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Ferdian JovanView profile

Assistant Professor

• Mobile Robotics
• Multimodal Learning
• Time Series Analysis
• +11 more

Ferdian Jovan is an Assistant Professor (Lecturer) at the University of Aberdeen, affiliated with the Aberdeen - South China Normal University Joint Institute within the School of Natural and Computing Sciences. He is also a visiting research fellow at the Faculty of Engineering, University of Bristol. PhD in Computer Science, University of Birmingham (2019) MSc in Computational Logic, Technische Universitaet Dresden (2014) BSc in Computer Science, Universitas Indonesia (2010) His research focuses on mobile robotics, multimodal learning, and time series analysis , with applications in service robotics, energy, healthcare, and extreme environments. He is particularly interested in AI systems that function efficiently in dynamic, resource-constrained settings. His expertise bridges statistical machine learning and real-world robotic deployment. His recent publications show a strong trend in applied AI for robotics and health , including work on digital biomarkers for Parkinson’s disease, battery health prediction, multirobot windfarm maintenance, and adaptive planning. These works have been presented at top venues like KDD, IAAI, and published in journals such as Autonomous Robots and Journal of Field Robotics. DAAD AInet Fellow for Human Centered AI (2023) Ferdian advises PhD students and is actively involved in research collaborations across the UK and internationally. He has held research positions at the University of Bristol, Royal Holloway University of London, and the University of Oxford. His work often involves interdisciplinary teams and real-world data, emphasizing robust and deployable AI solutions. He is associated with the Department of Computer Science at the Meston Building, University of Aberdeen, and leads research in intelligent systems for extreme and dynamic environments.

Torkel ErhardssonView profile

Associate Professor

• Probability Theory
• Stochastic Processes
• Statistical Inference
• +7 more

Torkel Erhardsson is an Associate Professor (Docent) in the Department of Mathematics at Linköping University, Sweden. He is affiliated with the Division of Applied Mathematics (TIMA), where he conducts research in probability theory, stochastic processes, and statistical inference. His research interests include: Bounds for distances between probability distributions using Stein's method and couplings Applications to normal and compound Poisson approximations Bayesian nonparametric inference and asymptotics of posterior distributions Higher-dimensional autoregressive processes with random coefficients Reciprocal chains and reciprocal random fields on undirected graphs His recent publications (2008–2023) in journals such as Journal of Applied Probability , Advances in Applied Probability , and IEEE Transactions on Automatic Control reflect a strong focus on theoretical probability and its applications, particularly in approximation methods and stochastic modeling. The work shows increasing emphasis on graphical models and reciprocal processes in recent years. There are no listed scientific awards or honors in the provided materials. Torkel Erhardsson actively contributes to the academic life at Linköping University, participating in seminars in statistics and mathematical statistics. There is no public information indicating student advising, grant funding, or leadership of specific research labs or teams.

Constantine MukasaView profile

Teaching Professor

• Engineering Education
• Diverse and Inclusive Learning Environments
• Wireless Communications
• +3 more

Constantine Mukasa is an Associate Teaching Professor in the First Year Engineering Program at the College of Engineering, Northeastern University. His office is located at 368E Snell Engineering Center (SN), 360 Huntington Avenue, Boston, MA 02115. He is actively involved in initiatives to enhance engineering education through collaborative and inclusive learning environments. His research interests span both engineering education and wireless communications. In education, he focuses on fostering student engagement and diversity in early engineering curricula. In technical domains, his work addresses stochastic modeling of wireless networks, interference analysis, and cognitive radio systems. In 2020, he contributed to College of Engineering (COE) presentations at the ASEE Virtual National Conference, highlighting his involvement in advancing educational and technical scholarship. His publications analyze network performance under diverse fading conditions and interference scenarios, reflecting expertise in signal processing and communication theory. No specific grants or advisees are listed, but his programmatic role suggests significant contributions to undergraduate curriculum development and student mentorship. No dedicated labs or teams are explicitly mentioned in the provided information.

• Applied Mathematics
• Statistics
• Strategy
• +7 more

Prof. Hanqin Zhang is a Professor in the Department of Analytics And Operations at the National University of Singapore (NUS Business School). He holds a Doctor of Science from the Chinese Academy of Sciences (1991) and a Master of Science from Xian Jiaotong University (1985). His research focuses on applied mathematics, statistics, strategy, transportation logistics, control engineering, and numerical methods. He has served as an associate editor for journals like European Journal of Operational Research and TOP , and has reviewed for top-tier journals including Operations Research and Queueing Systems . His recent work addresses optimal inventory policies, queueing systems, and stochastic control, with notable contributions to dual-sourcing strategies, staffing optimization in ticket queues, and fluid models of parallel service systems. He has supervised students in stochastic processes and inventory management, reflecting his expertise in bridging theoretical advancements with practical applications in operations research. Notable research trends include leveraging order-tracking information for inventory systems, analyzing ergodicity in Markov chains, and optimizing multi-source supply chains under uncertainty. His publications span high-impact journals such as Operations Research and Queueing Systems , showcasing a focus on stochastic systems and operations management.

Ruihua LiuView profile

Professor

• Financial Mathematics
• Computational Finance
• Stochastic Optimal Control
• +5 more

Ruihua Liu is a Professor in the Department of Mathematics at the University of Dayton, College of Arts and Sciences. He has been a full-time faculty member since 2004, achieving tenure as Associate Professor in 2010 and promotion to Full Professor in 2016. Educational Background: Ph.D., Engineering Science (Control Theory and Application), Nankai University, China, 1994 Ph.D., Mathematics, University of Georgia, 2001 M.S., Computer Science, University of Georgia, 2001 M.E., Engineering Science, Nankai University, 1988 B.E., Engineering Science, Nankai University, 1985 Ruihua Liu's research lies at the intersection of financial mathematics and stochastic control. His work emphasizes computational finance , particularly in developing numerical methods such as recombining trees and lattice models for pricing options under complex dynamics. A central theme in his research is the use of regime-switching models to capture structural changes in financial markets. He investigates optimal investment and consumption strategies , often incorporating realistic features like proportional transaction costs. His analytical focus includes stochastic optimal control, optimal stopping, and singular control problems, with applications in portfolio optimization and stock liquidation strategies. The 15 most recent publications show a consistent trajectory in applying advanced stochastic analysis to financial decision-making under uncertainty. Key trends include the development of computational algorithms for regime-switching frameworks, solving optimal control problems with state-dependent switching rates, and modeling market behaviors using multi-scale and diffusion processes. These works span top journals in applied mathematics, control theory, and financial engineering, indicating a strong interdisciplinary impact. Scientific Awards and Honors: No specific awards mentioned in the provided text. Advising and Grants: While no formal list of students is provided, his extensive publication record with multiple collaborators suggests active involvement in mentoring graduate students and junior researchers. Though specific grants are not listed, his research output in high-impact journals implies successful acquisition of external funding to support his work in financial mathematics and stochastic modeling. Laboratories and Research Teams: Ruihua Liu is affiliated with the Department of Mathematics at the University of Dayton. While no named lab or center is mentioned, his collaborative work with researchers such as G. Yin, Q. Zhang, and P. Eloe suggests participation in a research group focused on stochastic systems and financial applications.

Dimitri ShlyakhtenkoView profile

Professor

• Free Probability Theory
• Von Neumann Algebras
• C*-Algebras
• +6 more

Dimitri Shlyakhtenko is a Professor at the University of California, Los Angeles (UCLA) Department of Mathematics, with a distinguished career in free probability, operator algebras, and von Neumann algebras. He has held leadership roles as Department Chair (2012-2015) and Director of the Institute for Pure and Applied Mathematics (2017-). Ph.D. in Mathematics (1997) from UC Berkeley under Dan-Virgil Voiculescu . B.S. with high distinction from the University of Nevada, Reno (1993). His research spans free probability , von Neumann algebras , C*-algebras , L2-invariants , and Poisson geometry . He has pioneered connections between free probability and random matrix theory, subfactor classifications, and non-commutative transport equations. Recent work includes inequalities for free entropy dimension and duality in non-commutative optimal transport. His 15 most recent publications focus on free entropy dimension, crossed products, non-commutative transport, and classification of von Neumann algebras. Topics include non-microstates free entropy , free group factors , quasi-regular inclusions , and type B free probability , with applications to quantum information and ergodic theory. Scientific Awards : Sloan Foundation Fellowship (2001), NSF Fellowships (1994, 1998), Clay Mathematics Institute award (2002), and Bourbaki Seminar recognition (2004). Organized major conferences at Fields Institute, Oberwolfach, IPAM, and UC Berkeley on quantitative linear algebra, free probability, and von Neumann algebras. He has mentored 12 Ph.D. students, including David Jekel and Max Zhou , with research in free analysis and operator-valued distributions. His work also involves collaborations with leading mathematicians like Alain Connes and Sorin Popa .

Owen JonesView profile

Professor

• Operational Research
• Stochastic Modeling
• Environmental Science
• +7 more

Professor Owen Jones is a Chair in Operational Research at the School of Mathematics, Cardiff University. His work focuses on applying mathematical modeling and optimization techniques to address challenges in environment, energy, and sustainability, including renewable energy systems, water management, and disaster risk quantification. Operational Research Stochastic Modeling Environmental Data Analysis Renewable Energy Optimization His research spans environmental science, hydrology, and computational methods, with recent work leveraging approximate Bayesian computation (ABC) and generative adversarial networks (GANs) to model climate impacts, water systems, and biological dynamics. Articles highlight innovations in wastewater surveillance, bat roost detection, and tidal energy optimization. Professor Jones supervises advanced students in areas like spatio-temporal modeling, emergency response simulation, and multifractal processes. He has secured grants for interdisciplinary projects, including UKRO-funded freshwater solutions, GCRF wastewater monitoring, and EU Horizon2020 climate adaptation initiatives. He is part of the Operational Research group at Cardiff University and has collaborated with institutions such as the Australian Department of Agriculture, Fisheries and Forestry, and the EU Horizon2020 program.

• Risk Theory
• Actuarial Mathematics
• Bankruptcy Theory
• +4 more

Χατζηκωνσταντινίδης Ευστάθιος is a Professor at the University of Piraeus in the Department of Statistics and Actuarial Science. His academic career spans decades with significant contributions to actuarial mathematics and statistical theory. He teaches undergraduate courses in Actuarial Mathematics, Risk Theory, and Reliability Theory, and postgraduate courses in Generalized Linear Models and Risk Management. Education: PhD in Mathematics (1990) - Aristotle University of Thessaloniki (Grade: Excellent) BSc in Mathematics (1985) - Aristotle University of Thessaloniki (Grade: Excellent) Research Focus: His work centers on risk theory, bankruptcy modeling, compound Poisson processes, and optimal experimental designs. He has developed innovative approaches to: Perturbed risk models with diffusion processes Copula-based dependence modeling in insurance Gerber-Shiu function analysis for dividend strategies Recursive methods for compound distributions His research bridges theoretical mathematics with practical actuarial applications. Publication Trends: Analytical studies of stochastic processes dominate his recent work, focusing on: Ruin probabilities and deficit distributions Dependence modeling using copulas Optimal dividend strategies Computational methods for risk models Earlier publications emphasize experimental design optimization and reliability theory. Administrative Leadership: Chair of Department of Statistics and Actuarial Science (2007-2009) Director of Postgraduate Program in Actuarial Science & Risk Management Member of Senate of University of Piraeus Deputy Chair of Ministry of Finance's Actuarial Examination Committee Research Projects: Has participated in multiple funded projects including: 'Optimal Experimental Designs' (Greek Ministry of Education) 'Modern Model for Actuarial Studies Preparation' (University of Piraeus) EPEAEK programs on statistical applications

Sajidah AhmedView profile

Researcher

• Plasma Physics
• Nuclear Fusion
• Turbulence
• +2 more

Sajidah Ahmed is a plasma physicist affiliated with the University of York and actively contributes to nuclear fusion research. Her work focuses on turbulent phenomena in magnetically confined fusion plasmas, particularly the dynamics of scrape-off layer (SOL) fluctuations and their impact on plasma-wall interactions. Doctoral research (2023) on Intermittent fluctuations in the boundary of magnetically confined fusion plasmas . Published studies in leading fusion journals on topics such as filament propagation, MHD instabilities, and pulse superposition modeling. Research Highlights: Her research addresses critical challenges for commercial fusion reactors, including: Characterizing blob-like turbulent structures in SOL regions. Reconstructing intermittent time series using deconvolution methods. Investigating density limits and plasma confinement in devices like Alcator C-Mod and MAST Upgrade.

María Ignacia VicuñaView profile

Associate Professor

• Business Analytics
• Quantitative Methods
• Time Series Analysis
• +3 more

María Ignacia Vicuña is an Associate Professor at the School of Administration, Pontificia Universidad Católica de Chile, specializing in Business Analytics and Quantitative Methods. She holds a Ph.D. in Statistics from the same university. Education : Ph.D. in Statistics, Pontificia Universidad Católica de Chile Her research focuses on time series analysis and forecasting, with applications in public health and operational research. Recent work includes modeling ICU demand during the 2021 Chilean COVID-19 pandemic and developing statistical frameworks for epidemic progression. Key trends in her publications: integration of nonlinear time-series models for pandemic scenarios, multivariate quasi-Poisson regression in epidemiology, and methodological advancements in locally stationary processes. Programs : Associated with the MBA and Commercial Engineering programs

Marta LazzarettiView profile

Research Fellow

• Numerical Analysis
• Inverse Problems in Imaging
• Optimization Algorithms in Banach Spaces
• +3 more

Marta Lazzaretti is a Research Fellow at the Department of Mathematics (DIMA) of the University of Genoa. Her work focuses on inverse problems in imaging, numerical analysis, and optimization algorithms in non-standard functional spaces. Affiliation: Department of Mathematics, University of Genoa Academic Rank: Research Fellow Research Interests: Specializing in regularization techniques and numerical optimization, her research spans: Off-the-grid methods for Poisson inverse problems Banach space formulations for geophysical data inversion Stochastic gradient descent in variable exponent Lebesgue spaces Dual descent regularization algorithms Publication Trends: Recent work emphasizes non-Hilbertian optimization frameworks (2023-2025), combining stochastic methods with deterministic regularization for imaging and subsoil inversion applications. Collaborations include Claudio Estatico, Luca Calatroni, and Giuseppe Rodriguez.

Tania KosenkovaView profile

Researcher

• Probability Theory
• Stochastic Processes
• Lévy Processes
• +3 more

Tania Kosenkova is a researcher at the University of Potsdam , affiliated with the Department of Mathematics. Her work centers on advanced topics in probability theory and stochastic processes, particularly focusing on Lévy-type processes, statistical inference, and random dynamical systems under Lévy noise. Her research includes functional limit theorems , characterization of Lévy processes , and transportation distances between Lévy measures . She actively teaches courses such as Statistics for Teacher Education , Stochastic Models , and Limit Theorems for School Teaching , reflecting her dual focus on theoretical and pedagogical applications. Her publications reveal a consistent engagement with Lévy-driven SDEs , jump process analysis , and stochastic approximation schemes . While no formal awards are listed, her work has been featured in journals like Journal of Theoretical Probability and Stochastic Processes and their Applications , often in collaboration with researchers such as A. Kulik and J. Gairing.

• Stochastic Processes
• Probability Theory
• Mathematical Biology
• +3 more

Ilie Grigorescu is an Associate Professor at the University of Miami , affiliated with the College of Arts and Sciences and the Department of Mathematics . He also collaborates with the Computer Science division within the same college. Research Interests: Stochastic Processes Probability Theory Mathematical Biology Evolutionary Modeling Interacting Particle Systems Applied Mathematics Recent Publications focus on branching diffusions, evolutionary fixation times, stochastic game theory, and neuronal phase transitions. His work connects probabilistic models to biological and network systems, including studies on hydrodynamic limits and risk-averse optimal stopping. Contact: Email at i.grigorescu@miami.edu or call (305) 284-2146.

• Information Theory
• Network Security
• Coding Theory
• +7 more

Venkat Anantharam is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley . His research spans Information Theory , Network Security , Coding Theory , and Stochastic Processes , with a focus on theoretical foundations and applications in communication systems, game theory, and data compression. He has supervised numerous PhD and Master’s students , including Soham Phade, Payam Delgosha, and Sudeep Kamath, and hosted postdoctoral fellows such as Lei Yu and Charles Bordenave. His recent publications address advanced topics like hypercontractivity in Boolean functions, universal compression of graphical data, and game-theoretic models for security. Articles from 2019-2021 highlight work on entropy power inequalities, error bounds for Markov chains, and distributed compression techniques. Venkat's research often bridges theoretical insights with practical applications, including LDPC decoders, network coding, and risk-sensitive control.

Fraydoun RezakhanlouView profile

Professor

• Probability theory
• Partial differential equations
• Mathematical analysis
• +7 more

Professor Fraydoun Rezakhanlou is a faculty member at the Department of Mathematics , University of California, Berkeley , where he has been since 1991. His academic roles include serving as an Equity Advisor in the university's Senate Faculty and teaching advanced courses such as Math 270: Topics in Symplectic Geometry , Math 219: Dynamical Systems , and Math 279: Stochastic PDEs . He has also contributed to lecture notes on Symplectic Geometry, Dynamical Systems, and Stochastic PDEs. Research Interests: Rezakhanlou's work spans probability theory , partial differential equations , and their intersections with mathematical physics . His research includes coagulation-fragmentation models , kintetic theory , stochastic processes , and homogenization . He has explored applications to Navier-Stokes equations , Hamilton-Jacobi equations , and symplectic geometry . Article Trends: His publications focus on stochastic PDEs , Hamilton-Jacobi equations , and coagulation models . Recent articles analyze random tessellations , metastability in zero-range processes , and kintetic descriptions of scalar conservation laws. Older works address equilibrium fluctuations , Smoluchowski equations , and random walks in random environments . Advising: He has advised multiple PhD students, including Haotian Gu (2023), Kyeongsik Nam (2020), and Chanwoo Oh (2019), among others since the 1990s.