Grants and collaborations highlight her interdisciplinary approach, spanning engineering, medicine, and ethics. Ongoing projects explore inclusive autonomous vehicle design for people with disabilities and regulatory pathways for BCI medical devices. Dr. Huggins’ contributions bridge cutting-edge research with real-world clinical needs, fostering innovations that translate into tangible benefits for impaired populations.

• Computer Vision
• 3D Reconstruction
• Neural Rendering
• +۵ مورد دیگر

Dr. Miaomiao Liu is a Research Fellow at the School of Computing, The Australian National University. Her research focuses on computer vision, 3D reconstruction, and neural rendering, with applications in robotics, autonomous systems, and renewable energy forecasting. She leads multiple projects including Next-Generation Aviation Safety Net Air Traffic Management, Machine Vision Techniques for Solar Power Forecasting, and 3D Vision Geometric Optimization in Deep Learning. Her work integrates cutting-edge techniques such as neural radiance fields, depth estimation, and self-supervised learning to address challenges in dynamic scene reconstruction, motion forecasting, and image deblurring. She has pioneered methods for mining supervision signals in dynamic regions and developing language-driven deblurring networks. Key Projects: Aviation safety systems, solar irradiance prediction, and geometric optimization in deep learning Research Themes: 3D scene understanding, human motion prediction, and neural rendering Technical Expertise: Neural networks, multi-view stereo, and physics-based modeling Dr. Liu's research has been published in top-tier venues like CVPR and IEEE conferences, with over 2,450 citations. While not explicitly listed as part of a lab, her work demonstrates strong collaboration with industry partners such as CSIRO and aerospace stakeholders. She actively supervises research students in areas like 3D vision and energy systems.

Hanno Drewsمشاهده پروفایل

استاد

• Controlling
• Corporate Finance
• Management Accounting
• +۴ مورد دیگر

Prof. Dr. Hanno Drews is a Professor of Controlling at the West Coast University of Applied Sciences in Heide, holding leadership roles as Head of Controlling Studies and Vice Dean for Teaching in the Faculty of Economics. He has led the Business Administration program and manages academic affairs for all Bachelor’s and Master’s programs. His research focuses on decision-making psychology in controlling, bias mitigation in corporate reporting, and strategic portfolio models. He co-leads the AKC (Working Group on Controlling Professorships at Universities) with Prof. Dr. Britta Rathje. Educated at Georg-August University Göttingen and UC Santa Barbara, Drews combines academic expertise with industry experience from Procter & Gamble and research at the University of Trier. His doctoral work on cooperation controlling earned the Austrian Controller Prize 2000. He teaches controlling principles, operational and strategic controlling, and specialized modules across multiple business programs. Key research contributions address KPI design, portfolio models, and ethical reporting practices. His recent work critiques traditional frameworks like the BCG Matrix and emphasizes behavioral aspects in financial decision-making. He actively promotes controlling education through academic leadership and interdisciplinary initiatives. Positions: Dean of Economics Faculty, Controlling Program Head, AKC Spokesperson Education: PhD (University of Trier), Dual Degree (Göttingen + UC Santa Barbara) Research Focus: Human decision dynamics, reporting ethics, strategic models, and bias analysis Awards: Austrian Controller Prize 2000 for dissertation Teaching: Excel applications, TOPSIM simulations, green energy financing, and business psychology modules

Jessica Kleissمشاهده پروفایل

دانشیار

• Atmospheric Science
• Oceanography
• Image Processing
• +۵ مورد دیگر

Jessica Kleiss is an Associate Professor of Environmental Studies and Director of the Environmental Studies Program at Lewis & Clark College. Her research focuses on fluid dynamics in the ocean and atmosphere, particularly using image processing techniques to study cloud geometry and wave breaking. She holds a PhD in Physical Oceanography from Scripps Institution of Oceanography (2009) and dual BS degrees in Mathematics and Earth, Atmospheric, and Planetary Sciences from MIT (2000). Her work combines remote sensing, computational analysis, and field observations to inform climate models. Recent projects include estimating 3D geometry of shallow cumulus clouds using ground-based sensors and analyzing wave dynamics in extreme environments like the Gulf of Tehuantepec. She has also explored green roof runoff quality in urban settings. Teaching includes courses on climate science, oceanography, and spatial analysis in Earth systems. Her research methods span oceanographic instrumentation, atmospheric imaging, and interdisciplinary environmental problem-solving. Professional experience includes postdoctoral work at the University of Washington’s Joint Institute for the Study of the Atmosphere and Ocean (JISAO). Current research focuses on validating climate models through cloud observations and advancing automated cloud classification techniques.

Pawel Smietankaمشاهده پروفایل

استاد پژوهشی

• Microeconomics
• Expectations and uncertainty
• Corporate finance

Pawel Smietanka is a Research Professor at the Deutsche Bundesbank's Research Centre, previously affiliated with the Bank of England. His research focuses on economic uncertainty, corporate finance, and microeconomic expectations, with particular emphasis on analyzing firm-level data through initiatives like the Decision Maker Panel (DMP). This monthly survey, developed in collaboration with Stanford University and the University of Nottingham, tracks business expectations and uncertainty in real-time, providing critical insights into UK economic dynamics. Key affiliations include the Bank of England's Structural Economics Division and the Deutsche Bundesbank Research Centre. His work bridges macroeconomic theory with empirical analysis, addressing topics such as Brexit's impact on businesses, pandemic-related productivity shifts, and the role of uncertainty in investment and cash-holding decisions. Smietanka’s contributions to the DMP have established it as a leading source of timely business data, informing policy discussions on inflation, supply chain disruptions, and sectoral disparities during crises like the 2020 pandemic. Research interests span corporate finance, expectations modeling, and structural economic issues. He frequently collaborates on cross-institutional studies, integrating firm-level surveys with broader macroeconomic trends. While no formal awards are listed, his publications in top journals like the Journal of Public Economics and Review of Economics and Statistics underscore his academic influence. Smietanka’s work emphasizes data-driven policy solutions, reflecting his dual focus on academic rigor and real-world applicability.

Somayeh Mashayekhiمشاهده پروفایل

دانشیار

• Fractional Calculus
• Fractal Media
• Population Genetics
• +۵ مورد دیگر

Somayeh Mashayekhi is an Associate Professor in the Department of Mathematics at Kennesaw State University (KSU) and a Courtesy Assistant Professor at Florida State University (FSU) in the Department of Scientific Computing. She holds dual PhDs in Mathematical Sciences (Mississippi State University, 2015) and Applied Mathematics (Al-Zahra University, Iran, 2013). Her research focuses on computational methods, fractional calculus, fractal media viscoelasticity, population genetics, and optimal control. She has conducted postdoctoral research at FSU (2015–2019) and secured grants totaling over $127,000 from NSF and KSU. Education: PhD in Mathematical Sciences (Mississippi State), PhD in Applied Mathematics (Al-Zahra University), MSc in Applied Mathematics (Al-Zahra University). Research highlights include the fractional coalescent framework in population genetics, experimental validation of fractional viscoelastic models in polymers, and development of hybrid functions for solving fractional differential equations. She teaches advanced mathematics courses at KSU and mentors undergraduates in interdisciplinary projects.

• Control Theory
• Robust Control
• Nonlinear Control Systems
• +۳ مورد دیگر

Richard Seeber is a Researcher at the Institute of Control and Automation (Institut für Regelungstechnik und Automation) at TU Graz. His academic titles include Privatdozent (Priv.-Doz.), Diplom-Ingenieur (Dipl.-Ing.), Doctor of Engineering (Dr.techn.), and Bachelor of Science (BSc). His work focuses on advanced control theory, nonlinear systems, and observer design. He holds a teaching authorization in system dynamics and control theory, reflecting his dual role in research and education. Research interests include robust exact differentiators, sliding mode control, observer design for linear and nonlinear systems, and applications in thermal management and energy systems. He has contributed to methodologies addressing actuator saturation, discretization challenges, and real-time control implementation. His recent work emphasizes predefined-time convergence algorithms and stability analysis under bounded noise or disturbances. Selected projects involve heater modeling for fuel cell stacks, frequency converter nonlinearity compensation, and control strategies for biomass furnaces. His contributions are often applied to industrial systems requiring precise control under uncertainty, such as gas engine power plants and transient operating conditions. He collaborates within TU Graz's Institute of Control and Automation, contributing to both theoretical advancements and practical tool development. His research portal (https://irt.tugraz.at/) hosts publications and tools related to robust control methodologies.

Tim Davidsonمشاهده پروفایل

استاد

• Signal Processing
• Communications
• Optimization
• +۳ مورد دیگر

Tim Davidson is Professor and Chair of Electrical & Computer Engineering at McMaster University's Faculty of Engineering. His research focuses on signal processing for communications and networking, optimization, learning and control, with applications to integrated sensing-communication systems and radar target characterization. He received his B.Eng. from the University of Western Australia and D.Phil. from the University of Oxford. His honors include IEEE Fellow (2015), Canada Research Chair (2004-2014), and IEEE Signal Processing Society Best Paper Award. Research areas include mobile edge computing resource allocation, robust MIMO transceiver design, and radar-communication co-design. Recent publications focus on dual-function radar-communication systems and resonance-based radar target classification. Davidson has served as Chair of IEEE's Technical Committee on Signal Processing for Communications and Networking and as editor for multiple IEEE transactions. He teaches courses on Engineering Optimization (ECE 710) and Control Systems (EE 3CL4).

Luise Blankمشاهده پروفایل

استاد

• Numerical Optimization
• Partial Differential Equations
• Optimal Control
• +۴ مورد دیگر

Prof. Dr. Luise Blank is a faculty member at the Department of Mathematics, University of Regensburg, within the Faculty of Mathematics. She holds the academic rank of Professor. Her research focuses on numerical optimization with partial differential equations (PDEs), optimal control, iterative solvers for linear systems, and preconditioning techniques using wavelets and Schur complement methods. She is involved in the DFG-Graduiertenkolleg 2339 (GRK 2339) on Interfaces, Complex Structures, and Singular Limits since 2018. Education and Background: Habilitation thesis: 'Multiscale Concepts in State Estimation' (2003), University of Regensburg PhD thesis: 'Stabilitätsanalyse der Kollokationsmethode für Volterra-Integralgleichungen mit schwach singulärem Kern' (1991), University of Bonn Diploma thesis: 'Kollokations-Approximation mit nichtpolynomialen Splines für Lösungen von Volterra-Integro-Differentialgleichungen mit schwach singulärem Kern' (1987), University of Bonn Research Interests: Numerical optimization with PDEs Optimal control Iterative solvers and preconditioning techniques Structural topology optimization using phase-field models Teaching: Current courses include Optimization II, Seminars on ongoing final theses, and participation in the Oberseminar Analysis and IntComSin Colloquium. Past courses span numerical mathematics, optimal control, wavelets, and calculus. Recent Workshops/Events: Organized the Workshop: Women in Optimization 2024 in Erlangen (April 2024) Contributed to conferences on inverse problems, real-time optimization, and process monitoring