جست‌وجوی استاد و پژوهشگر

Lauren Simonمشاهده پروفایل

دانشیار

• Organizational Behavior
• Human Resources Management
• Career Development
• +۷ مورد دیگر

Dr. Lauren Simon is an Associate Professor of Management at the Sam M. Walton College of Business at the University of Arkansas. She earned her Ph.D. in Management with a concentration in Organizational Behavior and Human Resources from the University of Florida, along with a BS in Psychology and BSBA in Management from the same institution. Dr. Simon has a passion for career development and helping students successfully transition into the professional workforce, as well as for partnering with organizations to help them better manage, lead, and engage their workforce. Her research focuses on individual and social factors that influence career success, including individual differences (e.g., personality, ability, and disability), new employee onboarding and adjustment, interpersonal work relationships (particularly among managers and employees), and leadership. Her work has been published in top academic journals including the Journal of Applied Psychology, Personnel Psychology, the Journal of Management, and the Journal of Vocational Behavior, and has been featured in major media outlets such as Science Daily, The Wall Street Journal, CBS News, Economic Times, United Press International, and WebMD. Academy of Management HR Division's Scholarly Achievement Award Southern Management Association's Overall Best Conference Paper Award Innovative Teaching Award from Academy of Management's HR Division David Lepak Service Award from Academy of Management's HR Division Golden Tusk Award from University of Arkansas Division of Student Affairs Practitioner Research Award from American Real Estate Society Dr. Simon is an active member of the Academy of Management, where she volunteers as the webmaster for both the HR and Careers Divisions. She has served on various committees including the AOM HR Division Scholarly Achievement Award Committee. Her research demonstrates a consistent focus on workplace dynamics, leadership, and inclusion, with particular attention to disability in the workplace and employee well-being. Through her teaching and research, Dr. Simon has made significant contributions to understanding how organizations can create more inclusive workplaces that support diverse employee needs while enhancing organizational effectiveness.

Prateek Dwivediمشاهده پروفایل

پژوهشگر

• Theoretical Computer Science
• Algebraic Complexity Theory
• Graph Theory
• +۳ مورد دیگر

Prateek Dwivedi is a postdoctoral researcher in the Theory Group at the IT University of Copenhagen , collaborating with Prof. Nutan Limaye. He earned his Ph.D. in 2025 from the Indian Institute of Technology Kanpur under Prof. Nitin Saxena. His research focuses on Theoretical Computer Science , particularly Algebraic Complexity Theory , Graph Theory , and Computational Number Theory . Research interests include circuit complexity, polynomial identity testing, border complexity, and group testing problems. His work bridges algebraic methods with algorithmic challenges, emphasizing explicit polynomial constructions and bounded-depth circuit analysis. Recent publications highlight advancements in monotone bounded-depth circuits, deterministic identity testing for depth-4 circuits, and exploration of border complexity in algebraic circuits. These contributions span conferences like STOC, FOCS, MFCS, and CCC, reflecting both depth and breadth in his theoretical investigations. Collaborations frequently involve co-authors such as C. S. Bhargav, Nitin Saxena, and Pranjal Dutta. He has presented at international venues including workshops in Zinal (Switzerland), STOC, and online seminars, demonstrating active engagement with the global academic community.

• Time series
• Modeling
• Forecasting
• +۲ مورد دیگر

Dr. Salim Jibrin Danbatta is an Assistant Professor in the Department of Computer Engineering at Uskudar University. Born on May 13, 1987, in Kano State, Nigeria, he has established himself as a researcher specializing in time series analysis, modeling, and forecasting techniques with applications across multiple domains. His educational background includes: BSc in Information Technology from Limkokwing University of Creative Technology, Malaysia (2011) MSc in Information System Engineering from Near East University, Cyprus (2014) Ph.D. in Software Engineering from Firat University, Turkey (2022) Dr. Danbatta's research focuses on time series data, covering modeling, forecasting, analysis, and Monte Carlo simulation schemes. His work spans applications in environmental science, tourism, rainfall prediction, and software engineering. He has published papers in SSCI, SCI/E, ESCI journals and IEEE conference proceedings, with an h-index of 5 and 218 total citations according to Scopus metrics. His recent publications demonstrate a consistent application of hybrid time-series models and Monte Carlo simulation techniques to address practical challenges, particularly in environmental monitoring and prediction in Nigeria. His research shows increasing sophistication in combining multiple modeling approaches to improve forecasting accuracy while addressing uncertainty. Dr. Danbatta serves in several administrative roles including Student Adviser, Member of the Education Commission, and Member of the Erasmus and Foreign Relations Commission at Uskudar University. Prior to his current position, he taught at the Kano State Institute for Information Technology and worked as a computer officer at the Kano State Ministry of Science and Technology for three years.

Michael Karowمشاهده پروفایل

پژوهشگر

• Numerical Linear Algebra
• Control Theory
• Matrix Analysis
• +۶ مورد دیگر

Michael Karow is a Researcher at the Institute of Mathematics , Technical University of Berlin , affiliated with the Faculty II - Mathematics and Natural Sciences . His research focuses on Numerical Linear Algebra , Control Theory , and Matrix Perturbation , with specific interests in Pseudospectra , Stability Radii , and Structured Eigenvalue Problems . Educational background includes a Ph.D. (2003) from the University of Bremen, titled " Geometry of Spectral Value Sets ," and a Habilitation (2009) at TU Berlin. His work spans collaborations with institutions like IIT Guwahati, EPFL Lausanne, and SUNY Utica. His research involves stabilizing discrete-time linear systems via matrix factorizations, structured matrix pencils with no spillover effects, and backward error analysis for palindromic polynomials. Publications highlight applications in finite element model updating , eigenvalue sensitivity , and geometric matrix theory . Teaching includes courses like Numerical Mathematics 1 for Engineering , Differential Equations and Numerics , and Calculus of Variations . He has led workshops in India, Italy, and the U.S., focusing on numerical methods and control theory.

• Quantum Computing
• Cryptography
• Theoretical Computer Science
• +۳ مورد دیگر

Sean Hallgren is a Professor in Computer Science and Engineering, specializing in quantum algorithms and computational complexity. His research spans both theoretical and applied aspects of quantum computing, cryptography, and mathematical optimization. Research Interests Hallgren's work focuses on: Quantum algorithm design and complexity Cryptographic reductions under quantum models Number-theoretic problems in cryptography Quantum linear algebra techniques Computational complexity of combinatorial problems Recent Publications Hallgren's 15 most recent articles (5 shown) demonstrate expertise in quantum algorithm limitations, cryptographic hardness reductions, and isogeny-based cryptography. His 2023 study in Quantum analyzed the Macaulay matrix approach for solving polynomial systems using quantum linear solvers. Grants & Projects Current and past projects include: Exponential Speedups and Limitations of Quantum Computation (U.S. Navy, 2018–) NSF Convergence Accelerator: Scalable Quantum Artificial Intelligence for Discovery (2020–2023) SaTC: CORE: Small: Classical and quantum algorithms for number-theoretic cryptography (2020–2025) AF: Small: Quantum Algorithms and Complexity (2016–2020, PI)

Theo Douvropoulosمشاهده پروفایل

استادیار

• Algebraic Combinatorics
• Coxeter groups
• Artin groups
• +۴ مورد دیگر

Theo Douvropoulos is an Assistant Professor at the Department of Mathematical Sciences, University of Texas at Dallas. He works on Algebraic Combinatorics with a focus on Coxeter groups, Artin groups, hyperplane arrangements, poset homology, Hurwitz numbers, and Frobenius manifolds. His research bridges algebraic structures with geometric and topological phenomena. University of Texas at Dallas University of Massachusetts at Amherst (former) Brandeis University (former) University of Minnesota (PhD) His work includes generalizing Hurwitz numbers to reflection groups, studying deformations of restricted reflection arrangements, and exploring connections between W-parking spaces and noncrossing partitions. Recent projects involve spectral analysis of the W-Laplacian and its applications in Coxeter-Catalan combinatorics. Publications span topics like Lyashko-Looijenga morphisms, cyclic sieving phenomena, and matrix tree theorems for reflection groups, demonstrating interdisciplinary applications across algebra, geometry, and topology.

• Developmental Mathematics
• Algebra and Number Theory
• Instructional Design and Technology

John Redden serves as a Professor in Mathematics and Statistics at College of the Sequoias, a California community college, since January 2014. His primary academic focus spans developmental mathematics and algebra education within the Mathematics and Statistics department. Research Interests: Developmental Mathematics (Expert): Creator of the free online algebra study guide openAlgebra.com and author of comprehensive developmental math resources. Algebra and Number Theory (Advanced): Authored two algebra textbooks published by Flat World Knowledge, emphasizing accessible mathematical instruction. Instructional Design and Technology (Intermediate): Integrates digital tools into mathematics pedagogy with expertise in educational technology frameworks. His scholarly output centers on algebra education materials, including textbooks and open-access digital resources that address foundational mathematical literacy. These works demonstrate consistent focus on practical applications and student-centered learning approaches in algebraic concepts. Professional Recognition: No formal scientific awards or fellowships documented in available sources. Redden maintains active contributions through authored materials and course portfolios. His teaching portfolio includes Mathematics and Computer Science instruction since Fall 1997, with emphasis on curriculum development for community college mathematics. No laboratory affiliations or research teams are indicated in the provided documentation.

Lili Yuمشاهده پروفایل

استاد

• Biostatistics
• Survival Analysis
• Categorical Data Analysis
• +۵ مورد دیگر

Lili Yu is the Karl E. Peace Endowed Chair of Biostatistics and Professor in the Department of Biostatistics, Epidemiology & Environmental Health Sciences at Georgia Southern University, where she has been faculty since 2007. Her academic appointments include serving as Principal Investigator for the Office of International Chinese Statistical Association (2007-2017) and as Co-Principal Investigator for current research projects including 'Hierarchical Bayes Regression Models for Geospatial Inquiries' at Georgia Southern University. Dr. Yu's educational background is highly interdisciplinary, with degrees spanning medicine and statistics: PhD in Biostatistics from Ohio State University (2007) MS in Statistics from Ohio State University (2004) MS in Neuroscience from Capital Medical University (2001) MD in Clinical Medicine from Tianjin Medical University (1995) Her research interests focus on biostatistical methodology development and application, particularly in survival analysis, categorical data analysis, and multivariate data analysis. Dr. Yu has made significant contributions to accelerated failure time models, Bayesian statistics, and spatiotemporal modeling. Her work often addresses important public health questions related to disease modeling, mortality risk factors, and health outcomes assessment. Analysis of her publication trends shows a consistent trajectory from methodological development in survival analysis to applied studies addressing significant health issues. Dr. Yu has received recognition for her scholarly contributions, with an h-index of 11 according to Scopus data, and 1,876 citations across her publications. Her work has appeared in numerous high-impact journals across biostatistics, epidemiology, and public health disciplines. Her research funding includes multiple successful grant awards, demonstrating her ability to secure competitive research support. Notable projects include 'Hierarchical Bayes Regression Models for Geospatial Inquiries' (2022-2023), 'Efficient statistical methods in AFT model for cancer data' (2009-2010), and leadership of the Office of International Chinese Statistical Association (2007-2017). Dr. Yu's collaborative network is extensive, with co-authors from multiple institutions across the United States and internationally. Her work bridges methodological statistics with practical applications in public health and medicine, contributing to United Nations Sustainable Development Goals related to health and well-being.

• Theoretical High Energy Physics
• Gravitational Physics
• Astroparticle Physics
• +۶ مورد دیگر

Hjalte Axel Frellesvig is a Postdoctoral Researcher at the Niels Bohr Institute, University of Copenhagen, with additional affiliations as an External Researcher and Guest Researcher at the Niels Bohr International Academy. His research focuses on theoretical high energy physics, astroparticle physics, and gravitational physics. Dr. Frellesvig's research interests span several interconnected areas of theoretical physics: Theoretical High Energy Physics: Specializing in advanced computational methods for calculating scattering amplitudes and Feynman integrals Gravitational Physics: Working on the interface between quantum field theory and general relativity, particularly in the context of gravitational waves Mathematical Physics: Applying sophisticated mathematical techniques including Calabi-Yau geometry, intersection theory, and cohomology to physical problems Particle Physics Phenomenology: Contributing to precision calculations relevant for LHC experiments His recent work demonstrates a strong trend toward unifying mathematical structures in quantum field theory with gravitational physics, particularly through the application of Calabi-Yau geometry to post-Minkowskian expansions. Frellesvig has made significant contributions to developing the loop-by-loop Baikov representation and ε-factorized forms of Feynman integrals, which have important applications in both particle physics and gravitational wave astronomy. Frellesvig has established productive collaborations with researchers across multiple institutions, as evidenced by his co-authorship with scientists from various international organizations. His work bridges theoretical developments with potential observational consequences in astroparticle physics.

• Arithmetic Geometry
• Coding Theory
• Galois Representations
• +۳ مورد دیگر

Jérémy Le Borgne is an Assistant Professor in the Department of Mathematics at ENS Rennes, where he has held faculty positions since 2012. He is a core member of IRMAR's Geometry and Effective Algebra Team, contributing to France's national mathematics research infrastructure through this CNRS-affiliated institute. His dual role encompasses advanced teaching from undergraduate to Agrégation levels and active research at the intersection of algebra, geometry, and computation. His educational foundation includes: ENS Cachan - Antenne de Bretagne (2005-2009) PhD in Mathematics, University of Rennes 1 (2009-2012), supervised by Xavier Caruso and David Lubicz Le Borgne's research pioneers computational approaches to arithmetic geometry, with seminal work on Ore polynomials enabling breakthroughs in Gabidulin code construction for error correction. His investigations into p-adic Galois representations bridge number theory and algorithm design, while recent studies of Hall bases for free Lie algebras reveal deep combinatorial structures applicable to differential equations. This tripartite focus creates synergies between theoretical mathematics and practical computation. Analysis of his 2010-2023 publications reveals consistent progression from foundational number theory (Ax-Sen-Tate theorem optimization) toward increasingly computational work, with 2022-2023 papers emphasizing algorithmic Lie algebra structures and nonlinear system expansions. His research demonstrates strong continuity in non-commutative algebra applications while expanding into new combinatorial territories. No formal awards are documented in public materials, though his publication record in high-impact journals like Journal of Algebra and Comptes Rendus Mathématique indicates peer recognition. His teaching portfolio spans advanced algebra courses and Agrégation preparation, with documented outreach including Lebesgue lectures and Olympiad training. As a research supervisor, Le Borgne integrates students through IRMAR's collaborative environment, though specific advisee counts aren't public. His Geometry and Effective Algebra Team provides infrastructure for computational mathematics projects, with recent work suggesting active funding for skew polynomial and Lie algebra research. The lab maintains close ties with University of Rennes 1's mathematics department, facilitating resource sharing across Rennes' academic ecosystem.