جست‌وجوی استاد و پژوهشگر

Juergen Dingelمشاهده پروفایل

استاد

• Software Engineering
• Model-Driven Engineering
• Formal Methods
• +۷ مورد دیگر

Juergen Dingel is a Professor in the School of Computing at Queen's University, Canada. He joined the faculty in 2000 and holds a PhD in Computer Science from Carnegie Mellon University (1999). His research focuses on software modeling, model-driven engineering, formal methods, and formal verification, with applications in real-time systems and embedded systems. He leads the Modeling and Analysis in Software Engineering (MASE) research group. Education: PhD in Computer Science, Carnegie Mellon University (1999) M.Sc. in Pure and Applied Logic, Berlin University of Technology (1994) M.Sc. in Computer Science, Berlin University of Technology (1992) Research Interests: Model-driven engineering and transformation Formal specification and verification Automated testing and debugging Real-time and embedded systems Service composition and distributed systems His work emphasizes practical tools like Papyrus-RT and MDebugger , integrating formal methods into software development. Grants & Collaborations: Funded by NSERC, OCE, and industry partners (IBM, GM, Ericsson) Focus on automotive systems, IoT, and safety-critical applications Service: Editorial board member for SoSyM , STTT , and JOT Former chair of the MODELS Steering Committee (2016–2018) PC co-chair for MODELS 2014 and FMOODS/FORTE 2011 Labs & Teams: Leads the MASE group, which develops open-source tools for model-driven engineering. Collaborates with industry on automotive and IoT projects.

Justin Wanمشاهده پروفایل

استاد

• Scientific Computing
• Computer Graphics Simulation
• Medical Image Processing
• +۴ مورد دیگر

Justin Wan is a Professor in the Department of Computer Science at the University of Waterloo. His research focuses on scientific computing, medical image processing, computational finance, and machine learning. He holds a Ph.D. from UCLA (1998), an M.A. from UCLA (1995), and a B.Sc. from the Chinese University of Hong Kong (1992). Wan’s work bridges numerical methods, optimization, and deep learning, with applications in financial modeling, medical imaging, and fluid dynamics. His research interests include advanced techniques in scientific computing (e.g., multigrid methods), computer graphics simulation, and medical image enhancement (e.g., CT scan artifact reduction). He has pioneered applications of machine learning to computational finance, including option pricing and hedging using deep neural networks and GANs. His recent work explores denoising diffusion models and multi-agent systems for optimal execution in finance. Publications span topics like volatility surface computation, optimal mass transport for image registration, and parallel solvers for fluid dynamics. His methods address challenges in high-dimensional problems, robust numerical valuation, and scalable algorithms for large datasets. Wan collaborates across disciplines, integrating mathematical rigor with practical engineering solutions.

Samuel Chengمشاهده پروفایل

دانشیار

• Information Theory
• Signal and Image Processing
• Remote Sensing
• +۴ مورد دیگر

Dr. Samuel Cheng is an Associate Professor at the Gallogly College of Engineering , University of Oklahoma , specializing in Electrical and Computer Engineering . He holds a Ph.D. in Electrical Engineering from Texas A&M University (2004), preceded by M.S. and M.Phil. degrees from the University of Hawaii and Hong Kong University of Science and Technology. Education: B.S. (University of Hong Kong, 1995), M.Phil. (HKUST, 1997), M.S. (University of Hawaii, 2000), Ph.D. (Texas A&M, 2004) Professional Experience: Senior Research Engineer at Advanced Digital Imaging Research (2004-2005), prior internships at Microsoft Asia and Panasonic Technologies His research focuses on Information Theory , Signal and Image Processing , and Pattern Recognition , with applications in remote sensing, urbanization analysis, and disaster monitoring. His publications span topics including urban impervious surface mapping , nighttime light analysis , and machine learning for environmental data . His work often integrates multi-source datasets (e.g., Landsat, LiDAR, social media) for spatiotemporal modeling. Technical Expertise: Spectral unmixing, machine learning, thermal remote sensing, GIS integration Key Applications: Power outage detection, vegetation-crime correlation, PM2.5 estimation, smart meter data fusion Dr. Cheng holds three US patents in digital watermarking and is affiliated with IEEE, Sigma Xi, and AAAS. His recent articles demonstrate a trend toward leveraging AI for remote sensing challenges and analyzing urbanization impacts on ecosystems.

Farhad Aslaniمشاهده پروفایل

دانشیار

• Structural Engineering
• Concrete Engineering
• Sustainable Construction Materials
• +۵ مورد دیگر

Dr. Farhad Aslani is an Associate Professor in the Department of Civil, Environmental and Mining Engineering at the University of Western Australia (UWA), serving as Director of the Materials and Structures Innovation Group. He leads the $250M Australian Composites Manufacturing CRC and co-leads UWA's Engineering Materials Research Cluster. His research focuses on innovative construction materials, including self-sensing concrete, 3D-printed composites, and fire-resistant materials. He has secured over $20M in CRC funding and holds leadership roles in national/international conferences. Key awards include the 2024 Concrete Institute WA Rising Star Award and multiple citation milestones. His work aligns with sustainable development goals, emphasizing eco-friendly materials and infrastructure resilience. Education: PhD in Structural Engineering, University of Technology Sydney (2014) Certificates in Leadership, Research Commercialization, Public Policy, and Project Management from Curtin University, Queensland University of Technology, RMIT, and UTS. Research Interests: Smart materials, sustainable concrete technologies, additive manufacturing, blast/fire resistance, and composites for infrastructure. His lab develops self-sensing concretes, lightweight engineered composites, and electromagnetic shielding materials. Grants & Projects: $4.3M ACM CRC project on composite repairs ARC grants for nanocomposite coatings and fire facilities Main Roads WA funding for timber bridge strengthening Expertise: Structural design, composite materials, and industrial collaborations (e.g., Woodside, Holcim). He advises on major projects like the Morley Ellenbrook Rail Line and Forrestfield Airport Link. Awards: 2024 Concrete Institute WA Rising Star Highly Cited Scholar (ScholarGPS, 2024) Most Cited Paper Awards (2018–2020)

J. Eric Bickelمشاهده پروفایل

استاد

• Decision Analysis
• Probabilistic Modeling
• Climate Engineering
• +۴ مورد دیگر

J. Eric Bickel is a Professor at The University of Texas at Austin, serving as Director of the Operations Research & Industrial Engineering (ORIE) and Engineering Management programs. He holds a courtesy appointment in the Department of Petroleum and Geosystems Engineering and directs the Center for Engineering & Decision Analytics (CEDA). His academic background includes a PhD and MS in Engineering-Economic Systems from Stanford University and a BS in Mechanical Engineering from New Mexico State University. His research focuses on decision analysis under uncertainty, addressing topics like probabilistic modeling, climate engineering, risk management, and applications in sports and energy sectors. His work has been featured in major media including The New York Times and Wall Street Journal , and his climate engineering research was endorsed by Nobel Laureates as a top climate change response strategy. Professor Bickel has extensive industry experience, having previously served as Senior Engagement Manager and Co-Director of Client Education at Strategic Decisions Group (SDG), where he remains on the Board of Directors. His consulting spans oil/gas, energy trading, and financial services sectors. He has received recognition as a Fellow of the Society of Decision Professionals and contributed to the Copenhagen Consensus on Climate Project. His teaching extends to executive education through Texas Executive Education and McCombs School of Business. Research highlights include novel methods for probabilistic dependence modeling, value-of-information analysis in shale reservoirs, and critiques of risk assessment tools like heat maps. His climate engineering work emphasizes economically viable solar radiation management strategies.

• Manufacturing Systems Management
• Additive Manufacturing
• 3D Printing
• +۸ مورد دیگر

Professor Daniel Eyers is a Professor of Manufacturing Systems Management at Cardiff Business School, Cardiff University , where he also serves as Director of Quality Assurance & Enhancement. He is co-director of the Centre for Advanced Manufacturing Systems (CAMSAC) and Cardiff University RemakerSpace , highlighting his leadership in sustainable and advanced manufacturing innovation. Professor of Manufacturing Systems Management, Cardiff University (2024–present) Co-Director, Centre for Advanced Manufacturing Systems (CAMSAC) (2024–present) Co-Director, Cardiff University RemakerSpace (2020–present) External Advisor, Open University (2022–present) His research focuses on the strategic management of advanced manufacturing technologies , particularly Additive Manufacturing (3D printing) , within operations and supply chain contexts. He explores how digital technologies enhance supply chain flexibility, sustainability, and performance. His work spans flexible manufacturing systems, servitization, and change management in industrial settings. His recent publications (2020–2025) reveal a strong trajectory in AI-human collaboration in decision-making , sustainable manufacturing , urban logistics , and the integration of 3D printing in circular economies. Themes include risk management, digital transformation, and the strategic impact of emerging technologies on operations. He frequently publishes in top-tier journals such as International Journal of Operations and Production Management , Production Planning and Control , and Omega . CEng, Engineering Council (UK) FHEA, Higher Education Academy ESRC Early Career Impact Acceleration Fellowship Daniel Eyers actively supervises PhD, MSc, and MBA students and has attracted over £2.5 million in research funding from research councils, the Welsh Government, and industry. He contributes to academic program design and quality assurance, serving on university committees and as an external examiner for other institutions. He is deeply engaged in applied research with industrial partners, reflecting his background in commercial manufacturing. His leadership in research centers and commitment to sustainability, digital innovation, and education underscore his role as a key figure in modern operations management scholarship.

Torsten Wolfgang Kuhlenمشاهده پروفایل

استاد

• Virtual Reality
• Immersive Visualization
• Scientific Visualization
• +۵ مورد دیگر

Prof. Torsten Wolfgang Kuhlen serves as a Universitätsprofessor at RWTH Aachen University, leading the Teaching and Research Area for Virtual Reality and Immersive Visualization within the Department of Computer Science. He is affiliated with Chair of Computer Science 12 (High Performance Computing), the Visual Computing Institute, and remains an integral part of the RWTH IT Center where his research group operates one of the world's largest Virtual Reality laboratories including the 30 sqm aixCAVE visualization chamber. The group maintains strong connections with Computational Science & Engineering Division, National High Performance Computing Center for Computational Engineering Science (NHR4CES), and VR in Science and Industry Network NRW e.V. Prof. Kuhlen's research spans virtual reality, immersive visualization, and multimodal 3D user interfaces with applications across simulation science, production technology, neuroscience, and medicine. His work combines basic research on advanced methods and algorithms with interdisciplinary collaborations involving RWTH Aachen institutes, Forschungszentrum Jülich, and industry partners. Recent publications demonstrate strong focus on audiovisual perception, immersive analytics, collaborative virtual environments, and practical VR applications in education and manufacturing. His research group has produced significant work on listening effort in virtual environments, immersive authoring techniques, and VR applications for scientific visualization. Notable projects include VRScenarioBuilder for automated vehicle testing and applications in monitoring additive manufacturing processes. The group actively participates in major conferences including IEEE VIS and EuroVis, with several award-winning contributions. Prof. Kuhlen has advised PhD students including Martin Bellgardt who recently completed his doctoral degree on "Increasing Immersion in Machine Learning Pipelines for Mechanical Engineering". The research group maintains state-of-the-art VR infrastructure including the aixCAVE facility which is open to all RWTH research groups.

Eduardo Pereyraمشاهده پروفایل

استاد

• Multiphase Flow
• Flow Assurance
• Artificial Lift
• +۳ مورد دیگر

Eduardo Pereyra is a Professor in the McDougall School of Petroleum Engineering at The University of Tulsa, where he serves as Associate Director for the Tulsa Fluid Flow Projects (TUFFP) and the Horizontal Wells Artificial Lift Project (TUHWALP) . His academic career spans theoretical and applied research in multiphase flow, flow assurance, artificial lift systems, and separation technologies. Education: Ph.D. and M.Sc. in Petroleum Engineering from The University of Tulsa; Dual B.S. in Mechanical Engineering and Systems Engineering from the University of Los Andes, Venezuela Pereyra’s research focuses on multiphase flow dynamics , particularly in gas-liquid and oil-water systems. His work addresses critical challenges such as slug flow mitigation , downhole separator efficiency , and ESP motor cooling , leveraging computational fluid dynamics (CFD) and experimental validation. Recent publications emphasize inclined pipe flows , severe slugging mitigation , and plunger lift optimization . Pereyra has received multiple accolades, including the 2023 SPE Production and Operations Award and the 2022 Kermit Brown Outstanding Teacher Award . His contributions to multiphase flow modeling have been recognized through the 2021 Zelimir Schmidt Outstanding Researcher Award . He actively collaborates with industry partners through TUFFP and TUHWALP, directing projects like the Horizontal Wells Artificial Lift Initiative .

Niladri Banerjeeمشاهده پروفایل

مدرس ارشد

• Quantum Materials
• Spintronics
• Superconductivity
• +۴ مورد دیگر

Niladri Banerjee is a Senior Lecturer in the Department of Physics at Imperial College London, serving as Research Representative of the Matter Community in Physics. His research focuses on atomic-precision growth of materials, advanced electronic and magnetic characterisation, and modelling to develop emergent quantum phases in low-dimensional systems including thin films and van der Waals materials. Education PhD, University of Cambridge Postdoctoral Research Associate, University of Cambridge Junior Research Fellow, Wolfson College, Cambridge Research Interests His work spans critical areas in quantum technology development: Quantum Materials: Engineering emergent quantum phases through atomic-precision synthesis of low-dimensional materials. Spintronics: Investigating spin-orbit coupling effects and triplet supercurrents in superconducting hybrid structures. Superconductivity: Developing superconducting switches, diodes, and proximity-effect devices for quantum computing. Nanomaterials: Characterising thin films and van der Waals heterostructures for next-generation electronic applications. Recent Publications His 2021-2025 publications demonstrate sustained leadership in superconducting spintronics and topological quantum materials. Key contributions include realising de Gennes' superconducting switch, roadmap development for quantum technologies, and flux-pinning mediated superconducting diodes. His work consistently bridges experimental synthesis with theoretical modelling to address challenges in quantum computing and neuromorphic technologies. Scientific Awards No scientific awards were mentioned in the provided materials. Advising and Grants Details regarding student advising and research grants were not specified in the available information. Labs and Teams As an active member of Imperial's Matter Community in Physics, Dr. Banerjee collaborates on advanced characterisation techniques and quantum device engineering, focusing on spin-orbit coupled materials and topological phenomena for quantum technology applications.

• Hypersonics
• Plasma Flows
• Optical Diagnostics
• +۵ مورد دیگر

Tobias Hermann serves as an Associate Professor at the University of Oxford's Department of Engineering Science, where he leads research within the Oxford Thermofluids Institute and holds a prestigious UKRI Future Leaders Fellowship. Affiliated with St. Hilda's College as an Associate Research Fellow, his work centers on experimental hypersonics and advanced diagnostic development for extreme aerospace environments. Hermann earned his Dipl.-Ing. in Aerospace Engineering from the University of Stuttgart (2012) followed by a Dr.-Ing. degree (2017), with doctoral research focused on spacecraft re-entry phenomena and aerothermochemistry during atmospheric entry. His thesis involved developing optical diagnostics including Vacuum Ultraviolet spectroscopy and tomographic emission systems. His research program emphasizes experimental hypersonics and plasma flows , with core expertise in spacecraft re-entry physics , high-temperature material-flow interactions , and optical diagnostic innovation . Hermann pioneered analytical methods for transpiration cooling in porous media and developed system engineering tools for thermal protection systems. His current work bridges fundamental fluid dynamics with practical aerospace applications, particularly in hypersonic vehicle design and re-entry simulation through facilities like the T6 expansion tube. Analysis of Hermann's publication record reveals consistent focus on high-enthalpy flow diagnostics and thermal protection systems , with recent work advancing expansion tube capabilities for boost-glide re-entry simulation, integrated arc-jet facilities for ablating models, and vacuum ultraviolet spectroscopy for plasma flow characterization. His research demonstrates strong integration of experimental validation with analytical modeling across hypersonic testing regimes. Hermann's scientific recognition includes: UKRI Future Leaders Fellowship (2021-present) As an educator, Hermann supervises 4th-year undergraduate projects and DPhil (PhD) students in hypersonics while teaching Thermodynamics and Fluid Mechanics. His current research portfolio—primarily funded through his UKRI Fellowship—comprises three major thrusts: development of high-enthalpy wind tunnels (including the multi-mode T6 facility), pre-heating of hypersonic models using plasma flows, and advancement of measurement techniques like spatially resolved UV-nIR spectroscopy. These projects address critical gaps in hypersonic testing infrastructure and instrumentation. Hermann directs experimental efforts at Oxford's Southwell Laboratory within the Oxford Hypersonics group, operating facilities including the T6 Stalker tunnel, OPG1 plasma wind tunnel, and specialized arc-jet systems. His team develops cutting-edge instrumentation such as vacuum ultraviolet spectroscopy systems, high-speed focused Schlieren, and pressure-sensitive paint diagnostics to investigate complex phenomena in hypersonic boundary layers and re-entry flows.

Gabriella Pizzutoمشاهده پروفایل

مدرس

• Robotics
• Machine Learning
• Laboratory Automation
• +۵ مورد دیگر

Dr. Gabriella Pizzuto is a Lecturer in Robotics and Chemistry Automation at the University of Liverpool's Faculty of Science and Engineering, jointly appointed in the Departments of Computer Science and Chemistry. She leads the Pizzuto Group and joined the university in 2021 after completing her PhD at the University of Manchester. Born in Malta, she obtained her undergraduate degree from the University of Malta. Her research focuses on intelligent robotic systems for laboratory automation, specializing in: Contact-based robot skill learning for chemistry labs Failure recovery methods in experimental environments Safe human-robot collaboration frameworks Physics-constrained machine learning Machine vision for laboratory workflows Her work aims to develop robotic scientists that accelerate material discovery through autonomous experimentation. Publication analysis reveals strong emphasis on robotic manipulation (70%), laboratory automation (60%), and machine learning applications (40%), with recent work showing increased focus on multi-modal sensing and physics-informed learning. Her most frequent collaborators include Prof. Andy Cooper and Prof. Michael Mistry. Awards and Fellowships: Royal Academy of Engineering Research Fellowship (2023-2028) Marie Skłodowska-Curie Doctoral Scholarship EPSRC New Investigator Award (2025) Advising and Grants: Currently supervising 4 PhD students and 2 postdoctoral researchers Principal Investigator: £1.2M RAEng Fellowship for 'Upskilling Robotic Scientists' Co-Investigator: £12M EPSRC AI for Chemistry Hub (AIChemy) Lead Researcher: €8M ERC Synergy ADAM project Recipient of Google DeepMind Research Ready Grant (2024) Leads the Autonomous Robotic Chemistry Lab at Liverpool's Leverhulme Research Centre for Functional Materials. Her group combines expertise in robotics, computer science, chemistry, and engineering to develop next-generation robotic scientists.

Jerome Engelمشاهده پروفایل

استاد

• Epilepsy
• Neurophysiology
• High-Frequency Oscillations
• +۵ مورد دیگر

Jerome Engel, M.D., Ph.D. is a Professor at the Jane and Terry Semel Institute for Neuroscience and Human Behavior , University of California, Los Angeles (UCLA). He serves as Director of the Epilepsy Telemetry Unit within the Seizure Disorder Center and is a member of the Brain Research Institute and the Neuroscience GPB Home Area. His work spans neurology, psychiatry, and biomedical research. Research Focus: Epilepsy, epileptogenesis, high-frequency oscillations (HFOs), neuroimaging, surgical interventions, and biomarker development. Key Contributions: Pioneering studies on fast ripples as biomarkers, network-based surgical outcome prediction, and advanced HFO detection algorithms. Publications (15 most recent) address topics such as kainic acid models of epileptogenesis, thalamic sleep spindles in pediatric epilepsy, self-supervised HFO analysis, and graph theoretical measures for surgical planning. His work frequently employs medRxiv and Epilepsia as platforms for translational findings. Contact: engel@ucla.edu

Giulia Giordanoمشاهده پروفایل

استاد

• Automatic control
• Complex networks
• Control systems
• +۱۲ مورد دیگر

Giulia Giordano is a Full Professor in the Department of Industrial Engineering at the University of Trento, Italy, where she leads the Dynamical Networks and Systems Biology research group. She also holds a dual appointment as Visiting Professor and Delft Technology Fellow at the Delft Center for Systems and Control, Delft University of Technology, The Netherlands. Her career includes previous positions as Assistant Professor at Delft University of Technology (2017-2019), Postdoctoral Research Fellow at Lund University, Sweden (2016-2017), and Research Fellow at the University of Udine, Italy (2016). Giulia earned her Ph.D. in Industrial and Information Engineering: Automation (Excellent) from the University of Udine with a thesis titled "Structural Analysis and Control of Dynamical Networks." She completed her M.Sc. and B.Sc. in Electrical Engineering (both Summa cum laude) at the same institution. She also undertook research visits at Caltech (2012) as a SURF Fellow and at the University of Stuttgart (2015) as a DAAD Research Scholar. Her primary research focuses on the analysis and control of dynamical networks with applications in systems biology, mathematical ecology, and mathematical epidemiology. She develops mathematical frameworks that bridge control theory, network theory, and dynamical systems to address complex problems in biological systems. Her recent work spans epidemic modeling, opinion dynamics, biochemical networks, and neurological disorders, with a particular emphasis on structural analysis of networked systems. She employs both theoretical and computational approaches to understand system behavior under uncertainty. Giulia's publications reveal a strong interdisciplinary focus, spanning from theoretical control systems to practical applications in epidemiology and biology. Her recent work shows increasing emphasis on epidemic modeling (particularly related to mpox and SARS-CoV-2), network synchronization, and the application of control theory to biological phenomena like fibromyalgia pathogenesis and opinion formation. Many of her papers appear in top-tier control journals including Automatica and IEEE Transactions on Automatic Control. 2024: Outstanding Service as Associate Editor of IEEE Control Systems Letters 2021: SIAM Activity Group on Control and Systems Theory Prize 2020: Outstanding Reviewer, Annals of Internal Medicine 2017: NAHS Best Paper Prize and EECI PhD Award 2016: Outstanding TAC Reviewer, IEEE Transactions on Automatic Control Giulia actively mentors students and postdoctoral researchers, currently supervising five postdoctoral researchers and two Ph.D. students at the University of Trento. She has advised numerous M.Sc. and B.Sc. students on topics ranging from bio-inspired modeling to optimal control of epidemic systems. Her research is supported by competitive grants including the ERC Starting Grant INSPIRE (Integrated Structural and Probabilistic Approaches for Biological and Epidemiological Systems). She serves as Associate Editor for IEEE Control Systems Letters and Automatica, and is a Senior Member of IEEE and the Control Systems Society. Giulia leads the Dynamical Networks and Systems Biology research group at the University of Trento, which maintains strong international collaborations across Europe and North America. The group's work combines theoretical advances in control theory with practical applications to pressing problems in public health and biological systems, demonstrating the power of mathematical approaches to understanding complex phenomena in the life sciences.

Marios Polycarpouمشاهده پروفایل

استاد

• Intelligent Systems
• Adaptive Control Systems
• Fault Diagnosis
• +۳ مورد دیگر

Marios Polycarpou is a Professor of Electrical and Computer Engineering and Director of the KIOS Research and Innovation Center of Excellence at the University of Cyprus. He holds honorary positions at Imperial College London and is a member of Academia Europaea. His expertise spans intelligent systems, adaptive control, machine learning, and critical infrastructure. Education: B.A. Computer Science (Rice University, 1987) B.Sc. Electrical Engineering (Rice University, 1987) M.S. Electrical Engineering (University of Southern California, 1989) Ph.D. Electrical Engineering (University of Southern California, 1992) Research Focus: Polycarpou’s work emphasizes fault diagnosis in cyber-physical systems, water distribution networks, and adaptive control. He pioneers digital twin technologies for infrastructure resilience and develops algorithms for real-time anomaly detection and system optimization. Article Trends: His recent publications address adaptive control strategies, cybersecurity in networked systems, and AI-driven solutions for water management. Key themes include distributed control, event-triggered mechanisms, and transformer-based anomaly localization. Awards: 2023 IEEE Frank Rosenblatt Technical Field Award 2016 IEEE Neural Networks Pioneer Award Fellow of IEEE and IFAC Grants & Leadership: He secured prestigious grants including ERC Advanced and Synergy Grants. He led KIOS CoE’s Horizon 2020 projects and served as IEEE Computational Intelligence Society President (2012–2013). Labs & Teams: Directs the KIOS CoE, a hub for AI in critical infrastructure. Collaborates on projects like ERC Water-Futures, focusing on long-term water system transitions and contamination mitigation.

• Computational Photonics
• Optical Engineering
• Quantum Optics
• +۴ مورد دیگر

Özüm Asirim is a Researcher at the Technical University of Munich (TUM) under the Associate Professorship of Computational Photonics led by Prof. Christian Jirauschek. Her work focuses on computational photonics , quantum optics , and nonlinear optical phenomena , particularly in micro-resonators and semiconductor devices. Education: Ph.D. in Electrical Engineering from Middle East Technical University (Ankara, Turkey). Research spans optical parametric amplification , Fourier domain mode-locked lasers , self-phase modulation , and machine learning applications in photonics . Her studies include optimizing gain factors, enhancing harmonic generation, and modeling supercontinuum sources via carrier injection. Recent publications (2019–2023) highlight interdisciplinary approaches, merging photonics with computational finance and nonlinear dynamics . She contributes to EU Project QOMBS and teaches courses like Python for Engineering Data Analysis and Quantum Engineering and Machine Learning seminars. Collaborations include Prof. Christian Jirauschek (TUM), Prof. Mustafa Kuzuoğlu (Middle East Technical University), and teams in computational photonics and quantum optics. Her work impacts semiconductor physics , laser technology , and adaptive optical systems .