Sung Hoon Choi is an Assistant Professor in the Department of Economics at the University of Connecticut, part of the College of Liberal Arts and Sciences. His research focuses on developing econometric tools for analyzing big data, machine learning applications, and forecasting using high-dimensional panel datasets. He holds a Ph.D. in Economics from Rutgers University (2021), an M.A. in Applied Statistics from Yonsei University (2016), and a B.A. in Statistics from the University of California, Berkeley (2013). His research interests include econometric theory, financial econometrics, and high-frequency data analysis. Notable areas of concentration are large panel data and factor models, high-dimensional data techniques, and volatility matrix analysis. He teaches courses such as Econometrics I and III for Ph.D. students, and Python programming for economists at undergraduate and master's levels. Recent publications focus on volatility modeling using factor structures, high-frequency financial data, and panel data econometrics. His work addresses challenges in structural information analysis, standard errors for clustered panels, and feasible generalized least squares methods. He collaborates with researchers like Donggyu Kim and Jushan Bai, contributing to leading journals like the Journal of Econometrics and Econometric Theory .
Alan Sussman is a Professor and Associate Chair of Undergraduate Education in the Computer Science department at the University of Maryland. His research focuses on databases, high-performance computing, parallel systems, and educational curriculum development for computing disciplines. He holds a Ph.D. from Carnegie Mellon University (1991) and a B.S.E. from Princeton University (1982). His educational contributions include integrating parallel and distributed computing concepts into early undergraduate courses, supported by NSF-funded initiatives like the CyberTraining program. He has advised students such as Harshit Soora (Master's) and Xiaolong Tian (PhD). His research spans compiler optimizations for parallel programs, distributed data management systems, and scientific workflow frameworks like DYFLOW. He collaborates with UMIACS and contributes to interdisciplinary projects like the TASCS center. Key innovations include VeloxDFS for distributed dataset streaming, compiler techniques for irregular memory access in PGAS programs, and NetCDFaster for geospatial data optimization. His work emphasizes productivity improvements for high-performance applications and curriculum modernization to address emerging computational challenges. Awards: No individual awards explicitly listed; however, collaborator Jik-Soo Kim received a best paper award in 2006. Grants: NSF CyberTraining, TCPP Curriculum Initiative, and Center for Technology for Advanced Scientific Component Software (TASCS). Labs/Teams: Active in UMIACS and interdisciplinary collaborations, including the TASCS center and InterComm framework development.
Dr Andrea Greve is a Lecturer in the Department of Psychology at the University of Cambridge . Her research focuses on cognitive processes related to memory, prediction error, and learning mechanisms. Key areas of interest include declarative memory formation, semantic predictions, and the influence of novelty on memory retention. She has explored topics such as word learning in variable-choice paradigms, the role of hippocampal lesions in memory binding, and predictive coding in neuroimaging contexts. Her work integrates experimental psychology with neuroscience methodologies, particularly leveraging neuroimaging techniques to investigate memory systems. Notable contributions include studies on false memory effects, the nonmonotonic relationship between object-location memory and expectedness, and the impact of prior knowledge on memory encoding. Dr. Greve has also contributed to methodological advancements, such as improved MRI anonymization for MEG coregistration. While her research spans multiple decades, recent efforts (2023–2025) emphasize predictive frameworks and their applications in understanding cognitive phenomena like semantic surprise and episodic memory formation. Her findings challenge traditional assumptions about fast mapping in adults and highlight the importance of integrating computational models with empirical data. Dr. Greve collaborates extensively with neuroimaging and cognitive science teams, contributing to interdisciplinary projects that bridge theoretical and applied research in memory systems. Her work maintains a strong focus on methodological rigor, particularly in experimental design and data interpretation.
Katherine Hubbard is an Associate Professor of Art and Director of the MFA Program at Carnegie Mellon University School of Art. Her practice integrates photography, writing, and performance to explore the intersection of social politics, history, and narrative through a lens of bodily engagement. Hubbard's work emphasizes analog photography as a medium that mimics and interrogates the body's relationship to visual processes, often staging performances where participants' physical positioning becomes integral to the artwork's temporal experience. Education: MFA from the Milton Avery Graduate School of the Arts at Bard College (2010). Research focuses on the politics of looking, the malleability of vision, and bridging the imaginary with the familiar through interdisciplinary projects. Notable collaborations include the Poetry Parade series (2012–ongoing), a migratory feminist reading action performed in institutions like the Whitney Museum, and cyclops & slashes (2015), a participatory performance addressing social dynamics through photography and text. Awards: 2020 Guggenheim Fellowship in Photography. Hubbard has exhibited widely, including solo shows at Higher Pictures (New York) and Company Gallery (NY), with works featured in Frieze Magazine . Her projects often involve site-specific installations, such as Four shoulders and thirty five percent everything else (2014), which interrogates landscape and perception in Utah's desert.
Christopher Walters is a Professor at the Kenneth C. Griffin Department of Economics, University of Chicago, and previously served as an Assistant Professor at UC Berkeley (2013-2025). He is a Research Associate at the National Bureau of Economic Research, Research Fellow at IZA, and Faculty Affiliate at MIT's School Effectiveness and Inequality Initiative (SEII). PhD in Economics, MIT (2013) B.A. in Economics and Philosophy, University of Virginia (2008) Walters specializes in Labor Economics and the Economics of Education , focusing on school choice, early childhood interventions, and program evaluation. His work combines applied econometric methods with discrete choice modeling to analyze educational investments and labor market outcomes. Walters' recent publications examine class size effects, teacher quality impacts, and school finance policies, reflecting his interest in improving educational equity through rigorous empirical analysis. Research Fellow at IZA He collaborates with institutions like J-PAL North America and MIT Blueprint Labs, contributing to evidence-based policy design in education and labor economics.
Joseph P. Romano is a distinguished Professor of Statistics and Economics at Stanford University, where he has been on the faculty since 1986. He holds joint appointments in both the Department of Statistics and the Department of Economics, reflecting his interdisciplinary research that bridges statistical theory with economic applications. Romano has established himself as a leading scholar in mathematical statistics with significant contributions to econometrics, climate science, and multiple testing methodologies. Ph.D. in Statistics, University of California, Berkeley (1986) M.S. in Statistics, University of California, Berkeley (1983) A.B. in Statistics, Princeton University (1982), Summa Cum Laude Romano's research focuses on the theoretical foundations and practical applications of statistical methods, particularly in nonparametric statistics, bootstrap and resampling techniques, and multiple testing procedures. His work addresses the challenges of analyzing massive datasets with complex structures, such as those found in biotechnology, clinical trials, and econometrics. He has developed universal statistical tools applicable across diverse fields including climate science, genetics, finance, and education. His recent work emphasizes methods for multiple testing and multivariate inference driven by the availability of massive datasets, where he tackles issues like unknown dependence structures, heterogeneity, and high dimensionality. Analysis of Romano's recent publications reveals a consistent focus on developing robust statistical methodologies for complex data structures. His work spans theoretical advances in U-statistics with growing dimensions, practical applications in seroprevalence studies, and innovative approaches to ranking inference across various domains. The interdisciplinary nature of his research is evident in publications spanning economics journals, statistics journals, and even behavioral science preprints, demonstrating the broad applicability of his methodological contributions. 2021 LGBTQ+ Scientist of the Year, Out to Innovate Fellow, International Association of Applied Econometrics (2020) Fellow, Institute of Mathematical Statistics Presidential Young Investigator Award, National Science Foundation The Canadian Journal of Statistics Award Romano has mentored dozens of doctoral students throughout his career at Stanford, serving as dissertation advisor, co-advisor, and committee member for numerous PhD candidates in Statistics. His research has been consistently supported by National Science Foundation grants, including recent funding for computer-intensive inference with applications to social sciences (2020-2023) and randomization inference for contemporary statistical problems (2013-2016). He has served in various administrative roles at Stanford including Associate Chairman and Chair of Committee on Faculty Affairs. Beyond his academic pursuits, Romano is actively involved in the 500 Queer Scientists visibility campaign and maintains a balanced life with passions in music (having performed at Carnegie Hall), competitive tennis (ranked nationally in his age group), cooking, and architecture.
Adria Lawrence is the Aronson Associate Professor of International Studies and Political Science at Johns Hopkins University, holding a joint appointment between the Paul H. Nitze School of Advanced International Studies (SAIS) and the Department of Political Science at the Krieger School of Arts & Sciences. Her research focuses on Middle Eastern and North African politics, colonialism, nationalism, and conflict dynamics. She earned her PhD from the University of Chicago and a BA from Vassar College. Her groundbreaking book, *Imperial Rule and the Politics of Nationalism: Anti-Colonial Protest in the French Empire* (2013), examines post-WWII anti-colonial movements and has received prestigious awards including the J. David Greenstone Book Prize and the L. Carl Brown Book Prize. Current research explores colonial resistance and contemporary Arab world dynamics. Teaching interests include colonial rule, state formation, and qualitative research methods. She advises on topics such as Moroccan political cleavages, autocracy, and social movements in North Africa. Office hours are held via Zoom or in-person at 270 Mergenthaler Hall. Affiliations: Krieger School of Arts & Sciences, SAIS (Program Chair for International Studies Program) Research Sites: Morocco, Tunisia, France (archival work)
Jonathan Hauenstein is the Robert and Sara Lumpkins Collegiate Professor in the Department of Applied and Computational Mathematics and Statistics at the University of Notre Dame, serving as Department Chair. He holds a Ph.D. from Notre Dame (2009) and M.S. from Miami University (2005). His research focuses on numerical algebraic geometry and computational methods for solving nonlinear equations, implemented in the Bertini software package. Applications span engineering, ecology, sports science, and machine learning. Education: Ph.D., Applied and Computational Mathematics, University of Notre Dame (2009) M.S., Mathematics, Miami University (2005) Research Interests: Development of numerical algorithms for polynomial systems, real algebraic geometry, and scientific computing. Key areas include homotopy continuation methods, parameter space decomposition, and applications in mechanism design, ecological modeling, and sports biomechanics. His work bridges theoretical mathematics with practical computational tools. Awards: Sloan Research Fellowship DARPA Young Faculty Award Army Research Office Young Investigator Award Office of Naval Research Young Investigator Award College of Science Research Award Advising & Grants: Advised numerous undergraduates, graduate students, and postdoctoral researchers. Active in securing grants for computational mathematics projects, including NSF-funded initiatives. His work emphasizes interdisciplinary collaboration between mathematics and engineering. Labs/Teams: Leads computational algebraic geometry research groups at Notre Dame, focusing on software development (e.g., Bertini) and numerical methods innovation.
Joyelle McSweeney is a Professor of English at the University of Notre Dame, specializing in creative writing, poetry, and translation. She holds an MFA from the Iowa Writers' Workshop, an M.Phil. from the University of Oxford, and a B.A. from Harvard University. Her work spans poetry, prose, drama, and critical essays, emphasizing ecopoetics, decadence, and genre hybridization. Research focuses on intersections of ecology, media, and occult symbolism, with key works like The Necropastoral: Poetry, Media, Occults (2015) proposing a decadent approach to ecological writing. Awards include a 2022 Guggenheim Fellowship and the Shelley Memorial Prize for Toxicon and Arachne (2020). She co-founded Action Books press, amplifying global poetry and translation. Education: MFA (2001, Iowa), M.Phil (1999, Oxford), B.A. (1997, Harvard) Awards: Guggenheim Fellowship, Arts & Letters Award, Shelley Memorial Prize Key publications include Dead Youth , Salamandrine , and Death Styles Teaching excellence recognized by the Rev. Edmund P. Joyce C.S.C. Award. Her creative output combines experimental form with thematic explorations of decay, prophecy, and ecological crisis.
Rahul Kapoor is a Professor at the Wharton School of the University of Pennsylvania, where he also serves as the Chair of the Management Department. His research focuses on innovation management, business ecosystems, and technology strategy, with a particular emphasis on how firms navigate technological and organizational challenges in dynamic industries. University: University of Pennsylvania School: Wharton School Department: Management Department Academic Rank: Professor His research explores the interplay between organizational design, external collaboration, and innovation outcomes. Recent work includes studies on forecasting strategies, ecosystem interdependencies, and the role of setbacks in technology development. He has contributed to leading journals such as Strategic Management Journal and Research Policy , with a recurring focus on technology ecosystems and modular innovation. Kapoor’s research spans both theoretical and applied dimensions. He has examined how firms can optimize value creation in business ecosystems, the impact of organizational design on invention sourcing, and the dynamics of technology emergence. His studies often integrate historical case analyses and simulation models to uncover patterns in innovation management. Scientific Awards: Inaugural Academy of Management Emerging Scholar Award Strategic Management Journal Best Paper Prize Wharton Teaching Excellence Award (multiple years) Editorial Roles: Associate Editor, Strategic Management Journal Contributing Editor, Strategy Science Teaching: Undergraduate, MBA, Executive MBA, and PhD courses on technology and innovation strategy Leadership in Wharton’s Executive Education programs He has advised firms on innovation initiatives and draws on over seven years of industry experience in high-tech, including roles at Texas Instruments and co-founding a startup, to inform his academic work.
Prof. Dr. Hakkı Polat Gülkan is a Professor at Başkent University's Civil Engineering Department. With a PhD (1971) and Master's (1968) from the University of Illinois in Civil Engineering and a Bachelor's (1966) from METU, his career spans over five decades in earthquake engineering, structural dynamics, and disaster management. PhD: University of Illinois, Civil Engineering (1971) Master's: University of Illinois, Civil Engineering (1968) Bachelor's: Middle East Technical University, Civil Engineering (1966) His research focuses on seismic risk assessment, structural behavior under extreme loads, and disaster mitigation strategies. Key contributions include earthquake simulator development, ground motion analysis, and retrofitting techniques for masonry and reinforced concrete structures. He has published extensively on deformation limits, response spectra, and historical building preservation. Recent work includes 15+ articles from 2024-2012 analyzing Istanbul's seismic hazards, Marmara region dynamics, and post-earthquake structural integrity. Conference papers address Turkey's endemic building vulnerabilities and deformation thresholds for seismic isolation systems. Scientific Achievements: Elected to U.S. National Academy of Engineering (2023) As an active journal reviewer for 13+ publications (2023-2024), he contributes to advancing earthquake engineering discourse. His teaching portfolio includes advanced structural analysis, concrete mechanics, and seismic design courses.
Vincent Dufour-Décieux is a researcher at the Professorship for Energy and Process Systems Engineering at ETH Zürich , focusing on developing computational methods for material screening in separation processes and global net-zero transitions. He earned his Master's in Materials Chemistry from Ecole Polytechnique (France) and a PhD in Materials Science from Stanford University , where he pioneered statistical methods combining Kinetic Monte Carlo and random graph theory to study planetary diamond formation. Research Highlights: Application of Classical Density Functional Theory (cDFT) for 100x faster adsorption property predictions in porous materials Development of science-based definitions for "hard-to-abate" emissions to guide climate action prioritization Integration of Coulombic interactions in cDFT for CO2 adsorption accuracy Article Trends : His work spans computational materials science (cDFT, random graph theory) and climate policy analysis, with recent publications in Joule , AIChE Journal , and Physical Review E . These studies emphasize scalable solutions for carbon capture, material screening efficiency, and accurate thermodynamic modeling. Collaborations : Active in international conferences (FOA15, MolMod, Gordon Research Conference) and cross-institutional projects with teams at Stanford, ETH Zürich, and industry partners.
Adeel Tariq is a Post-Doctoral Researcher at the Industrial Engineering and Management department of LUT School of Engineering Sciences , Lappeenranta University of Technology, Finland. He completed his Ph.D. (2019) and MBA (2014) at the School of Management , Asian Institute of Technology, Thailand. Research Focus: Technology and innovation management, digital transformation, sustainable development, knowledge management, and leadership studies. Peer Review: Active reviewer for journals including Leadership & Organization Development Journal , Journal of Intellectual Capital , and European Journal of Innovation Management . Collaborations: Regular co-author with Waqas Tariq, Muhammad Saleem Sumbal, and Marko Torkkeli on topics like digital governance, fintech, and SME sustainability.
Professor Alexander Koller is a leading academic in Computational Linguistics at Saarland University's Department of Language Science and Technology. He holds a courtesy appointment in Computer Science and contributes to the Saarland Informatics Campus - one of Europe's premier computer science research centers. He leads the Computational Linguistics group and serves as speaker for the DFG-funded Research Training Group 'Neuroexplicit Models of Language, Vision, and Action'. PhD in Computer Science (Saarland University) Former positions: University of Potsdam, Columbia University, University of Edinburgh Sabbatical experiences: Meta AI (Paris), Allen Institute for AI (Seattle) His research focuses on computational modeling of meaning and reasoning in NLP, combining neural and symbolic approaches. Key contributions include semantic parsing systems like the AM parser and Alto, neurosymbolic models, and the GIVE Challenge for NLG evaluation. His recent work explores LLMs' limitations in problem-solving and compositional generalization. Recent publications highlight diverse applications across semantic parsing, dialogue systems, and LLM evaluation. Awards include ACL 2020 Best Theme Paper and multiple Outstanding Paper recognitions at ACL conferences. 2025 - AI Action Summit keynote speaker 2023 - ACL Outstanding Paper Awards 2022 - ELLIS Faculty appointment He maintains the DialogOS system for spoken dialogue development and teaches advanced computational linguistics topics. His group includes multiple postdocs and PhD students working across LLMs, dialogue systems, and semantic modeling.
Professor John D. Cressler is a tenured faculty member at the Georgia Institute of Technology, holding a position within the School of Electrical and Computer Engineering in the College of Engineering. His research focuses on cutting-edge semiconductor technologies, particularly silicon-germanium heterojunction bipolar transistors (SiGe HBTs) for mixed-signal applications spanning RF, microwave, mm-wave, analog, and digital domains. His research interests center on atomic-scale bandgap engineering for next-generation semiconductor devices, with emphasis on SiGe HBT technology development, radiation-hardened circuits for space applications, cryogenic electronics, and device-circuit interactions. His team explores fundamental device theory, broadband noise analysis, profile optimization, 2-D/3-D simulation, compact modeling, and radiation effects. Current projects include Europa-surface mission electronics, D-band/sub-THz systems, and radiation-tolerant receiver designs. Analysis of his 15 most recent publications (2024-2025) reveals a dominant focus on radiation-hardened electronics for space applications (40% of works), millimeter-wave circuit design (30%), and SiGe HBT reliability optimization (30%). Key trends include Europa mission electronics development, D-band/sub-THz circuit innovation, and advanced radiation mitigation techniques using SiGe BiCMOS technology. Professor Cressler teaches multiple courses including ECE 3040 (Microelectronic Circuits), ECE 3450 (Semiconductor Devices), ECE 6444 (Silicon-Based Heterostructure Devices and Circuits), and the interdisciplinary IAC 2002 course on Science, Engineering and Religion. His research is supported by industrial collaborations and Georgia Tech facilities including the Georgia Electronic Design Center (GEDC), NanoTECH, and C-STAR.
