جست‌وجوی استاد و پژوهشگر

• Quantum Optics
• Terahertz Technology
• Photonics
• +۴ مورد دیگر

Lukas Seitner is a researcher at the Technical University of Munich (TUM), affiliated with the School of Computation, Information and Technology and the Department of Electrical Engineering. He operates within the Associate Professorship of Computational Photonics led by Prof. Christian Jirauschek, focusing on advanced modeling of quantum cascade devices and terahertz photonics systems. His research spans quantum cascade lasers (QCLs), terahertz frequency combs, optical solitons, and computational photonics. Seitner has developed sophisticated simulation frameworks including Maxwell-Bloch and density matrix approaches to study nonlinear dynamics in optoelectronic devices. Key contributions involve passive mode-locking mechanisms in THz QCLs, graphene-integrated saturable absorbers for pulse generation, and backscattering effects in ring-cavity soliton formation. His work bridges theoretical modeling with practical device engineering for next-generation terahertz sources. As an educator, Seitner serves as assistant lecturer for multiple courses including Computational Photonics Laboratory (5 PR), Partial Differential Equations for Electrical Engineering (4 VI), and Simulation of Quantum Devices (4 VI). He actively participates in doctoral candidate seminars and specialized courses on quantum engineering, demonstrating strong commitment to academic training in photonics and quantum device physics. His teaching integrates cutting-edge research concepts into practical computational exercises. Seitner maintains active collaboration within the EU Project QOMBS and contributes to TUM's Computational Photonics group research infrastructure. His technical expertise encompasses numerical methods for partial differential equations, semiconductor device simulation, and nonlinear optical modeling. Current projects focus on optimizing THz comb sources for spectroscopic applications and extending quantum walk models for novel frequency comb generation mechanisms.

Eunchun Parkمشاهده پروفایل

استادیار

• Risk Analysis
• Commodity Futures and Options
• Crop Insurance
• +۳ مورد دیگر

Eunchun Park serves as an Assistant Professor in the Department of Agricultural Economics and Agribusiness at the University of Arkansas, concurrently holding the position of Director of the Experiment Station (DREX). A specialist in Bayesian spatial statistics and econometrics, his research focuses on agricultural risk analysis with particular emphasis on crop insurance mechanisms and financial commodity markets. His methodological expertise addresses critical data scarcity challenges in federal crop insurance premium calculations through advanced spatial modeling techniques. Dr. Park's academic foundation includes: Ph.D. in Agricultural Economics from Oklahoma State University (2017) M.S. in Food and Resource Economics from Korea University (2013) B.S. in Food and Resource Economics from Korea University (2010) His research program centers on extreme price and yield risk quantification in agricultural commodities, employing sophisticated Bayesian modeling frameworks to overcome data limitations in spatial risk assessment. Current work develops innovative approaches for measuring catastrophic risks in crop production systems and refining insurance rating structures through spatial smoothing of yield densities. This research bridges theoretical econometric advances with practical applications for risk management tools used by farmers and policymakers. Analysis of Dr. Park's recent publications reveals a consistent trajectory in spatial risk modeling for agricultural insurance systems, with increasing focus on prevented planting coverage factors, commodity market volatility around information releases, and climate-related production risks. His work demonstrates methodological progression from theoretical Bayesian frameworks toward actionable risk assessment tools, particularly through the application of kriging techniques to non-normal yield distributions and extreme event modeling. Dr. Park's scholarly contributions have been recognized through: Outstanding Contribution to Applied Risk Analysis Award (2020) from the Agricultural and Applied Economics Association Outstanding Graduate Student Paper Award (2018) from the Agricultural and Applied Economics Association Outstanding Doctoral Dissertation Award (2018) from the Southern Agricultural Economics Association While specific details of current advisees and grant funding are not provided in available materials, his active publication record in top agricultural economics journals suggests an ongoing mentorship role for graduate students and potential involvement in externally funded research initiatives related to agricultural risk management. His work on spatial smoothing techniques and extreme risk modeling likely informs collaborative projects with agricultural extension services and federal risk management agencies. No specific laboratory facilities or dedicated research teams are mentioned in the available documentation, though his methodological expertise suggests collaboration with spatial statistics and agricultural risk modeling groups within the university's research infrastructure.

Aleksandar Mihajlovicمشاهده پروفایل

پژوهشگر

• Visual Communication
• Graphic Design
• Digital Marketing
• +۵ مورد دیگر

Aleksandar Mihajlovic is a researcher and Art Director at Singidunum University, Serbia. With a doctoral degree in Contemporary Business Decision-Making (2022), a master's in Business Economics (2014), and a bachelor's in Computer Graphics and Design (2008), he combines academic rigor with creative leadership in the university's marketing strategy. Doctoral studies: Contemporary Business Decision-Making, Singidunum University (2022) Master studies: Business Economics, Singidunum University (2008–2014) Undergraduate: Computer Graphics and Design, Faculty of Informatics and Management (2005–2008) High school: Robotics and Flexible Production Systems Technician, Polytechnic Academy (1995–1999) His research spans visual communication , digital marketing , and artificial intelligence applications in creative industries. Key contributions include Co-authoring 11 academic papers (2015–2025) on topics like Instagram ad effectiveness, techno-feudalism, and responsive logo design. Developing the scientific research portal 'Singipedia' and international magazine 'SingiLogos'. Participating in 7 global projects including Erasmus+ and TEMPUS initiatives. His scientific awards include the JISA Discobolos Special Award (2010), IT Globus Award (2010), and Grafima Fair Special Award (2025). He serves on the organizing committee for conferences like Sinteza and Sitcon , and has judged marketing competitions while volunteering for NGOs like the City Organization of the Deaf of Belgrade.

Eva Cetinicمشاهده پروفایل

پژوهشگر

• Deep Learning
• Explainable AI
• Digital Art
• +۵ مورد دیگر

Dr. Eva Cetinic is a DSI Bridge Postdoc Fellow at the University of Zurich, conducting research at the intersection of deep learning, explainable AI, and digital art and humanities. Previously, she held postdoctoral positions at Durham University and the Center for Digital Visual Studies at the University of Zurich, and worked as a Professional Associate and Postdoc at the Rudjer Boskovic Institute in Croatia from 2015 to 2021. Her educational background includes: PhD in Computer Science, University of Zagreb (2019) Dr. Cetinic's research focuses on computational image understanding and multimodal learning for visual art and culture, investigating how text-image models encode socio-cultural patterns and impact artistic creation. Her work critically examines ethical and societal implications of AI while bridging computer science, digital humanities, and art history through interdisciplinary methodologies. Her publication trends (2019-2025) reveal concentrated analysis of generative AI's cultural impact, particularly text-to-image systems. She systematically investigates bias propagation (gender, cultural), user interaction dynamics, and creative processes while developing technical frameworks for art analysis - moving beyond technical capabilities to address real-world implications in artistic and cultural contexts. She currently leads the UZH-funded project 'From Hype to Reality: Artificial Intelligence in the Study of Art and Culture' in collaboration with the University of Cambridge, establishing cross-institutional frameworks for responsible AI adoption. Her research methodology emphasizes practical implementation within humanities workflows through international networks like DARIAH. As a DSI Bridge Postdoc Fellow, Dr. Cetinic operates within the University of Zurich's Digital Society Initiative ecosystem, connecting computational research with the Center for Digital Visual Studies and global digital humanities infrastructures to examine AI's transformative role in cultural production and interpretation.

Shiyu Changمشاهده پروفایل

دانشیار

• Machine Learning
• Natural Language Processing
• Computer Vision
• +۳ مورد دیگر

Shiyu Chang is an Associate Professor of Computer Science at the University of California, Santa Barbara, and a Research Staff Member at the MIT-IBM Watson AI Lab. His work bridges machine learning, natural language processing, and computer vision with a focus on interpretability and robustness. Current Affiliation: UC Santa Barbara Lab: MIT-IBM Watson AI Lab His research explores how to make AI systems more interpretable and robust by integrating human intuition and rationalization. Key themes include adversarial learning, self-supervised methods, and improving transferability in models. Recent publications span conferences like ICML, CVPR, and NeurIPS, addressing topics such as black-box text classification, fairness-aware algorithms, and speech representation disentanglement. Broad keywords include Machine Learning, NLP, and Computer Vision. Fairness Reprogramming (AI Fairness) TransGAN: Transformer-based GANs Adversarial Robustness Certificates

• Stochastic Processes
• Probability Theory
• Mathematical Modeling
• +۴ مورد دیگر

Professor Vitali Wachtel of Bielefeld University's Faculty of Mathematics specializes in advanced stochastic processes, probability theory, and their applications in mathematical modeling. Since 2021, he holds a W3 Professorship and serves as Principal Investigator in CRC 1283 'Taming uncertainty and profiting from randomness and low regularity in analysis, stochastics and their applications' since 2023. Chaired Examination Boards for Bachelor & Master Business Mathematics Member, Bielefeld Graduate School in Theoretical Sciences Research focus: Markov processes, random walks in cones, branching processes Research Trends: His recent work spans critical multitype branching in random environments (2025), asymptotic expansions for conditioned random walks (2024), and invariance principles for integrated processes. He explores connections between stochastic processes, combinatorial structures, and risk modeling with level-dependent premiums. Awards: Feodor Lynen Research Fellowship (2017), Alexander von Humboldt Foundation Teaching: Coordinates modules including 'Stochastic Processes' (24-M-PT-STP) and 'Introduction to Probability Theory' (24-B-EW-5). Active in curriculum development and academic governance through multiple university committees.

• Automated Transportation Systems
• Connected Vehicles
• Electric Vehicles
• +۳ مورد دیگر

Dr. Xiaopeng Li is the Harvey D. Spangler Professor in the Department of Civil and Environmental Engineering at the University of Wisconsin-Madison, with an affiliation in the Department of Electrical and Computer Engineering. He leads the USDOT Rural Autonomous Vehicle Program and previously directed the National Institute for Congestion Reduction. He earned his B.S. in Civil Engineering from Tsinghua University (2006), M.S. in Civil Engineering (2007), M.S. in Applied Mathematics (2010), and Ph.D. in Civil Engineering (2011) from the University of Illinois at Urbana-Champaign. His research focuses on modeling and field experiments for connected, electric, and automated vehicles (CAVs), infrastructure systems analysis, and interdependent network modeling. He has pioneered physics-enhanced machine learning frameworks for vehicle control and developed simulation tools for CAV deployment. His 2025-2024 publications highlight advancements in Connected vehicle trajectory modeling Energy consumption optimization Edge computing for autonomous operations Residual learning control systems Equity analysis in AV deployment Communication technologies for V2X Awards include: TRB Best Paper Award (2025) NSF CAREER (2015) ASCE Fellow (2024) IEEE Senior Member (2022) Multiple institution-specific fellowships He has advised 15+ graduate students, secured $35M+ in grants from NSF, USDOT, and industry partners, and chairs the IEEE ITSS Emerging Transportation Technology Testing committee. His work addresses real-world AV implementation, safety validation, and sustainable transportation systems.

Jennifer Brick Murtazashviliمشاهده پروفایل

دانشیار

• Self-governance
• Security Studies
• Political Economy
• +۷ مورد دیگر

Jennifer Brick Murtazashvili is an associate professor at the University of Pittsburgh's Graduate School of Public and International Affairs and founding director of the Center for Governance and Markets. She also serves as a nonresident scholar in the Asia Program at the Carnegie Endowment for International Peace. Her academic career bridges rigorous scholarly research with practical policy engagement across multiple international institutions. Dr. Murtazashvili's research focuses on self-governance, security, political economy, and public sector reform in the developing world, with particular expertise in Afghanistan and Central Asia. Her work examines the intersection of formal state institutions and customary governance structures, challenging conventional approaches to state-building and democracy promotion. She argues that top-down imposition of centralized governance models often undermines local legitimacy and creates unintended consequences, as documented in her award-winning book Informal Order and the State in Afghanistan . Her recent publications and media commentary analyze evolving geopolitical dynamics in Central Asia following the Russian invasion of Ukraine and the Taliban's return to power in Afghanistan. She has identified significant shifts in regional power dynamics, with Central Asian states increasingly asserting strategic autonomy while navigating complex relationships with both Russia and China. Best Book Award in Social Sciences by the Central Eurasian Studies Society Honorable mention from the International Development Section of the International Studies Association As president-elect of the Central Eurasian Studies Society and an elected board member of the Section for International and Comparative Public Administration of the American Society of Public Administration, Dr. Murtazashvili has advised numerous international organizations including USAID, the World Bank, the U.S. Department of Defense, UNDP, and UNICEF. Her policy work bridges academic research with practical governance challenges, particularly in post-conflict settings where state capacity intersects with local governance traditions.

Emily Burkheadمشاهده پروفایل

دانشیار

• Dynamical Systems
• Ergodic Theory
• Mathematics Education
• +۳ مورد دیگر

Emily Burkhead is a Teaching Associate Professor in the Department of Mathematics at the University of North Carolina at Chapel Hill (UNC). She holds a Ph.D. in Mathematics from UNC (2006) and has held academic positions at Meredith College, Duke University, and as a Visiting Lecturer/Researcher at UNC. Her research bridges discrete dynamical systems, ergodic theory, and mathematics education. Early work focused on topological classifications of cellular automata, while recent contributions involve stochastic cellular automata models for virus dynamics (HIV, Ebola) and pedagogical best practices. Key publications include analyses of HIV spread in lymph nodes (with Jane Hawkins and Donna Molinek) and Ebola virus dynamics. Her methodological innovations in stochastic cellular automata have been cited in studies on disease progression, computational modeling, and urban information diffusion. Emily earned a B.A. from the College of Wooster (2001), M.S. (2004) and Ph.D. (2006) from UNC, followed by postdoctoral work at the Santa Fe Institute (2006-2007).

• Computer Science
• Virtual Reality
• Scientific Visualization
• +۵ مورد دیگر

David H Laidlaw is a Professor of Computer Science at Brown University, specializing in virtual reality, scientific visualization, and medical imaging. His work spans interdisciplinary applications in neuroscience, biomedical research, and educational tools. Brown University Affiliation Department of Computer Science His research focuses on: Immersive visualization for complex data analysis Diffusion MRI and neuroimaging techniques Human-computer interaction in virtual environments 3D interaction methods for scientific exploration Collaborative visualization tools for multidisciplinary teams Recent trends in his publications highlight advancements in: Graph neural networks for biomedical data Memory-efficient segmentation algorithms Perceptual studies in VR environments Annotation and analysis of placental vasculature Technological innovations in foot dynamics research He teaches courses in virtual reality design and scientific visualization, including: CSCI 1370 - Virtual Reality Design for Science CSCI 1951S - Virtual Reality Software Review CSCI 1951T - Surveying VR Data Visualization Software CSCI 2370 - Interdisciplinary Scientific Visualization

Juan Alcacerمشاهده پروفایل

استاد

• International Business
• Corporate Strategy
• Global Strategic Management
• +۷ مورد دیگر

Juan Alcacer is the James J. Hill Professor of Business Administration at Harvard Business School. He holds a PhD in International Business and Strategy from the University of Michigan, an M.A. in Economics, an MBA in Finance, and a Computer Engineering degree. His research focuses on international strategies, location decisions, and agglomeration economies. PhD - University of Michigan (Ross School of Business) MA - Economics, University of Michigan MBA - IESA Computer Engineering - Universidad Simon Bolivar Alcacer’s work examines how firms build competitive advantage through geographic choices, supply chain dynamics, and knowledge transfer. Recent projects analyze Brexit’s impact on investment and the role of internal/external agglomeration economies. His publications span top journals like Strategic Management Journal , Management Science , and Journal of International Business . Awards include the 2024 HBS Student Association Faculty Teaching Award and the 2016 Michigan Ross Distinguished PhD Alumni Award. 2024 HBS Student Association Faculty Teaching Award 2019 Greenhill Award for Field Global Immersion program 2016 Michigan Ross Distinguished PhD Alumni Award 2013 Meritorious Service Award from Management Science At HBS, he teaches required MBA strategy courses, Executive Education programs, and PhD seminars. His consulting spans global corporations on competitive advantage and location strategy.

• Fluid Dynamics
• Mathematical Physics
• Partial Differential Equations
• +۵ مورد دیگر

Vincenzo Sciacca is a Full Professor in the Department of Mathematics and Computer Science at the University of Palermo, Italy. His academic position is listed under classification code MATH-04/A, which typically refers to Mathematical Analysis in the Italian academic system. He maintains regular office hours on Thursdays from 3:00 PM to 6:00 PM at the Department of Mathematics and Computer Science, Via Archirafi 34, Office No. 216 (2nd floor). Professor Sciacca's research spans several areas of mathematical physics and fluid dynamics. His primary interests include: Fluid dynamics and vortex theory Partial differential equations, particularly Navier-Stokes and Euler equations Singularity formation in boundary layer theory Numerical analysis of complex fluid systems Mathematical modeling in geophysical fluid dynamics Complex singularity analysis for nonlinear systems Analysis of his recent publications reveals a strong focus on the mathematical aspects of fluid dynamics, with particular attention to singularity formation, vortex dynamics, and the behavior of solutions to fundamental equations in fluid mechanics. His work combines rigorous mathematical analysis with computational approaches to understand complex phenomena in fluid systems. Over the years, his research has evolved from fundamental studies of singularity formation to more applied problems in geophysical fluid dynamics and mathematical biology as evidenced by his 2024 paper on Multiple Sclerosis. Professor Sciacca maintains an active research profile with publications spanning from 1994 to the present, demonstrating sustained scholarly contribution to his fields of expertise. His work shows interdisciplinary reach, connecting pure mathematical analysis with applications in physics, geophysics, and biomedical modeling. He can be contacted at vincenzo.sciacca@unipa.it and maintains a personal web page at http://math.unipa.it/~sciacca/ where additional information about his teaching and research is available.

• Medical Image Analysis
• Machine Learning
• Generative AI
• +۳ مورد دیگر

Dr Vu Minh Hieu Phan is a Research Fellow at the Australian Institute for Machine Learning , University of Adelaide. His work focuses on foundational models, multimodal learning, and medical image analysis, leveraging deep learning and large language models. Research Interests : Medical Image Analysis, Vision-Language Models, Generative AI, Semantic Segmentation, Continual Learning, Knowledge Distillation. Key Venues : CVPR, ACL, EMNLP, IJCAI, MICCAI, NeurIPS, TPAMI, and IJCV. Notable Contributions include advancements in multimodal learning for medical imaging, explainable AI frameworks, and efficient knowledge distillation techniques. He serves as a reviewer for top-tier journals and conferences. Email : vu.minhhieu.phan@adelaide.edu.au

Julian Adamekمشاهده پروفایل

پژوهشگر

• Computational Cosmology
• Theoretical Cosmology
• Large-scale structure of the Universe
• +۳ مورد دیگر

Julian Adamek is a computational cosmologist and lead developer of gevolution , a general-relativistic N-body code for cosmological simulations. His work focuses on modeling relativistic effects in cosmic structure formation to better understand gravity’s role on large scales and dark energy. Research Interests: Computational Cosmology, Theoretical Cosmology, Large-scale structure of the Universe, Relativistic N-body simulations. Technical Leadership: Lead developer of gevolution , a public cosmological simulation code available via GitHub. Recent publications span diverse applications of deep learning in geospatial analytics, environmental monitoring, and computer vision, including phenology modeling, biomass mapping, conflict assessment, and 3D reconstruction from point clouds. Key Trends: Integration of AI/ML for environmental tasks, cross-domain applications (cosmology, ecology, forestry), and satellite data processing. Technical Focus: Transformer networks, diffusion models, super-resolution imaging, and ensemble learning for uncertainty quantification. Julian collaborates with researchers in cosmology and geospatial science, though specific students or awards are not mentioned in the provided texts.

• Energy Chemistry
• Inorganic Materials Chemistry
• Solid-State Ionics
• +۲ مورد دیگر

Professor Masashi Okubo at Waseda University's School of Advanced Science and Engineering specializes in electrochemistry and energy materials development. With cross-appointments at Kyoto University and the Advanced Collaborative Research Organization for SmartSociety, his work focuses on sustainable battery systems including aqueous proton batteries, MXene-based electrodes, and oxygen-redox chemistry. His research bridges fundamental materials science with practical energy storage applications through combined experimental-theoretical approaches. Education : Ph.D. in Basic Science (2005) and M.Sc./B.Sc. in Basic Science from The University of Tokyo Research Strengths : Solid-state ionics and intercalation chemistry MXene electrode engineering Oxygen-redox reaction mechanisms High-rate energy storage systems Hydrate-melt electrolyte optimization Scientific Contributions include: Discovering near-zero-volume-phase battery materials Developing distortion-relieving voids in host structures Elucidating multiorbital bond formation in oxygen-redox reactions Advancing aqueous redox-flow battery catholyte design Prominent Awards : Waseda Research Award (2021) ACS Reviewer Excellence Award (2018) Ministry of Education Young Scientist Award (2017) Multiple Young Investigator Awards (2016)