Maximilian Egger is a Doctoral Researcher at the Institute for Communications Engineering under Prof. Antonia Wachter-Zeh at the Technical University of Munich (TUM). His research focuses on distributed machine learning, privacy-preserving computing, and information theory. He holds an M.Sc. in Electrical Engineering and Information Technology (2022, TUM) and a B.Eng. in Electrical Engineering (2020). He has conducted research stays at École Polytechnique Fédérale de Lausanne (2024) and Imperial College London (2023). Egger has received several awards, including the DAAD Scholarship (2023) and the VDE Award Bavaria (2020). His work emphasizes secure federated learning, Byzantine-resilient systems, and efficient distributed algorithms. He is affiliated with the Chair of Coding and Cryptography and actively contributes to advancements in decentralized learning systems. Recent publications highlight breakthroughs in privacy preservation, channel capacity estimation, and scalable federated edge learning.
Professor Line Roald is a faculty member in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison. Her research focuses on power system optimization, renewable energy integration, grid resilience, and wildfire risk mitigation using stochastic optimization and data-driven methods. Education : PhD (2016), MS (2012), BS (2009) from ETH Zurich Key Research Areas : Power Systems Optimization, Renewable Energy Integration, Wildfire Risk Mitigation, Stochastic Programming, Grid Decarbonization Her work addresses critical challenges in sustainable energy systems, including balancing grid efficiency and risk, optimizing electrolyzer scheduling for flexibility, and predicting cascading blackout severity using graph neural networks. She has developed frameworks for carbon intensity comparison and wildfire risk assessment in power systems. Scientific Awards : 2024 Inclusion, Equity and Diversity in Engineering Award 2024 Vilas Faculty Early Career Investigator Award 2023 IEEE Power Tech Best Student Paper Award 2021 NSF CAREER Award 2019 MTLE Fellow Professor Roald mentors graduate students and teaches courses including Introduction to Optimization and On-Line Control of Power Systems . Her publications highlight innovative approaches to grid security, carbon-efficient energy markets, and climate resilience in infrastructure systems.
Travis Desell is a Professor in the Department of Software Engineering at Rochester Institute of Technology (RIT), part of the B. Thomas Golisano College of Computing and Information Sciences. His research focuses on data science and machine learning applied to large-scale datasets using high-performance and distributed computing. He specializes in neuro-evolution, combining evolutionary algorithms with neural networks, particularly through his EXACT and EXAMM algorithms. He leads the D2S2 Lab and has developed the SALSA programming language based on the actor model. Currently funded projects include the National General Aviation Flight Information Database (NGAFID) and an NSF award exploring contextual bandits for decision-making in cyber-physical systems. His work emphasizes practical scientific applications, including stock forecasting, power plant data prediction, and explainable time series models. Education details are not explicitly provided, but his roles and publications indicate advanced academic credentials. Research interests span neuro-evolutionary techniques, recurrent neural networks, and distributed computing frameworks. Key projects include EXAMM for time series forecasting and NGAFID for flight safety analysis. Collaborations involve students and teams at RIT and beyond, with a focus on advancing AI-driven solutions in dynamic environments. Lab affiliations include the D2S2 Lab, where he mentors students and conducts cutting-edge research. Current opportunities exist for PhD students with backgrounds in software engineering and expertise in areas like NLP, web development, and distributed systems.
Stefan Krastanov is an Assistant Professor at the University of Massachusetts Amherst, focusing on quantum hardware design, control, and optimization across multiple layers of quantum computing and networking technologies. His work bridges physical hardware descriptions with logical circuit compilation, emphasizing resilience in noisy quantum systems. Research Interests include Quantum Hardware Design, Entanglement-Based Networking, Quantum Error Correction, and Modeling Software for Quantum Systems. His primary lab is the Quantum Information Lab , with affiliations to the Advanced Classical and Quantum Information Research Lab. Recent work trends highlight advancements in quantum repeater networks, error-corrected compilation, and photonic neural networks. His publications span topics like non-Markovian dynamics simulation, NP-hard optimization in quantum dot arrays, and scalable spin quantum memory control. Labs and Teams: Quantum Information Lab (leading experimental/theoretical work) and collaborations through the Advanced Classical and Quantum Information Research Lab.
Dr. Liu Yang is an Associate Professor jointly appointed in the Department of Civil and Environmental Engineering and the Department of Industrial Systems Engineering and Management at the National University of Singapore (NUS). She holds a B.S. from Tsinghua University, an MPhil from the Hong Kong University of Science and Technology, and a Ph.D. from Northwestern University. Her research focuses on urban mobility and transport systems, including ridesharing, carsharing, traffic congestion management, and data-driven modeling. She leads the Lab for Urban Mobility Systems (LUMOS), comprising 15 members. Dr. Liu serves on editorial boards of journals like Transportation Science and Transportation Research Part C, and holds leadership roles in professional organizations such as the Chinese Overseas Transportation Association (COTA). Her work has been published in top journals including Transportation Research Part A/B/C/E and Transportation Science. Key awards include the CICTP Best Area Editor Award (2022) and the Faculty Teaching Excellence Award (2022). Her research is funded by agencies like the US Federal Highway Administration and Singapore's Ministry of Education. Education: B.S., Civil Engineering, Tsinghua University (2005) M.Phil., Civil Engineering, Hong Kong University of Science and Technology (2007) Ph.D., Transportation System Analysis and Planning, Northwestern University (2013) Professional Activities: Associate Editor, Transportation Science Co-Chair, WTC Shared Logistics and Transportation Systems Committee Member, Transportation Research Board Committee AP020 and AEP40 Her publications emphasize optimization, dynamic systems, and policy analysis in transportation networks. Recent work explores autonomous vehicles, incident-responsive traffic management, and shared mobility systems. She advises students on topics like ridesharing algorithms and congestion pricing strategies.
Jennifer Williams is a Professor in the Department of Geography at the University of British Columbia (UBC), located on the traditional, ancestral, and unceded territory of the Musqueam People. She holds a PhD from the University of Montana (2008) and a BA from the University of California, Berkeley. Her primary research focuses on understanding how interacting ecological and evolutionary processes influence species distributions and abundances, particularly in the context of global environmental changes like climate change, habitat fragmentation, and biological invasions. Her work integrates field experiments, observational studies, and mathematical modeling to address conservation challenges. Her current research themes include eco-evolutionary dynamics of range expansion, species interactions in Garry oak savannas, plant life history responses to climate change, and invasive species management. She received the prestigious Killam Research Fellowship in 2020, recognizing her contributions to biodiversity and climate science. Williams teaches courses in geography and ecology, and her lab actively collaborates with the Biodiversity Research Centre. Her recent work emphasizes forecasting species' responses to climate change and developing strategies for ecosystem resilience.
David R. Just is a Professor and Director of Graduate Studies at the Charles H. Dyson School of Applied Economics and Management at Cornell University. He holds a Ph.D. (2001) and MS (1999) from the University of California, Berkeley, and a BA (1998) from Brigham Young University. His research focuses on behavioral economics, examining how environmental and psychological factors influence economic decisions, particularly in food choices and agricultural contexts. His work on school lunch programs and low-cost behavioral nudges has been widely recognized. He co-directs the Cornell Center for Behavioral Economics in Child Nutrition Programs. Key research interests include the application of behavioral insights to public health, consumer decision-making, and agricultural policy. His studies often combine field experiments with econometric analysis to address real-world challenges, such as improving food accessibility and sustainability. His work has been featured in prominent media outlets and has influenced policy initiatives in food systems and nutrition. Roles: Professor, Director of Graduate Studies, Co-Director of Cornell Center for Behavioral Economics in Child Nutrition Programs. Education: Ph.D. and MS in Agricultural and Resource Economics (UC Berkeley), BA in Economics (BYU). Research: Behavioral economics, food policy, agricultural decision-making, and sustainable practices. Affiliations: Cornell SC Johnson College of Business, College of Agriculture and Life Sciences.
Dr Won-Ki Seo is a Senior Lecturer in the School of Economics at the University of Sydney. His research focuses on time series analysis, econometric theory, and functional data analysis. He holds a Ph.D. in Economics from the University of California, San Diego. Research Interests: Dr Seo's work centers on cointegration analysis in functional spaces, Hilbertian processes, and the application of advanced mathematical frameworks to econometric problems. His recent studies explore tail behavior of Lévy processes, functional principal component analysis, and nonlinear time series modeling. Recent work includes analyzing stopped Lévy processes with Markov modulation and developing methodologies for functional time series inference Key contributions to cointegration theory in Banach spaces and functional data econometrics Dr Seo has published extensively in top journals like Econometric Theory and Journal of Time Series Analysis . His research bridges theoretical econometrics and practical applications in financial and environmental economics. Contact: won-ki.seo@sydney.edu.au | Office: A02 Social Sciences Building
Dr. Aaron Schurger is an Assistant Professor in the Psychology Department at Chapman University’s Crean College of Health and Behavioral Sciences. He is also a member of the Institute for Interdisciplinary Brain and Behavioral Sciences. Schurger holds a BA from Indiana University, and MA and PhD from Princeton University. His research focuses on the neuroscience of volition, consciousness, and decision-making, particularly exploring the readiness potential (RP) and its implications for free will debates. His work challenges classical interpretations of the RP using computational models, suggesting it reflects stochastic neural processes rather than preconscious decisions. Recent contributions include studies on the origins of the RP in spiking neural networks, critiques of causal structure theories of consciousness, and interdisciplinary analyses of free will. His findings emphasize that the RP may not indicate preconscious decision-making but instead arise from natural neural fluctuations during decision thresholds. Schurger collaborates across neuroscience, philosophy, and cognitive science, contributing to debates on consciousness, action initiation, and neural correlates of subjective experience. His research also addresses methodological rigor in studying unconscious processing and integrates computational models with empirical data, as seen in studies on movement timing and neural stability during perception. While no specific grants or labs are explicitly listed, his affiliations suggest involvement in interdisciplinary projects at Chapman.
Johanna Ziegel is a Professor of Statistics at ETH Zurich, Switzerland, since 2024, and a Visiting Scientist at the Heidelberg Institute for Theoretical Studies (HITS). Previously, she held positions at the University of Bern, where she was promoted to Full Professor in 2023. Her research focuses on decision-theoretically sound methods for forecast evaluation, probabilistic forecasting, risk measures in finance, and applications in meteorology, medicine, and climate science. She is actively involved in editorial roles for journals like Bernoulli , JASA: Theory & Methods , and SIAM Journal on Financial Mathematics . Education: PhD in Stereological Analysis of Spatial Structures from ETH Zurich (2010), supervised by Paul Embrechts and Eva B. Vedel Jensen. Postdoctoral research at the University of Melbourne and Heidelberg University. Research Interests: Forecast evaluation, elicitable functionals, risk measures, isotonic regression, statistical calibration, and applications in finance, climate science, and biostatistics. Her work bridges theoretical statistics with practical challenges in uncertainty quantification and decision-making under uncertainty. Advising & Collaborations: Supervised 7 PhD students and mentored several postdocs. Collaborates with the Computational Statistics group at HITS and the Oeschger Centre for Climate Change Research. Her group explores distributional regression under order constraints and novel methods for forecast comparison. Recognition: Credit Suisse Award for Best Teaching (2022), H.I.T. Program for Academic Leadership (2021–2022). Active in professional service, including the Bernoulli Society Council and editorial boards.
Endre Süli is a Professor of Numerical Analysis at the University of Oxford, affiliated with Worcester College and Linacre College. He has held various academic roles since 1985, including Fellowships and Tutorships in Mathematics. University Education: B.Sc. in Mathematics, University of Belgrade (1974-1978) M.Sc. in Mathematics, University of Belgrade (1978-1980) Ph.D. in Mathematics, University of Belgrade (1985) M.A., University of Oxford (1985) British Council Visiting Student, Reading University and University of Oxford (1983/84) Süli's research focuses on numerical methods for partial differential equations (PDEs), with expertise in finite element methods, adaptive algorithms, error control, and computational modeling of fractures and non-Newtonian fluids. His work bridges mathematical theory and practical applications in fluid dynamics and material science. His recent publications emphasize finite element approximations, nonlinear PDEs, and stochastic models for polymer dynamics. Themes include multiscale methods, tensor-sparsity for high-dimensional problems, and compressible flow simulations. Scientific Awards: Fellow of the Royal Society (2021) London Mathematical Society Naylor Prize and Lectureship (2021) Pro Urbe Prize, City of Subotica (2021) SIAM Fellow (2016) Member, Academia Europaea (2020) Foreign Member, Serbian National Academy of Sciences and Arts (2009) IMA Service Award (2011) Fellow, European Academy of Sciences (EurASc) (2010) Fellow, Institute of Mathematics and its Applications (2007) London Mathematical Society/New Zealand Mathematical Society Forder Lecturer (2015) Professor Hospitus, Charles University, Prague (2012) Distinguished Visiting Chair Professor, Shanghai Jiao Tong University (2013) Invited Speaker, International Congress of Mathematicians, Madrid (2006) Süli has supervised numerous research projects and held visiting appointments globally. His contributions to numerical analysis span foundational work on error estimation, nonlinear stability, and advanced computational frameworks for complex physical systems.
Marco Di Renzo is a CNRS Professor (Directeur de Recherche Titulaire) at University of Paris-Saclay, affiliated with CentraleSupelec and the Signals and Systems Laboratory (L2S). He serves as Coordinator of the Communications Networks Area at the DigiCosme Laboratory of Excellence and Editor-in-Chief of IEEE Communications Letters. His academic leadership includes membership in the Ph.D. School on ICT Admission Committee at Paris-Saclay University. His educational background includes a Laurea (cum laude) and Ph.D. in Electrical Engineering from University of L'Aquila, Italy (2003, 2007), and a Habilitation à Diriger des Recherches from University Paris-Sud (2013). Laurea (cum laude), Electrical Engineering, University of L'Aquila (2003) Ph.D., Electrical Engineering, University of L'Aquila (2007) Habilitation à Diriger des Recherches, University Paris-Sud (2013) Di Renzo's research focuses on next-generation wireless communications, particularly reconfigurable intelligent surfaces (RIS), 6G technologies, and stochastic geometry modeling. His work bridges theoretical communication theory with practical implementations in cellular networks, millimeter-wave communications, and ultra-wide band systems. Recent publications demonstrate leadership in holographic metasurfaces, integrated sensing and communication (ISAC), and AI-empowered network design, establishing him as a pioneer in electromagnetic wave manipulation for future networks. His award-winning publications span RIS-aided communications, channel modeling, and security frameworks. Analysis of his recent work reveals consistent focus on three pillars: (1) fundamental electromagnetic theory for wave manipulation, (2) practical RIS implementations across frequency bands, and (3) integration with AI for network optimization. His articles frequently address industrial applications including factory automation and space-air-ground networks. Di Renzo's scientific recognition includes: IEEE Fellow (2020) and IET Fellow (2020) Highly Cited Researcher (Web of Science, 2019) SEE-IEEE Alain Glavieux Award (2017) Multiple Best Paper Awards (IEEE ICC, EURASIP) Nokia Foundation Visiting Professorship (2020) As Principal Investigator for CNRS, he coordinates multiple Horizon 2020 projects including SURFER, PathFinder, and MetaWireless. His leadership extends to serving as Project Coordinator for H2020 5Gwireless, 5Gaura, MAPNET, and REDESIGN. With over 350 publications, 17,000+ citations, and h-index of 66+, his research group maintains strong industry partnerships with Nokia and other telecommunications leaders. Di Renzo directs the Signals and Systems Laboratory (L2S) at Paris-Saclay and coordinates the DigiCosme Excellence Lab's Communications Networks Area. His team specializes in electromagnetic modeling for wireless networks and has pioneered the European Telecommunications Standards Institute (ETSI) Industry Specification Group on RIS. The group maintains active collaborations with Aalto University (Finland), University of Technology Sydney (Australia), and University of L'Aquila (Italy).
Jianhua Zhang is a Professor of Computer Science and founding deputy head of the AI Lab at the Department of Computer Science, OsloMet - Oslo Metropolitan University, Norway. He holds affiliations with the Faculty of Technology, Art and Design. His career includes roles as Scientific Director at Vekia (France), Head of Machine Learning Lab, and Professorships at East China University of Science and Technology and Beijing University of Technology. He has held visiting positions at TU Berlin, TU Dresden, and the University of Catania. Educations: PhD in Electrical Engineering and Information Sciences (Ruhr University Bochum, 2005), Postdoctoral Research at the University of Sheffield (2005-2006). Research focuses on artificial intelligence, computational intelligence, cognitive human-machine systems, neuroergonomics, affective computing, and AI-driven neuroergonomics. Applications span engineering, biomedicine, finance, and business. He has led over 20 large-scale projects and published extensively (4 books, 13 chapters, ~200 papers). Leadership roles include Chair of IFAC Technical Committee on Human-Machine Systems (2017-2023), Vice Chair of IEEE Norway Section, and editorial roles at journals like Frontiers in Neuroscience and Cognitive Neurodynamics . He organized major conferences like IFAC HMS2025 (Beijing) and ICMLT 2024 (Oslo). Awards: Stanford/Elsevier Top 2% Scientists (2023/2024), Senior Research Fellowship (CSC, 2012), Max Planck Fellowship (2011), Shanghai Pujiang Talent (2007), DAAD Scholarship (2002-2004). Grants and advising: PI for 20+ projects, advising PhD students in AI, machine learning, and control systems. Teaching includes courses on computational intelligence, IoT, and fuzzy systems at both undergraduate and graduate levels. Labs/Teams: AI Lab at OsloMet, Machine Learning Lab (Vekia), and collaborations with institutions globally. Current work emphasizes AI ethics, neuroergonomics in smart cities, and adaptive human-machine systems.
Guillermo Ferreyra is a Professor in the Department of Mathematics at Louisiana State University (LSU), where he has served since 1996. He holds a Ph.D. from Rutgers University (1983) and a Licenciado from the Universidad de Córdoba, Argentina (1977). His research focuses on Deterministic and Stochastic Control Theory, Partial Differential Equations, Probability Theory, and Financial Mathematics. Ferreyra has held significant administrative roles, including Associate Dean for Science Education (2012–present), Deputy Superintendent of the Office of STEM at the Louisiana Department of Education (2010–2012), and Dean of the College of Arts and Sciences at LSU (2004–2009). He has led initiatives to enhance STEM education, including professional development programs for K-12 teachers and strategies to improve 8th-grade math achievement. Ferreyra’s academic contributions include over 30 journal articles and co-edited volumes on evolution equations and control theory. He has advised five Ph.D. students and secured millions in grants for interdisciplinary research and educational initiatives. His administrative achievements at LSU include expanding faculty diversity, improving student advising, and fostering interdisciplinary programs such as the China Initiative. He has also contributed to statewide education reforms, including planning for the Common Core State Standards. Ferreyra is a member of the American Mathematical Society and has served on national evaluation committees and grant review panels. Publications highlight his work in stochastic control, free boundary problems, and applications to finance and advertising models. His research bridges theoretical mathematics with practical applications, such as the mathematical underpinnings of the 1997 Nobel Prize in Economics for the Black-Scholes formula.
Goran Avlijaš is a researcher affiliated with Singidunum University in Belgrade, specializing in project management, operations research, and retail logistics. He holds a Doctorate in Engineering Management (2011–2016) from Singidunum University, a Master’s in Project Management (2008–2009) from the Faculty of Organizational Sciences, and a Bachelor’s in Management (2003–2007) from the same institution. His research focuses on optimizing project schedules through methods like Earned Value Management and Monte Carlo Simulation, analyzing supply chain efficiency, and exploring gig economy impacts on well-being in Balkan countries. Key research areas include: Project Management Innovation: Developing risk analysis tools (e.g., Event Chain Methodology) and applying earned value metrics to construction projects. Retail Operations: Investigating automated replenishment systems and inventory management challenges in retail environments. Social-Economic Dynamics: Studying gig economy effects on workforce well-being and regulatory impacts on entrepreneurship. His work spans 30+ peer-reviewed articles and conference papers, including contributions to Management , Sustainability , and Frontiers in Psychology . He co-authored textbooks like Project Management and Entrepreneurship for Singidunum University’s curriculum. Active in academic events such as Sinteza and FINIZ conferences, he bridges theoretical research with practical industry applications.
