Dr. Giulia Donati is a Researcher at Eawag – Swiss Federal Institute of Aquatic Science and Technology, affiliated with the Department of Environmental Social Sciences. She holds a PhD from ETH Zürich and has extensive experience in conservation biology, inter/transdisciplinary research, and project management. Her work focuses on social-ecological systems, ecological connectivity, and biodiversity conservation in aquatic and terrestrial ecosystems. Education: PhD (2016–2020, ETH Zürich), MSc (2013–2015, University of Lausanne), BSc (2010–2013, University of Lausanne). Notable roles include postdoctoral research on BlueGreenNet (2021–2024) and Connect-HDL (2020), and leadership in the Save Our Seas Foundation project (2019–2020). Research emphasizes social-ecological networks, blue-green infrastructure, and amphibian connectivity in human-dominated landscapes. Projects like BlueGreenNet and Connect-HDL integrate ecological modeling with stakeholder collaboration to enhance biodiversity. Her work bridges ecology, policy, and urban planning to address global conservation challenges. Publications span topics from clownfish genetics to urban biodiversity frameworks, reflecting interdisciplinary approaches. Active in science communication and policy-relevant research, she collaborates across sectors to foster sustainable solutions. Current affiliations include Eawag’s PEGO research group and the Department of Environmental Social Sciences.
Réka Albert is a Distinguished Professor of Physics at Pennsylvania State University, affiliated with the Eberly College of Science. Her research focuses on the application of network science to biological systems, including signal transduction networks, ecological interactions, and cancer systems biology. She holds editorial roles at npj Systems Biology and Applications , IET Systems Biology , and Bulletin of Mathematical Biology . Education: Ph.D. in Physics from the University of Notre Dame (2001), M.S. and B.S. from Babeș-Bolyai University, Romania (1995-1996). Research Interests: Modeling complex systems using network theory; Boolean network analysis of biological pathways; ecological community dynamics; systems-level understanding of disease mechanisms (e.g., cancer, AML). Her work bridges theoretical physics, computational biology, and experimental data to predict system behavior and therapeutic strategies. Awards: External member of the Hungarian Academy of Sciences (2016), APS Maria Goeppert-Mayer Award (2011), NSF CAREER Award (2007), and Alfred P. Sloan Fellowship (2004). Grants/Support: NSF awards (MCB 1715826, IIS 1814405), ARO MURI on hyperuniform systems, and collaborations with biologists like Sarah Assmann (plant signaling) and Katriona Shea (ecology). Labs/Teams: Leads a multidisciplinary research group at Penn State, mentoring over 20 PhD alumni and current students like Eli Newby and Fatemeh Nasrollahi. Active in developing tools like pystablemotifs for Boolean network analysis.
Manuel Del Pino is Professor at the University of Bath's Department of Mathematical Sciences and Royal Society Professor specializing in nonlinear partial differential equations. His research focuses on singularity formation, geometric evolution equations, and asymptotic analysis in fluid dynamics and mathematical physics. His investigations encompass blow-up phenomena in heat equations, vortex dynamics in Euler flows, and minimal surface theory. Current projects examine infinite-time singularity formation in parabolic equations and asymptotic properties of vortex configurations. Del Pino has received the Royal Society Professorship and leads multiple grants including 'Asymptotic patterns in nonlinear evolution problems' (EPSRC). He maintains collaborations with researchers globally through projects on singularity formation in PDEs.
Johannes Larsch is a tenure-track Assistant Professor at the Center for Integrative Genomics within the Faculty of Biology and Medicine at Université de Lausanne (UNIL). His research focuses on understanding the neuronal mechanisms underlying social interactions, using larval zebrafish as a model organism. He employs advanced techniques like virtual reality and optical imaging to study how social signals are processed in the brain. Education: Bachelor of Biology, University of Konstanz, Germany PhD in Neurobiology, Rockefeller University, USA (lab of Cori Bargmann) Postdoc at Max Planck Institute of Neurobiology, Germany (with Herwig Baier) Research interests center on neuronal circuits driving group behavior, social recognition, and the interplay between genetics and environment in shaping behavior. His lab investigates how individual brains coordinate collective social behaviors through studies of neuronal activity and circuit dynamics. Current lab openings include fully funded PhD and PostDoc positions focused on social neuroscience and neurogenomics. Contact: johannes.larsch@unil.ch .
Evangelos Katsanos is an Associate Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU), where he contributes to research and education in structural engineering and safety. He is affiliated with the Structures and Safety research group and actively supervises PhD students. His work spans advanced computational methods for structural monitoring and risk assessment. Research Interests: His expertise lies in structural dynamics, modal analysis, state estimation, and structural health monitoring of civil and offshore infrastructure. He applies physics-informed models and data-driven techniques to assess structural response under extreme loading conditions such as earthquakes, storms, and wave impacts. His research integrates finite element modeling with Kalman filtering methods for enhanced system identification and damage detection. The recent publications highlight a strong trend toward physics-informed and data-driven structural health assessment, particularly for offshore and wind energy infrastructure. Topics include joint input-state estimation, slamming loads on offshore jackets, and damage identification using Kalman filters. These works emphasize robust modeling under uncertainty and real-world applicability in extreme environments. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: Evangelos Katsanos is the main supervisor of PhD student Al-Hagri, A., and co-supervisor or collaborator on several research projects. He is Principal Investigator (PI) or co-PI on multiple funded research initiatives, including projects on physics-informed structural health assessment of offshore infrastructures, residual bearing capacity of damaged concrete beams, and quality assurance for construction 3D printers. These projects reflect his leadership in interdisciplinary and applied research with societal impact. Labs and Teams: He is part of the research environment at DTU Construct, specifically within the Structures and Safety group, which focuses on resilience, risk assessment, and advanced monitoring of civil and mechanical systems. His collaborations extend to national and international partners in offshore and wind energy engineering.
Kristofer Pister is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He co-directs the Berkeley Sensor and Actuator Center (BSAC) and the Ubiquitous Swarm Lab. His career spans groundbreaking innovations in Micro/Nano Electro Mechanical Systems (MEMS), Control Systems, and Low-Power Circuits, with a focus on Smart Dust and synthetic insects. Education: Ph.D. and M.S. in EECS from UC Berkeley (1992, 1989); B.A. in Applied Physics from UC San Diego (1986). His research areas include MEMS , Control Systems , Robotics , and Integrated Circuits , with recent work on self-powered micro-sensors, crystal-free radios, and interplanetary swarm networks. Key awards include the ISA Albert F. Sperry Founder Award (2009) , Alexander Schwarzkopf Prize (2006) , and the NSF CAREER Award (1996) . He has authored numerous influential publications in wireless sensor networks and microrobotics. His lab, Ubiquitous Swarm Lab , explores distributed robotics and swarm intelligence. Pister emphasizes open collaboration in research, ethical conduct in academia, and efficient resource utilization for graduate students.
Paulo Blikstein serves as Associate Professor of Communications, Media and Learning Technology Design at Columbia University. Previously, he was Assistant Professor of Education and (by courtesy) Computer Science at Stanford University and co-founded the Lemann Center for Brazilian Education (2008-2018). Education: Ph.D. in Learning Sciences, Northwestern University (2009) M.A. in Media Arts & Sciences, MIT Media Lab (2002) M.Eng. in Electronic Engineering, University of São Paulo (2000) B.S. in Metallurgical Engineering, University of São Paulo (1998) His research pioneers constructionist learning environments through digital fabrication, educational robotics, and tangible interfaces—focusing on equitable access for underserved communities. Inspired by Paulo Freire and Seymour Papert, he develops open-source tools like the GoGo Board robotics platform and leads the global FabLab@School initiative establishing fabrication labs in schools across four continents. Current work emphasizes multimodal learning analytics to study student interactions in maker-centered classrooms. Publications reveal strong focus on democratizing invention through maker education, with recurring themes in constructionist theory application, multimodal assessment, and context-specific technology adaptation. Brazilian education reform and low-cost computational solutions form significant threads, particularly in 2016-2017 publications. Scientific Awards: Two Google Faculty Awards National Science Foundation Early Career Award (highest U.S. government honor for early-career scientists) Blikstein directs the Transformative Learning Technologies Lab (TLTL) and co-founded Stanford's Center for Educational Entrepreneurship and Innovation in Brazil. His FabLearn conference established the first academic forum on Maker Movement applications in education. While specific grant details aren't listed, the NSF CAREER Award signifies major federal research funding. He spearheads the FabLab@School project deploying advanced fabrication labs in K-12 institutions worldwide and founded the FabLearn conference series. His work integrates teams of engineers, educators, and designers to create scalable solutions for resource-constrained learning environments.
Michal Kolesár is a Professor in the Department of Economics at Princeton University , holding this position since July 2020. Previously, he served as Assistant Professor (2014-2020) with dual appointments in Economics and the Woodrow Wilson School (2018-2020), and as Visiting Assistant Professor at MIT (2016-2017). His research focuses on econometrics , particularly causal inference , instrumental variables , nonparametric regression , and robust statistical methods . His work addresses fundamental challenges in high-dimensional data analysis, treatment effect heterogeneity, and finite-sample inference validity. Current projects include developing bias-aware methods for regularized regression and analyzing dynamic causal effects in nonlinear systems. Kolesár's recent publications reveal a strong emphasis on methodological rigor with practical applications. His work spans instrumental variable techniques (addressing contamination bias, weak identification), regression discontinuity designs (discrete running variables, measurement error), and high-dimensional inference (sparsity fragility, honest confidence intervals). Key recurring themes include finite-sample optimality, coverage probability guarantees, and robustness to model misspecification. Fellow of the International Association for Applied Econometrics (2023) Journal of Econometrics best associate editor award (2023) Sloan Research Fellowship (2019) NSF grants for high-dimensional data inference (2021-2025) and nonparametric regression (2016-2019) Graduate Economics Club teaching awards (2017, 2018) As an educator, Kolesár teaches advanced econometrics courses at both undergraduate (ECO 312, ECO 313) and graduate levels (ECO 517, ECO 519, ECO 539b). He serves as Co-editor of the Journal of Business & Economic Statistics (2024-2027) and sits on editorial boards of Econometrica , American Economic Journal: Applied Economics , and others. His professional activities include extensive peer review for top journals and organization of major econometrics conferences including the 2026 Econometric Society Winter Meeting.
Pinar Keskinocak serves as the H. Milton and Carolyn J. Stewart School Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology. She co-founded and directs the Center for Health and Humanitarian Systems, demonstrating leadership in both academic administration and research innovation. Her career includes prior roles as College of Engineering ADVANCE Professor and interim associate dean for faculty development, alongside industry experience at IBM T.J. Watson Research Center. Her educational foundation includes a Ph.D. in Operations Research from Carnegie Mellon University and M.S. and B.S. degrees in Industrial Engineering from Bilkent University. This rigorous training underpins her interdisciplinary approach to complex societal challenges. Dr. Keskinocak's research pioneers operations research applications for societal impact , with dual emphases on health systems and humanitarian logistics . She develops advanced models for infectious disease dynamics (including COVID-19, malaria, and Guinea worm), vaccination strategies, disaster response, and supply chain optimization. Her work uniquely bridges engineering analytics with real-world implementation through partnerships with the CDC, American Red Cross, Carter Center, and Children's Healthcare of Atlanta. Analysis of her 2023-2025 publications reveals intensifying focus on eradication program modeling for polio and Guinea worm, with increasing integration of machine learning for predictive accuracy in vaccine distribution. A pronounced trend addresses health equity through targeted interventions for under-immunized populations in Sub-Saharan Africa, emphasizing resource allocation under constraints and cross-border coordination challenges. Her scientific recognition includes: INFORMS Fellow (2015) NSF CAREER Award (2001) Outstanding Professional Education Award, Georgia Tech (2018) Denning Award for Global Engagement, Georgia Tech (2016) Women in Engineering Excellence Teaching Award (2005) Moving Spirit Award, INFORMS (2005) Dr. Keskinocak has secured extensive project funding through collaborations with federal agencies and NGOs, directing research on pandemic response systems, vaccine logistics, and disaster debris management. While specific advisees aren't publicly cataloged, her leadership in the Center for Health and Humanitarian Systems mentors numerous graduate researchers through interdisciplinary projects. She significantly influences national policy via National Academies committees addressing supply chain resilience and vaccine distribution infrastructure. The Center for Health and Humanitarian Systems operates as a dynamic hub where engineering rigor meets humanitarian action, coordinating multi-institutional teams to develop deployable solutions for global health crises and disaster response systems.
Ville Vuorinen is an Associate Professor at the Department of Energy and Mechanical Engineering, Aalto University. His research focuses on computational fluid dynamics (CFD) in energy technology, particularly using Large-Eddy Simulation (LES) and hybrid LES-RANS approaches with OpenFOAM. Research Interests: Combustion, Turbulence, Hydrogen, Emission Reduction, Biofuels, Marine Engine Hydrodynamics, Primary Atomization, Liquid Cooling. His team explores hydrogen-enriched flames, ammonia combustion, two-phase flows, and virus transmission modeling. Article Trends : Recent work spans hydrogen pre-ignition in engines, LES of ammonia/methanol flames, aerosol transmission in choir rehearsals, atomic layer deposition conformality, underwater noise analysis, and techno-economic waste-to-hydrogen systems. Keywords include combustion modeling, sustainable energy, and cross-disciplinary CFD applications. Scientific Awards Teknologiateollisuus ry Diesel- ja kaasumoottoritoimialaryhmän tunnustusapuraha (2010) Collaborations : Works closely with experimentalists. Advisees include Shervin Karimkashi Arani, Parsa Tamadonfar, Ossi Kaario, and others. Research impacts energy-efficient ships, marine engines, and biomedical applications.
Soumya Dutta is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur (IITK), where he leads the INSIGHT: Intelligent Scientific and Visual Computing of Big Data Research Group. He joined IIT Kanpur in October 2022 after working as a Scientist II at Los Alamos National Laboratory (LANL) from July 2019 to August 2022, and previously as a Postdoctoral Research Associate at LANL from June 2018 to July 2019. His educational background includes a Ph.D. and M.S. in Computer Science and Engineering from The Ohio State University (2011-2018), where he was part of the GRAVITY research group, and a B.Tech. in Electronics and Communication Engineering from West Bengal University of Technology, India (2005-2009). Research Interests: Dr. Dutta's research focuses on the intersection of machine learning, visual computing, big data, and high-performance computing. His primary research areas include Machine Learning for Visual Computing and Image Analysis, Big Data Visualization and Analytics, Data Science and HPC, Machine Learning for Scientific Computing, and Explainability and Interpretability of AI Models. His work addresses various big data characteristics including the 5 Vs: Volume, Velocity, Variety, Veracity, and Value. He develops techniques that make complex machine learning models more interpretable and explainable, enabling their effective adoption in real-life applications across scientific domains, social media, IoT, healthcare, and industry applications. Dr. Dutta's research group has secured multiple funded projects including: DAVi: An Intelligent Data Analytics and Visualization Framework (funded by ISRO), Intelligent Visual Computing of Extreme-scale Data for Accelerating Scientific Discovery (IIT Kanpur Initiation Grant), Enabling Interactive Big Data Analytics and Visualization at Exascale (SERB), Development of AI-Enabled National Portal for Efficient Search of Missing People (C3iHub), and Proactive and Generalized Deepfake Defense Mechanisms (C3iHub). Best Reviewer, Honorary Mention Award for IEEE Transactions on Visualization & Computer Graphics (TVCG), 2021 Best Paper Award at ISAV 2021, co-located with Supercomputing (SC) LAAP Award at Los Alamos National Laboratory, 2021 Best Paper Award at TopoInVis 2019 Best Paper Award at ISAV 2018, co-located with Supercomputing (SC) Best Poster Award in 12th Annual CSE Student Poster Exhibition, The Ohio State University, 2018 Best Poster Award in 11th Annual CSE Student Poster Exhibition, The Ohio State University, 2017 Best Paper Honorable Mention Award at IEEE Visualization Conference (IEEE VIS) 2016 Dr. Dutta actively mentors a large group of students including Ph.D., M.Tech., and B.Tech. students. His current Ph.D. students include Shanu Saklani, Sankhadeep Bhowmick, Ananya Chaturvedi, Arpita Santra, Anubhav Dixit (co-supervised), and Robin Shah. He has supervised numerous M.Tech. students with thesis topics ranging from uncertainty-aware neural networks to deepfake detection. Dr. Dutta currently teaches courses including CS360 - Introduction to Computer Graphics and CS661 - Big Data Visual Analytics. The INSIGHT research group collaborates internationally with researchers from Meta, Oak Ridge National Laboratory, and National Taiwan Normal University. The group's work focuses on building machine learning and data science-based solutions to analyze large-scale multifaceted data in a scalable way, enabling interactive and interpretable analytics of complex data from scientific simulations, social media, IoT, healthcare, and other application domains.
John Baillieul is Distinguished Professor at Boston University with joint appointments in Mechanical Engineering, Systems Engineering and Electrical & Computer Engineering. He directs experimental laboratories for real-time control of lightweight robotic systems and applies nonlinear control theory to complex multi-body, networked, and bio-inspired systems. Education: Ph.D., Harvard University Research Interests: Baillieul’s work spans robotics, nonlinear control, and networked systems. Early contributions resolved motion-planning for kinematically redundant manipulators; current themes include neuromimetic learning, vision-based navigation, and resilience of infrastructure networks such as power grids. His group couples rigorous geometric control with real-time hardware to create lightweight, high-performance robots and to uncover fundamental information limits in feedback systems. Recent Publication Trends (2021-2025): Over the past five years his output has concentrated on three synergistic directions: (i) neuromimetic and Koopman-based data-driven methods for estimating and controlling nonlinear systems, (ii) vision-based guidance and sparse optical-flow primitives for agile autonomous flight, and (iii) network-theoretic decomposition and information-rate studies for resilient operation of power grids and collective dynamics. Honors & Awards: IEEE Fellow 2025 Roger W. Brockett Control Systems Award Former Editor-in-Chief, IEEE Transactions on Automatic Control Affiliations & Service: He is a member of Boston University’s Center for Information and Systems Engineering (CISE), has served as Editor-in-Chief of IEEE Transactions on Automatic Control, and remains active in editorial and organizational roles across the IEEE control systems community.
Morteza Fayazi is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Utah, with an adjunct position in the Kahlert School of Computing. His research focuses on Electronic Design Automation (EDA), applying machine learning to automate analog and mixed-signal circuit design, and developing high-performance computing systems. He holds a B.Sc. from Sharif University of Technology, and M.S.E./Ph.D. degrees from the University of Michigan. His research interests include AI-driven EDA, RF/circuit automation, and energy-efficient processors. Key achievements include the MEDAL lab’s work on terahertz radars, systolic-array processors (e.g., DAP and Versa), and open-source frameworks like FASCINET and Tablext. He has received awards such as the 2024 College of Engineering Dean’s ETR Fund and the 2017 Outstanding Undergraduate Thesis Award. Teaching responsibilities include multiple iterations of the Digital System Design course (ECE/CS 3700). His work spans over 15 peer-reviewed articles in IEEE Transactions, ACM, and top conferences like ICCAD and VLSI-SOC, emphasizing automation, efficiency, and AI integration in hardware design.
Changhuei Yang is the Thomas G. Myers Professor of Electrical Engineering, Bioengineering, and Medical Engineering at California Institute of Technology, serving as Executive Officer for Electrical Engineering and Investigator at Heritage Medical Research Institute. He holds a Ph.D. and three master's degrees from MIT, with appointments at Caltech since 2003. Research focuses on: Advanced microscopy techniques including Fourier Ptychography Wavefront shaping for biological tissue imaging Optical phase conjugation for deep-tissue applications Compact medical devices for cerebral monitoring Publications demonstrate leadership in computational imaging, with recent advances in stain-free embryo analysis, portable cerebral blood flow monitors, and high-resolution volumetric imaging techniques using neural representations. Honored as National Academy of Inventors member. Research applications span deep-tissue biochemical imaging, incisionless surgery, and optogenetic activation systems.
James J. Gross is the Ernest R. Hilgard Professor of Psychology at Stanford University, directing the Stanford Psychophysiology Laboratory. He specializes in emotion regulation, with affiliations in Philosophy (courtesy). His education includes a Ph.D. in Clinical Psychology from UC Berkeley (1993), a B.A. in Philosophy and Psychology from Yale (1987), and a visiting graduate year at Oxford (1988). Research focuses on emotion regulation mechanisms, psychopathology, neuroimaging, and cultural influences. His work bridges clinical, cognitive, and social psychology, examining how individuals manage emotions to influence mental health and behavior. Notable contributions include the Process Model of Emotion Regulation and interventions targeting emotion regulation deficits. Publications (~650, 250k citations) highlight studies on emotion regulation strategies, clinical applications, and neural underpinnings. Recent work explores transdiagnostic treatments, digital health interventions, and the interplay between beliefs and emotion regulation. Awards: Stanford Dean’s Teaching Award, Walter J. Gores Award (highest teaching honor), multiple mentoring awards, and honorary doctorates from UC Louvain and Tilburg. Professional Roles: Co-founding President of the Society for Affective Science, Founding Co-Editor-in-Chief of Affective Science , and Fellow of major psychological and scientific societies. Labs/Teams: Directs the Stanford Psychophysiology Lab, collaborating on projects involving neuroimaging, psychophysiological assessment, and computational modeling of emotion processes.
