جست‌وجوی استاد و پژوهشگر

Sophie de Buylمشاهده پروفایل

دانشیار

• Theoretical Physics
• Mathematical Physics
• Biophysics
• +۷ مورد دیگر

Sophie de Buyl is an Associate Professor at the Vrije Universiteit Brussel (VUB), actively contributing to interdisciplinary research bridging theoretical physics and biological systems. She is affiliated with the Department of Bio-engineering Sciences and the VUB Data Lab, focusing on mathematical modeling of biological processes, synthetic biology, and biophysics. PhD in Theoretical Physics (2006, Université Libre de Bruxelles) Postdoctoral experience at IHES, UC Santa Barbara, Harvard University Her research spans cosmological singularities, gauge/gravity correspondence, and black hole entropy in her early career, evolving to integrate theoretical physics with experimental biology. Current projects include synthetic gene regulatory circuits, microbial community dynamics, and embryonic development precision. Key publication trends (2025–2019) reflect dual expertise in mathematical physics (Kac-Moody algebras, black holes) and biological systems (microbial ecology, synthetic biology, circadian clocks). Awards highlight early-career recognition by the Belgian Physics Society and Belspo. Supervised FWO PhD projects on dynamic pathway regulation and microbial systems Director of the Interuniversity Institute of Bioinformatics in Brussels since 2020 Her work emphasizes data-driven discovery of general laws in biological systems, with collaborations spanning bioinformatics, microbiology, and computational modeling.

Marcus Holzingerمشاهده پروفایل

استاد

• Space Policy
• Space Situational Awareness
• Information Theory
• +۴ مورد دیگر

Dr. Marcus Holzinger is the Joseph T. Negler Professor and Hatfield Endowed Professor in Space Policy & Law at the University of Colorado Boulder's Department of Aerospace Engineering Sciences. He leads the Colorado Center for Astrodynamics Research (CCAR) and the VADeR Laboratory, focusing on advancing space exploration through interdisciplinary research in space policy, autonomy, and space situational awareness. His work emphasizes collaboration and sustainable practices in space. Education: PhD in Aerospace Engineering Sciences, University of Colorado Boulder (2011) MS in Aeronautics & Astronautics Engineering, University of Washington (2005) BS in Aeronautics & Astronautics Engineering, University of Washington (2003) Research Interests: Space Policy & Law Space Domain Awareness Autonomy & Decision Support Systems Cislunar Space Dynamics Information Theory & Estimation Space Traffic Management Recent Research Trends: Holzinger’s work prioritizes cislunar space exploration and decentralized decision-making for space systems, with applications in orbital debris mitigation, sensor tasking, and spacecraft autonomy. His publications frequently address challenges in initial orbit determination and spacecraft maneuver detection . Awards: American Astronautical Society Fellow (2022) AIAA Associate Fellow (2018) AFOSR Young Investigator Award (2017) Advising & Labs: Holzinger mentors students in the STARLIT and VADeR Observatories. Notable advisees include Sam Fedeler (2023 PhD) and Katie Melbourne (PhD student). His labs develop technologies like astrographic mapping and sensor networks for space surveillance. Labs/Teams: CCAR and the VADeR Lab collaborate on projects funded by NASA, AFRL, and industry partners, emphasizing hardware-in-the-loop testing and space policy frameworks.

• Power Electronic Converters
• Embedded Systems
• Analog and Mixed-Signal Circuit Design
• +۵ مورد دیگر

Dr. Anwar Ali is a Lecturer in the Department of Electronic and Electrical Engineering at Swansea University's Bay Campus, United Kingdom. He earned his MSc (2010) and PhD (2014) in Electronic Engineering from Politecnico di Torino, Italy. His academic roles include postgraduate supervision and teaching modules like EG-152: Analogue Design EG-158: Software Engineering EG-252: Embedded System Design EG-319: Integrated Circuit Design His research focuses on power electronic converters, embedded systems, satellite technologies (power management, attitude determination), and thermal modeling of aerospace systems. Recent work spans autonomous vehicle mobility management, medical imaging diagnostics, and multisource energy harvesting. He has authored over 50 publications and led five research projects as Principal Investigator. Dr. Ali supervises PhD students in areas like wireless power transfer for medical devices and satellite control optimization. His teaching emphasizes practical engineering applications, including PCB design, Python programming, and thermal analysis of spacecraft systems.

Sharad Ramanathanمشاهده پروفایل

استاد

• Developmental Biology
• Stem Cell Research
• Morphogenesis
• +۴ مورد دیگر

Sharad Ramanathan is the Llura and Gordon Gund Professor of Neurosciences and of Molecular and Cellular Biology at Harvard University, with a dual appointment as Professor of Applied Physics and of Stem Cell and Regenerative Biology in the John A Paulson School of Engineering and Applied Sciences. He serves as Principal Investigator of the Ramanathan Lab and is Co-Director of the Quantitative Biology Initiative. His research focuses on understanding how cells and organisms process environmental signals to make developmental decisions, particularly in the context of human development and stem cell morphogenesis. Ramanathan employs a multidisciplinary approach combining stem cell and molecular biology, genomics, bioengineering, and computational biology to investigate these fundamental biological processes. His lab recently achieved a groundbreaking discovery in controlling stem cell colony arrangements to reliably produce embryonic body plans, with 99% of colonies developing proper anterior-posterior axes. This work, which uses hexagonal arrangements of stem cell colonies, has been described as revolutionary for mimicking mammalian embryogenesis in vitro. Ramanathan's publications reveal a strong focus on developmental dynamics, with recent work emphasizing human organoid systems, stem cell differentiation, neural circuit mapping, and the computational analysis of cellular decision-making processes. His research bridges physics, engineering, and biology to tackle fundamental questions in developmental biology. As an educator, he teaches MCB198 Mathematical Techniques for Modern Biology and Applied Physics 286 / Physics 286 Inference, Information Theory, Learning and Statistical Mechanics, demonstrating his commitment to quantitative approaches in biological sciences. The Ramanathan Lab has made significant contributions to understanding stem cell differentiation, embryonic development, and neural circuit organization, with work that has important implications for regenerative medicine and understanding developmental disorders.

Jonathan Fitz Geraldمشاهده پروفایل

دانشیار

• Plant Biology
• Developmental Biology
• Molecular Genetics
• +۳ مورد دیگر

Jonathan Fitz Gerald serves as Associate Professor of Biology at Rhodes College, where he teaches core courses including Biology I, Animal Development, Genetics, and advanced seminars on Stem Cells, Seeds, Morphogenesis, and Evolution of Multicellularity. His academic work spans plant developmental biology with emphasis on molecular genetics and epigenetic regulation. Ph.D. in Molecular Genetics and Cell Biology, University of Chicago B.S. in Biological Sciences, University of California at Irvine Dr. Fitz Gerald's research centers on seed development in Arabidopsis thaliana , specifically investigating the gene AtFH5 and its role in endosperm morphogenesis. His laboratory employs molecular biology, genetics, and advanced microscopy techniques including H2B::RFP labeling to study parental genome imprinting mechanisms. Key questions address how Polycomb group complexes regulate maternal-specific expression of AtFH5 and how cytoskeletal dynamics control nutrient transfer to the embryo. His work bridges fundamental developmental processes with agricultural applications in seed size determination. Analysis of his publication record (1999-2016) reveals a progression from vascular development and yeast cell biology to focused research on seed formation. His most significant contributions involve epigenetic regulation of endosperm development, with recurring themes of genomic imprinting, actin cytoskeleton function, and quantitative genetic control of seed traits. The publications demonstrate consistent use of Arabidopsis as a model system with increasing specialization in reproductive biology. Dr. Fitz Gerald actively mentors undergraduate researchers, evidenced by multiple publications featuring undergraduate co-authors (denoted by †). His teaching portfolio spans introductory to advanced levels with specialized seminars reflecting his research interests. The Fitz Gerald Lab maintains active research on endosperm cell division dynamics using fluorescent labeling techniques to visualize developmental processes in real time.

• Manufacturing Engineering
• Machining
• Production Engineering
• +۳ مورد دیگر

Milenko Sekulić is a Full Professor at the Chair of Machining within the Department of Production Engineering, Faculty of Technical Sciences, University of Novi Sad. He has held this position since 2017 and currently serves as Head of the Chair of Machining (since 2018), following previous roles as Associate Professor (2012-2017) and Assistant Professor (2008-2012) at the same institution. His academic foundation includes a Bachelor's degree (1993), Magister degree (1998), and PhD (2007), all in Mechanical Engineering from the Faculty of Technical Sciences. His educational journey focused on cutting force analysis in milling, development of cutting force calculation models, and determination of drilling forces. Professor Sekulić's research centers on advanced manufacturing engineering, specializing in machining process optimization, thermal analysis, and cutting force prediction. His work integrates fuzzy logic, evolutionary algorithms, and response surface methodology to solve complex problems in electrical discharge machining, abrasive water jet systems, and high-pressure jet assisted turning. Key contributions include energy efficiency models for EDM, surface roughness prediction frameworks, and thermal state optimization in creep-feed grinding. Analysis of his 15 most recent publications reveals a strong trend toward sustainable and intelligent manufacturing solutions. His work consistently addresses material-specific challenges (particularly nickel-based alloys), develops predictive models for machining outcomes, and pioneers hybrid techniques like laser-assisted cutting. The research demonstrates increasing sophistication in combining computational intelligence with traditional manufacturing physics. No scientific awards or fellowships are documented in the available information. Professor Sekulić actively mentors students through thesis supervision and teaching, building on his own academic progression within the institution. His leadership as Head of Chair involves guiding research direction and laboratory activities for the machining group. International collaborations with Slovenian institutions (evident in co-authored publications) highlight his cross-border research engagement. He leads the Chair of Machining research team, which maintains specialized laboratories for conventional and non-conventional machining processes including EDM, water jet systems, and high-pressure jet assisted equipment. Current work focuses on AI-driven process optimization and sustainable manufacturing techniques.

Hong Qianمشاهده پروفایل

استاد

• Mathematical Biology
• Mathematical Physics
• Stochastic Mathematics
• +۷ مورد دیگر

Professor Hong Qian is the Olga Jung Wan Endowed Professor of Applied Mathematics at the University of Washington, Seattle. He holds adjunct roles in Bioengineering and has held visiting professorships at institutions like Jilin University and Fudan University. His research focuses on stochastic analysis and nonequilibrium thermodynamics in biological systems, particularly cellular dynamics and complex systems like epidemiology and economics. Education: B.A. in Astrophysics (Peking University, 1982), Ph.D. in Biochemistry and Biophysics (Washington University School of Medicine, 1989). Professional Experience: Postdoctoral fellowships at Caltech and University of Oregon, prior roles at UCLA and NIH-funded National Simulation Resource. Research interests include nonlinear stochastic systems, nonequilibrium statistical physics, and mathematical biology. He has pioneered work on mesoscopic thermodynamics of small systems and biochemical networks. His contributions span over 160 peer-reviewed articles, including books on chemical biophysics and stochastic reaction systems. Awards: APS Fellow (2010), Royalty Research Fund (2002-2003), multiple editorial roles in top journals. Grants: Over $5M in NIH/NSF funding for projects on metabolic networks, cardiac systems, and cell population dynamics. Teaching spans advanced courses in stochastic analysis, dynamical systems, and mathematical biology. Advised over 30 graduate students and postdocs, many now leading academic and industrial roles.

William Ericksonمشاهده پروفایل

پژوهشگر ارشد

• Representation Theory
• Lie Groups
• Invariant Theory
• +۳ مورد دیگر

Dr. William Erickson is a Postdoctoral Research Fellow in the Department of Mathematics at Baylor University, affiliated with the College of Arts & Sciences. He holds a Ph.D. from the University of Wisconsin-Milwaukee (2022) and a B.A. from the University of Notre Dame (2010). Before pursuing his doctorate, he taught middle/high-school mathematics and Latin for eight years, while also managing a local pool as a lifeguard and swim instructor. His research focuses on the representation theory of Lie groups from a combinatorial perspective, invariant theory, and algebraic statistics, with notable contributions to combinatorial algebra and geometric probability. Educations: Ph.D., Mathematics, University of Wisconsin-Milwaukee, 2022 (Advisor: Jeb Willenbring) B.A., Mathematics, University of Notre Dame, 2010 Research Interests: Dr. Erickson explores the intersection of algebra, combinatorics, and geometry, with a focus on Lie groups and their representations. His work often employs combinatorial tools to study invariant rings, Young tableaux, and algebraic statistics. Recent projects include analyzing the earth mover’s distance in probabilistic contexts and developing new methods for reconstructing Young tableaux via minors. Publications Trends: His articles span combinatorial algebra, representation theory, and applied statistics. Notable topics include Demazure products, palindromicity in generating functions, and geometric interpretations of statistical metrics. His work frequently bridges pure and applied mathematics, with applications ranging from optimization to geometric analysis. Scientific Awards & Grants: No awards or grants explicitly listed in the provided text. Advising & Teams: No formal advisees or lab teams explicitly mentioned. His collaborative work includes co-authors like Rebecca Bourn, Jan Kretschmann, and Markus Hunziker.

• Signal Processing
• Machine Learning
• Tracking Algorithms
• +۳ مورد دیگر

Ángel García-Fernández is an Associate Professor at the Polytechnic University of Madrid , specializing in Bayesian inference , multi-target tracking , and nonlinear filtering with applications in signal processing, robotics, and underwater mapping. His work includes the development of Poisson multi-Bernoulli mixture (PMBM) filters, iterated posterior linearization algorithms, and direction-of-arrival (DOA) measurement models.

Mazen Bou Khuzamمشاهده پروفایل

دانشیار

• Low Dimensional Topology
• Exotic R^4 Structures
• Contact Structures on 3-Manifolds
• +۲ مورد دیگر

Mazen Bou Khuzam serves as Associate Professor in the Department of Mathematics and Natural Sciences at the American University of Iraq, Sulaimani (AUIS), where he has contributed over eighteen years of university-level teaching experience in the Middle East. His academic foundation includes doctoral specialization in Geometry and Topology from the University of Cambridge. Education Ph.D. in Mathematics, University of Cambridge M.S. in Mathematics, American University of Beirut B.S. in Mathematics, American University of Beirut Research Focus Dr. Bou Khuzam's scholarly work centers on low dimensional topology, particularly exotic R 4 structures, contact geometry on 3-manifolds, and the Atiyah-Sutcliffe conjectures concerning point configurations in R 3 . His investigations extend to knot theory invariants and geometric inequalities, with recent publications demonstrating expansion into applied mathematics through chaotic image encryption systems. This evolution reflects both theoretical depth and practical adaptation within geometric frameworks. Publication Trends His 15-year publication trajectory (2006-2022) reveals sustained engagement with topological invariants, transitioning from pure topology (exotic R 4 studies) toward geometric inequalities and computational applications. The 2021-2022 works on convex quadrilaterals and image encryption indicate strategic interdisciplinary movement while maintaining core topological principles. Keyword analysis shows consistent emphasis on geometric structures with growing computer science intersections.

Benoît SAGOTمشاهده پروفایل

استاد

• Aerosol Science
• Thermophoresis
• Particle Separation
• +۵ مورد دیگر

Benoît SAGOT is a Professor at ESTACA (Higher School of Aeronautical and Automotive Engineering Construction), Campus Paris Saclay, where he serves as a Teacher-researcher in the School of Mobility Systems and Complex Engineering within ESTACA'Lab. His work focuses on aerosol science, thermophoresis, and particle separation technologies, with applications in automotive engineering and pollution control systems. His educational background includes: Accreditation to Supervise Research (HDR) from University of Paris-Est (2020) PhD in Process Engineering and Sustainable Development from University of Technology of Compiègne (2010) DEA in Fluid Mechanics and Energy from INPL (1993-1994) Engineering degree from ENSEM (National School of Electricity and Mechanics, Nancy) (1991-1994) Dr. SAGOT's research centers on thermophoresis, aerosol science, and particle separation technologies. His work investigates the behavior of particles in gas flows, with particular focus on thermophoretic transfer mechanisms, cyclone separator efficiency, and applications for reducing particulate emissions from internal combustion engines. His research has significant implications for automotive emissions control and air quality improvement. His publication record shows a consistent focus on thermophoresis and particle separation, with recent work expanding into respiratory droplet characterization. The research demonstrates a progression from fundamental thermophoretic principles to practical applications in automotive engineering, particularly in blow-by gas cleaning systems and engine emissions control. Dr. SAGOT holds several professional leadership positions: Board member of ASFERA (French Aerosol Research Association) since 2017 Member of GDR "Suies" (Soot Research Group) since 2014 Member of ISO/TC 22/SC 34/WG 11 for standardizing test protocols for crankcase gas filters Session chair at European Fluid-Particle Separation Congress (2018) Session chair at French Aerosol Congress (2019) As a research supervisor with HDR accreditation, Dr. SAGOT leads projects including CAPNAV and EMINAV (ADEME CORTEA and AQACIA type projects). His work bridges academic research and industrial applications in automotive engineering, with strong connections to industry standards through his ISO committee work. Dr. SAGOT is actively involved with ESTACA'Lab, where he conducts research on thermophoretic phenomena and particle separation technologies. His laboratory work focuses on experimental validation of theoretical models for particle deposition and the development of instrumentation for aerosol characterization, particularly for automotive applications.

Hsiao-Chun Wuمشاهده پروفایل

استاد

• Statistical Learning
• Digital Signal Processing
• Wireless Communications
• +۹ مورد دیگر

Hsiao-Chun Wu is a Professor and holder of the Michel B. Voorhies Professorship at Louisiana State University (LSU), affiliated with the Division of Electrical & Computer Engineering within the School of Electrical Engineering and Computer Science. He earned his Ph.D. in 1999 from the University of Florida. His research focuses on statistical learning, embedded algorithms, digital signal processing, and wireless communications. Key areas include optimization techniques for detection and estimation, image/speech processing, and networked systems design. He has contributed to advancements in sensor deployment strategies, tensor-based signal processing, and machine learning applications for posture recognition and multimedia classification. Notable technical interests span computational photography, robust multichannel decorrelation, and energy-efficient data collection in wireless sensor networks. His work often integrates tensor analysis and graph convolutional networks to address challenges in high-dimensional data processing. Dr. Wu's academic contributions include pioneering methods for indoor line-of-sight coverage optimization and developing novel modulation recognition techniques. His research also addresses industrial IoT performance optimization and biomedical applications such as noninvasive activity recognition using mmWave radar.

Mareike Dresslerمشاهده پروفایل

مدرس ارشد

• Real Algebraic Geometry
• Computational Algebraic Geometry
• Polynomial Optimization
• +۶ مورد دیگر

Mareike Dressler is a Senior Lecturer (A/Professor, tenured) and ARC Discovery Early Career Research Fellow at the School of Mathematics and Statistics, University of New South Wales (UNSW Sydney). She joined UNSW in February 2022 as a Lecturer (Assistant Professor, tenure-track) and was promoted to Senior Lecturer with tenure in July 2024. Her educational background includes: PhD in Mathematics from Goethe-Universität Frankfurt/Main (2018), supervised by Thorsten Theobald M.Sc. in Mathematics from Goethe-Universität Frankfurt/Main (2013) B.Sc. in Mathematics from Goethe-Universität Frankfurt/Main (2010) Mareike's research focuses on real and computational algebraic geometry and polynomial and convex optimization. She also works on problems intersecting with convex geometry, matrix and tensor computation, applied algebraic geometry, algebraic and geometric combinatorics, and real analysis. Her work particularly involves nonnegativity of polynomials, optimization methods, and ranks of matrices and tensors, with a special interest in sums of nonnegative circuits (SONCs) for sparse polynomials. Her research has strong applications in data science and machine learning. Mareike has received several prestigious awards including the ARC Discovery Project 2025 grant for "Quantifying Uncertainty of Risk-Aware Optimization for Safe Decision-Making," the J G Russell Award from the Australian Academy of Science, and the Early Career Impact Award from UNSW Science. She actively supervises research students, including PhD student Hongzhi Liao, Master's student Qi Wang, and recently supervised Moritz Schick to completion of his PhD in 2025. Mareike has secured significant research funding, including an ARC Discovery Early Career Researcher Award (DECRA) for 2024-2026. Mareike is an active member of the academic community, regularly organizing workshops and conferences such as "Optimization Days" at UNSW and minisymposia at major conferences like SIAM Conference on Applied Algebraic Geometry.

Amit Kumarمشاهده پروفایل

استاد

• Combinatorial Optimization
• Online Algorithms
• Approximation Algorithms
• +۷ مورد دیگر

Amit Kumar is a Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Delhi . He teaches several core and advanced courses including Mathematical Programming (COL 756) , Advanced Algorithms (COL 758) , Approximation Algorithms (COL 754) , Introduction to Automata and Theory of Computation (COL 352) , Design and Analysis of Algorithms (COL 351) , Data Structures (COL 106) , Discrete Mathematics (COL 202) , and Numerical Analysis and Scientific Computing (COL 726) . His office is located in Room 417, Bharti Building, and he uses email amitk@cse.iitd.ac.in for communication. His research lies primarily in combinatorial optimization and online algorithms , with recent work focusing on clustering problems with side constraints, understanding biases in evaluation processes, and online allocation with additional constraints. He has made significant contributions to approximation algorithms, stochastic optimization, and fairness in algorithmic systems. His research interests span theoretical foundations and practical applications in algorithm design. The recent publications (2023–2025) reflect a strong trend in fairness-aware algorithms , learning-augmented online algorithms , and advanced clustering techniques . The work spans top-tier venues such as STOC, FOCS, SODA, ICML, and NeurIPS, indicating high impact and interdisciplinary reach. Topics include bias in evaluation, fair service allocation, consensus clustering, and robust sorting, showing a shift toward socially aware and data-driven algorithmic solutions. Scientific Awards: Best paper award at International Symposium on Algorithms and Computation (ISAAC), 2023 Advising and Grants: While specific students and grants are not listed in the provided texts, Amit Kumar has supervised or co-supervised numerous publications with junior collaborators, suggesting active mentoring. His extensive collaboration network (e.g., with Anupam Gupta, Debmalya Panigrahi, Ragesh Jaiswal) indicates leadership in research projects and likely involvement in funded grants, though specific grant details are not mentioned. Labs and Teams: No specific lab or research group name is mentioned in the provided materials. However, his frequent collaborations and supervision of research projects suggest he is part of or leads a research team in theoretical computer science and algorithms at IIT Delhi.

Christoph Lossenمشاهده پروفایل

استاد

• Algebraic Geometry
• Singularity Theory
• Computer Algebra
• +۳ مورد دیگر

Dr. habil. Christoph Lossen is a Professor at the Department of Mathematics, Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, and has served as Managing Director of the Mathematics Examination Office since 2006. His academic career spans roles such as Hochschuldozent (2002–2006) and scientific assistant (1994–2002) at TU Kaiserslautern. His research focuses on Algebraic Geometry, Singularity Theory, and Computer Algebra, with significant contributions to the development of SINGULAR software and the study of plane curve singularities and equisingular families. 1986: Abitur at Willi-Graf-Gymnasium Saarbrücken 1987–1994: Diplom in Mathematics and Economics at TU Kaiserslautern 1998: PhD (Dr. rer. nat.) at TU Kaiserslautern 2002: Habilitation in Mathematics at TU Kaiserslautern His research interests include the geometry of equisingular families, computational methods in algebraic geometry, and the analysis of plane curves with prescribed singularities. He has co-authored foundational books such as Introduction to Singularities and Deformations and developed SINGULAR libraries for equisingular strata and AG codes. The 15 most recent publications highlight his work on singularity theory, computer algebra, and equisingular deformations, with a focus on plane curves, zero-dimensional schemes, and algorithmic solutions. These span mathematics education in higher education organization (2010) to studies on Hessian determinants (2004) and minimal-degree curves (1998). Lossen has not been explicitly mentioned to advise students or receive grants in the provided text. However, he has contributed extensively to the development of SINGULAR, a computer algebra system, and co-authored influential works with G.-M. Greuel and E. Shustin.