Jump Processes Professors and Supervisors | ApplySharif

جست‌وجوی استاد و پژوهشگر

استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۷۰۶-۷۲۰ از ۷۷۳ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Nianqiao Juمشاهده پروفایل

استادیار

Dartmouth CollegeUnited States

Nianqiao 'Phyllis' Ju is an Assistant Professor of Mathematics at Dartmouth College (starting July 2025) and previously held a tenure-track position at Purdue University's Department of Statistics (2021–2025). She earned her Ph.D. in Statistics from Harvard University (2021) and a B.A. in Mathematics & Physics from Wellesley College (2016). Her research focuses on Bayesian statistics, Monte Carlo methods, differential privacy, and computational biology. She has received awards such as the Showalter Trust Young Investigator Award and NIH-NIAID funding for her work on disease progression modeling. She is also involved in the Online Monte Carlo Seminar and maintains a blog (phylliswithdata.wordpress.com) to communicate statistical ideas broadly. Education: Ph.D., Harvard University; B.A., Wellesley College Affiliations: Dartmouth College (2025–present), Purdue University (2021–2025) Professional Activities: Organizer of the Online Monte Carlo Seminar, YouTube channel for statistical content Her research spans theoretical and applied domains, including privacy-preserving Bayesian inference, MCMC convergence analysis, and computational methods for genetic data. Recent work includes developing the SOMA sampler and SNP-Slice framework for mixed infection analysis. She has authored over 10 peer-reviewed articles and secured multiple grants, including NIH-NIAID funding for systems biology research. Teaching responsibilities at Dartmouth include courses on probability and applied statistics (e.g., MATH 20, MATH 146). Her advising includes overseeing students in computational and privacy-focused projects.

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Nuno C. Martinsمشاهده پروفایل

استاد

University of Maryland, College ParkUnited States

Nuno C. Martins is a Professor of Electrical Engineering at the University of Maryland, College Park, with a joint appointment in the Institute for Systems Research. He holds a Ph.D. from MIT (2004) and an M.S. from IST, Portugal (1997), and completed a Financial Technology program at MIT's Sloan School. He served as Director of the Maryland Robotics Center (2012–2014) and has held editorial roles for journals like IEEE Transactions on Control of Network Systems and Automatica . His research focuses on distributed control systems, evolutionary dynamics, population games, and networked control. Notable contributions include work on Nash equilibrium learning in large populations, optimal remote estimation, and decentralized control under communication constraints. Martins' team explores applications in robotics, autonomous systems, and infrastructure safety. He has received prestigious awards such as the 2006 O. Hugo Schuck Award, 2007 NSF CAREER Award, and 2008 IEEE Axelby Award. His lab, the CPS and Cooperative Autonomy Lab, validates research on platforms like quadrotors and ground robots. Current projects include the ASTrA initiative for multi-agent cyber-physical systems and strategic traffic management during disasters. Education: M.S., Electrical Engineering, IST, Portugal (1997) Ph.D., Electrical Engineering and Computer Science, MIT (2004) Financial Technology Option, MIT Sloan (2004) Awards: 2023 IEEE TCNS Paper on Pairwise Comparison Dynamics 2022 Population Games with Erlang Clocks (CDC) 2010 George Corcoran Award (UMD) Grants: NSF ASTrA grant for trustworthy autonomous systems AFOSR/ONR-funded distributed tracking and secrecy control His lab hosts interdisciplinary research collaborations and undergraduate/graduate training programs. Recent work includes evolutionary dynamics models for epidemiology and mixed-autonomy systems.

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Dörte Kreherمشاهده پروفایل

استاد

University of ZurichSwitzerland

Dörte Kreher is a Professor of Applied Stochastic Analysis at Humboldt University of Berlin, leading the Department of Mathematics since August 2017. Her research focuses on stochastic analysis, mathematical finance, and energy markets, with a particular emphasis on stochastic processes, limit order book models, and market microstructure. Education: PhD in Mathematics (2014), Universität Zürich Diplom in Mathematics (2009), Humboldt University of Berlin B.Sc. in Economics (2009), Humboldt University of Berlin Research Interests: Dr. Kreher’s work integrates theoretical stochastic analysis with practical applications in finance and energy markets. Her projects include modeling intraday electricity markets, optimal control strategies for battery storage, and microstructural foundations of rough volatility models. She collaborates with institutions like MATH+, the Berlin-Oxford IRTG 2544, and the SFB/TRR 388. Teaching: She teaches advanced courses in stochastic finance, stochastic analysis, and statistics, including Stochastik I , Stochastische Finanzmathematik , and Methoden der Statistik . Grants & Projects: MATH+ Project AA4-4: Stochastic modeling of intraday electricity markets MATH+ Project AA4-9: Volatile Electricity Markets and Battery Storage Berlin-Oxford IRTG 2544: Stochastic Analysis in Interaction SFB/TRR 388 Project B02: Microstructural Foundations of Rough Volatility Models Labs/Teams: Leads research groups in stochastic finance and mathematical modeling, supervising PhD students such as Cassandra Milbradt, Wilfried Kenmoe Nzali, and Konstantins Starovoitovs.

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Theodosiadou Ouraniaمشاهده پروفایل

پژوهشگر

Aristotle University of ThessalonikiGreece

Ourania Theodosiadou is a Researcher at the Department of Mathematics, Aristotle University of Thessaloniki (since Oct 2024). Previously, she served as a Postdoctoral Researcher at the Institute of Information and Communication Technologies (CERTH) from 2019 to 2024 and held multiple contracted lecturer roles at Aristotle University and the University of Macedonia. She earned a PhD in Mathematics (2019) and a Master's in Statistics and Modeling (2014), both from AUTH, with a focus on stochastic processes and financial applications. Her doctoral thesis explored latent stochastic processes with jumps in finance under Prof. Georgios Tsaklidis. Her research interests span stochastic modeling, time series analysis, computational statistics, and machine learning. Recent work includes real-time threat assessment using Hidden Markov Models (2023), cryptocurrency transaction analysis for illegal activity detection (2023), and centrality-based network node identification (2022). Methodological contributions include state space modeling with constraints (2021) and Kalman filter applications for jump detection in financial markets (2017-2019). Publications reflect interdisciplinary applications in finance, security, and computational methods. Current work extends AI-driven solutions against terrorist financing and explores blockchain forensics through time series analysis.

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Andreas Wettreمشاهده پروفایل

مدرس

Oslo School of Architecture and DesignNorway

Andreas Wettre is a Lecturer at The Oslo School of Architecture and Design (AHO), where he teaches Systems Oriented Design (SOD) and chairs the Executive Master program—a 3-year part-time course for professionals. His research integrates SOD with organizational development, focusing on complexity management, silo-busting methodologies like 'Jumping Conversations,' and sustainable industrial transitions. With 25 years of prior experience in management consulting and technical leadership, Wettre bridges academia and industry practice. His work explores how SOD enhances organizational capacity to handle complexity, emphasizing practical frameworks for big data utilization, sustainable transitions, and cross-functional collaboration. Recent publications analyze industrial case studies in Norway, workshop-based training methods, and systemic barriers to change. Wettre’s teaching spans bachelor/master levels, including courses on complex systems design and implementation strategies. He has also contributed to student well-being initiatives at AHO.

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Christian Flindtمشاهده پروفایل

دانشیار

Aalto UniversityFinland

Christian Flindt is an Associate Professor at the Department of Applied Physics , School of Science , Aalto University . His research group focuses on theoretical quantum transport, with expertise in dynamic single-electron emitters, noise and fluctuations in electronic conductors, and charge transport in hybrid microwave cavity architectures. Education : Doctoral degree in Natural Sciences from Danmarks Tekniske Universitet (DTU) Flindt's research spans quantum many-body physics, statistical mechanics, and scattering theory, with applications to quantum devices and nanoelectronics. His recent work explores non-classical correlations, entanglement, and quantum jump trajectories. Key projects include the Finnish Centre of Excellence in Quantum Technology (2023–2025) and the QuLeeYang project on Lee-Yang theory for quantum phase transitions. His publications in 2025 address temperature control using qubits, Lee-Yang phase transition theory, and photon statistics in bosonic networks. Earlier works (2024) analyze Cooper pair splitters and charge tunneling in quantum dots. Flindt frequently collaborates internationally and has led projects funded by the Academy of Finland and EU H2020 MC.

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Jinling Wangمشاهده پروفایل

دانشیار

University of New South WalesAustralia

Geospatial Mapping
Global Navigation Satellite Systems (GNSS)
Inertial Navigation Systems (INS)
+۵ مورد دیگر

Associate Professor Jinling Wang is an academic at the University of New South Wales (UNSW), affiliated with the School of Civil Engineering and the Department of Civil Engineering. Her research focuses on geospatial mapping and navigation, including Global Navigation Satellite Systems (GNSS), Inertial Navigation Systems (INS), and multi-sensor integration for applications in autonomous vehicles and high-definition mapping. She has supervised 22 PhD and 6 Master’s students, seven of whom won prestigious international awards during their studies. Her awards include being named on the World’s Top 2% Scientists List from 2020 to 2024 and recognized as Australia’s Research Leader in 'Radar, Positioning, and Navigation' multiple times. She leads projects such as the UNSW Engineering Goldstar Award 2024 Research Grant and the UNSW-Tsinghua Collaborative Research Seed Project. Dr. Wang’s research trends emphasize ionospheric analysis, robust positioning algorithms, and sensor fusion for autonomous systems. Her articles span disciplines like atmospheric science, data science, and geomatics engineering, addressing challenges in GNSS reliability and real-time navigation integrity. Her advisory and grants section highlights her role in advancing autonomous vehicle technologies and HD mapping. She is part of research teams utilizing advanced facilities at UNSW’s Mark Wainwright Analytical Centre and collaborates on global navigation challenges.

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Renjie Liaoمشاهده پروفایل

استادیار

University of British ColumbiaCanada

Renjie Liao is an Assistant Professor (tenure-track) in the Department of Electrical and Computer Engineering (ECE) at the University of British Columbia (UBC), with an associated appointment in the Department of Computer Science. He is also a Faculty Member at the Vector Institute and a Canada CIFAR AI Chair. Prior to UBC, Dr. Liao was a Visiting Faculty Researcher at Google Brain and held a Senior Research Scientist position at Uber Advanced Technologies Group during his PhD. He earned his B.Eng. (Automation) from Beihang University, M.Phil. (CS) from the Chinese University of Hong Kong, and PhD (CS) from the University of Toronto. His research focuses on probabilistic and geometric deep learning , with key contributions in deep generative models, geometric deep learning, neural algorithmic reasoning, and generalization bounds. Notable areas include 3D point cloud analysis, self-driving systems, and healthcare applications using graph neural networks. His work bridges theoretical foundations (e.g., PAC-Bayes bounds) with practical applications like motion forecasting and medical imaging. Education: B.Eng. in Automation, Beihang University (2011) M.Phil. in Computer Science, CUHK (2015) PhD in Computer Science, UofT (2021) Dr. Liao has received awards such as the RBC Graduate Fellowship and Connaught International Scholarship. His lab (Deep Structured Learning Lab) emphasizes principled mathematical approaches to solving complex problems. He advises students in machine learning, computer vision, and robotics, encouraging applications from those with strong coding/mathematical backgrounds. Labs/Teams: Deep Structured Learning Lab (UBC) Vector Institute Collaboration

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Aurélien ALFONSIمشاهده پروفایل

استاد

École des Ponts ParisTechFrance

Aurélien ALFONSI is a Professor at École des Ponts ParisTech and Director of the Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique (CERMICS). His primary affiliation is within the Mathematical and Computer Engineering Information department. He also holds a teaching position at the École Polytechnique, where he leads the Finance course in the Master’s program in Mathematics and Applied Computer Science. He specializes in Numerical Probability , Financial Computing , and Mathematics , with a focus on stochastic processes, optimal transport, and computational finance. His work bridges theoretical developments (e.g., Wasserstein distance analysis, stochastic Volterra equations) with practical applications in derivative pricing, risk management, and climate finance. ALFONSI’s research emphasizes high-order numerical schemes for stochastic models (e.g., Heston, Cox-Ingersoll-Ross processes) and innovative methods for solving complex financial and mathematical problems, such as the stochastic sewing lemma and dual approaches to option hedging. His contributions span Monte Carlo methods, volatility modeling, and the interplay between stochastic calculus and optimal transport theory. Though no specific awards are listed, his prolific publication record reflects sustained academic engagement. His role as department director suggests leadership in research and educational initiatives. He actively collaborates on projects involving financial engineering, climate derivatives, and computational methods for stochastic systems.

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Jean-Michel PEREIRAمشاهده پروفایل

استاد

École des Ponts ParisTechFrance

Jean-Michel PEREIRA is a Professor at École nationale des ponts et chaussées, serving as Deputy Chairman of the Civil Engineering and Construction Department and a researcher at the Navier Laboratory. He holds a Doctorate in Civil Engineering (2005) and a Habilitation to Supervise Research (2014). His expertise lies in geomechanics, focusing on energy production-related challenges such as geotechnical heat exchangers, CO2 geological storage, and hydrocarbon production. He teaches soil and rock mechanics, emphasizing advanced geotechnical studies. His research explores coupled thermal-hydro-mechanical behaviors of soils, with applications in energy geotechnics and sustainable infrastructure. Recent studies include experimental and numerical analyses of energy piles, frost heave dynamics, and multiphase flow in porous media. Collaborations involve advanced imaging techniques (MRI, X-ray tomography) to study material behavior at microstructural scales. Key contributions include advancing understanding of geothermal systems, CO2 storage mechanics, and structural responses under thermal cycling. His work bridges fundamental geomechanics with practical engineering solutions for energy transition challenges.

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Mark Simonlehnerمشاهده پروفایل

پژوهشگر

St. Pölten University of Applied SciencesAustria

Mark Simonlehner is a Junior Researcher at the Institute of Health Sciences, Department of Health Sciences at Steyr University of Applied Sciences. His work focuses on applying virtual reality (VR) and advanced motion capture technologies to study human movement biomechanics and rehabilitation engineering. He holds an MSc in Biomedical Engineering and has contributed to projects such as VReeze, ULTRASKEL3D, and ReMoCap-Lab, exploring applications of VR in healthcare and motion analysis. Education: Master's in Health and Rehabilitation Technology (2017–Present), Bachelor's in Biomedical Engineering (2013–2017). Prior to academia, he worked as a carpenter and attended the Holztechnikum Kuchl (2004–2009). Research interests include gait analysis, wearable sensor technologies, and improving clinical assessment methods through VR. His publications emphasize the effects of VR on dynamic balance, motion variability, and joint alignment in rehabilitation contexts. Key collaborations involve studies on exergame development for physical activity promotion and biomechanical validation of VR systems against traditional force plate measurements. His work bridges clinical needs with innovative engineering solutions in health sciences.

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Laurent Saloff-Costeمشاهده پروفایل

استاد

Cornell UniversityUnited States

Laurent Saloff-Coste is the Abram Rogers Bullis Professor of Mathematics at Cornell University , affiliated with the College of Arts and Sciences . His research focuses on analysis , probability theory , stochastic processes , and their interplay with Riemannian geometry and geometric group theory . He explores heat diffusion on manifolds, random walks on groups (both finite and infinite), and quantitative estimates for ergodic Markov chains. Education: Ph.D. in Mathematics (1983), Université Paris VI Doctorat d'État (1989), Université Paris VI Research Interests: His work bridges analysis and probability, studying properties of heat kernels, potential theory, and functional inequalities. He investigates geometric aspects of large-scale structures, such as Cayley graphs, and the relationship between group algebraic properties and random walk behavior. Key areas include: Heat kernel estimates on manifolds and graphs Isoperimetric profiles and their applications Mixing times of Markov chains Sub-elliptic diffusions on Lie groups Recent Trends in Publications (2023–2025): His recent work emphasizes geometric analysis of heat kernels, long-range random walks on nilpotent groups, and functional inequalities. He explores applications to stochastic processes on discrete and continuous spaces, including studies of Lévy processes on nilpotent groups and transient subgraphs. Notable themes include: Estimates for hitting times and Harnack inequalities Perturbation methods for Dirichlet eigenfunctions Uniform doubling properties in Lie group geometries Awards: 2022 Simons Fellow Advising and Grants: No specific advisees or grant details are listed in the provided materials. His research has been supported by collaborations with institutions like the Institute of Mathematics in Wrocław, Poland, and participation in events such as the Midwest Probability Colloquium. Labs/Teams: No dedicated lab or team is explicitly mentioned, though his work involves interdisciplinary collaborations in geometric analysis and probability.

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Erich Walter Farkasمشاهده پروفایل

دانشیار

University of ZurichSwitzerland

Erich Walter Farkas is an Associate Professor of Quantitative Finance at the University of Zurich (UZH) and an Associate Faculty member at ETH Zurich's Department of Mathematics. He serves as Program Director for the joint UZH-ETH Zurich Master of Science in Quantitative Finance, established to bridge expertise in finance and mathematics. His research focuses on risk management, sustainable investments, and mathematical finance, emphasizing holistic approaches that integrate quantitative analysis with behavioral factors. Education: Farkas earned his doctorate and habilitation in Germany, later moving to Switzerland. He holds a Master's and Licentiate in Mathematics from the University of Bucharest, and a Certificate in Advanced Studies for Board Members from Bern-Rochester. Research Interests: Mathematical Finance, Quantitative Risk Management, Volatility Modeling, Sustainable Investment Impact, and Risk Measures. He leads projects like the Data-Driven Financial Risk (DaDFiR3) initiative and co-initiated the Finance Roundtable 2025 on AI and Big Data in finance. Advising & Grants: Supervises theses in quantitative finance and risk management. Active in organizing conferences such as ETH Risk Days and serves on boards like the Swiss Risk Association and Swiss Finance Institute. Professional Roles: Member of the Executive Education Board at UZH, Director of the Teaching Center at the Department of Finance, and founder of the Swiss Risk Association. His work bridges academia and industry, emphasizing practical applications of theoretical frameworks.

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IMMACULATE OLIVAمشاهده پروفایل

دانشیار

Sapienza University of RomeItaly

Immaculate Oliva is an Associate Professor at the Department of Methods and Models for Economy, Territory and Finance within Sapienza University of Rome's Faculty of Economics. She teaches Quantitative Finance, Methods and Models for Finance, and Financial Mathematics courses for undergraduate and graduate programs in Finance and Economics. Her office hours are held weekly on Mondays from 14:30 to 16:30, available both in-person and remotely via scheduled appointments. Her research specializes in mathematical finance with focus areas including: Optimal portfolio allocation in continuous-time models Derivative valuation and structured products design Counterparty credit risk management frameworks Portfolio insurance strategies (CPPI/TIPP) Stochastic processes with jumps and co-jumps Actuarial solutions for longevity risk Recent publications (2020-2025) demonstrate strong focus on portfolio insurance mechanisms, derivatives pricing under jump diffusion models, counterparty risk quantification, and computational methods for financial equations. Her work frequently combines theoretical rigor with practical applications in energy markets, pension systems, and cryptocurrency trading. She coordinates research projects including: Facing emerging risks: an actuarial perspective Actuarial and financial risk management solutions in a pandemic mortality framework and supervises thesis students through structured guidance documented in her Vademecum.

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David Glavind Skovmandمشاهده پروفایل

دانشیار

University of CopenhagenDenmark

David Glavind Skovmand is an Associate Professor in Financial Mathematics at the Department of Mathematical Sciences, University of Copenhagen. He specializes in interest rate modeling, pricing of derivatives, and risk management. Education: PhD (2008) and MSc in Economics (2004) from Aarhus University His research focuses on mathematical modeling of benchmark interest rates like LIBOR, SOFR, and ESTER. Key areas include transition risk, multicurve term structures, and backward-looking benchmarks. He applies stochastic processes and numerical analysis to derivative pricing and risk assessment. Recent publications analyze LIBOR transition complexities, SOFR term structure dynamics, and multicurve frameworks. His work emphasizes practical implications for financial markets and regulatory compliance. Skovmand also teaches and supervises in mathematical finance, financial econometrics, and numerical analysis. He serves as Head of Studies at his department and contributes externally as a lecturer at Copenhagen Business School and Reykjavík University.

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