Find Academic Supervisors

• Graph Theory
• Domination in Graphs
• Isolation in Graphs
• +3 more

Geoffrey Boyer is a Lecturer at Clemson University's College of Science , affiliated with the Department of Mathematical and Statistical Sciences . He obtained a B.S. in Mathematics from Wake Forest University (2020) and an M.S. in Mathematics from Clemson University (2024). B.S., Mathematics, Wake Forest University, 2020 M.S., Mathematics, Clemson University, 2024 Research Interests: Graph Theory Domination in Graphs Isolation in Graphs Graph Coloring Recent work focuses on domination and isolation parameters in graphs, particularly examining the effects of matching removal on graph stability. Publications from 2023-2024 address disjoint isolating sets, total isolation, and computational methods in graph theory. Contact Information: Phone: 864-656-3434 Email: gboyer@clemson.edu Office: Jordan Hall G15 Department: O-110 Martin Hall Hours: Monday-Friday, 8 a.m.-4:30 p.m.

Wayne GoddardView profile

Professor

• Graph Theory
• Discrete Mathematics
• Algorithms
• +1 more

Wayne Goddard is Professor at Clemson University with joint appointments in the School of Computing and School of Mathematical and Statistical Sciences within the College of Science. He specializes in discrete mathematics with research focusing on graph theory, algorithms, and combinatorial optimization. His research explores fundamental questions in graph theory including domination parameters, isolation numbers, packing problems, and graph toughness. Recent publications examine extremal values of graph invariants, structural properties of regular graphs, and combinatorial optimization techniques. Goddard has developed educational materials covering algorithms, graph theory, discrete mathematics, and programming. He teaches courses including Data Structures, Algorithms, Linear Algebra, and Graph Theory at both undergraduate and graduate levels. He is recognized as a Fellow of The Institute of Combinatorics and its Applications, reflecting his contributions to discrete mathematics. His research continues to advance understanding of structural graph properties and combinatorial optimization techniques.

Beth A NovickView profile

Lecturer

• Combinatorial Optimization
• Discrete Mathematics
• Graph Theory
• +7 more

Beth A Novick is a Principal Lecturer in the Department of Mathematical and Statistical Sciences at Clemson University, part of the College of Science. She holds a Ph.D. in Operations Research from Carnegie Mellon University (1990) and completed a postdoctoral fellowship at the University of Waterloo's Department of Combinatorics and Optimization (1990–91). Her primary research focuses on combinatorial optimization, discrete mathematics, graph theory, and related areas including median graphs, metric dimension, and reconfiguration graphs. She has been affiliated with Clemson University since 1992. Her research interests encompass integer programming, algebraic graph theory, matroids, and closure systems. Notable contributions include studies on reconfiguration graphs of shortest paths and geometric interpretations of threshold dimensions. She is a member of the American Mathematical Society and Women in Combinatorics. Teaching responsibilities include courses such as Linear Algebra and Graph Theory. No scientific awards or grants are explicitly listed in the provided information. Her work spans theoretical advancements in discrete mathematics and applications in graph-based optimization problems.

Ping ZhangView profile

Professor

• Graph Theory
• Combinatorics
• Discrete Mathematics
• +2 more

Dr. Ping Zhang, Distinguished University Faculty Scholar and Professor of Mathematics at Western Michigan University, is a renowned researcher in graph theory and combinatorics. She has authored 6 textbooks and over 340 research papers, with editorial roles at SpringerBriefs in Mathematics and the Journal of Algebraic Combinatorics. Research Impact: Her influential works include pioneering studies in graph colorings, labelings, and decompositions. Her co-authored book The Fascinating World of Graph Theory (Princeton University Press) received a 2015 Choice Magazine Outstanding Academic Title award. She has mentored 26 doctoral students to completion.

Daniel HerdenView profile

Associate Professor

• Algebra
• Set Theory
• Combinatorics
• +2 more

Daniel Herden is an Associate Professor in the Department of Mathematics at Baylor University's College of Arts & Sciences. He earned his Habilitation (2013) and Dr. rer. nat. (2005) from the University of Duisburg-Essen, Germany. His research spans algebra-set theory interactions, combinatorics applications, and coding theory. Herden maintains strong international collaborations and currently serves on the problem proposal committee of the German Mathematical Olympiad. Research interests focus on constructing large algebraic structures under set-theoretic constraints, applications of infinite combinatorics to algebra, finite combinatorics in symplectic geometry and partitions, and emerging work in coding theory at the algebra-combinatorics interface. Herden's publication trends demonstrate sustained contributions to pure mathematics, with recent work expanding into applied combinatorics and coding theory. Earlier research emphasized foundational work in set-theoretic algebra and module theory. Scientific honors include: 3 Silver Medals at International Mathematical Olympiad (1997-1999) Ranked #2 in German Math Olympiad Hall of Fame 5 First Prizes in German Mathematical Olympiad 3 First Prizes at German Federal Math Competition He advises PhD students in algebra and combinatorics, with current joint supervision in coding theory. Former students have completed dissertations on incidence algebras, group automorphisms, and forcing methods in group theory.

Sanjiv K. BhatiaView profile

Professor

• Image Processing
• Computer Vision
• Digital Terrain Modeling
• +4 more

Sanjiv K. Bhatia is a Professor and Director of Graduate Computer Science Programs (M.S. and Ph.D.) at the University of Missouri–St. Louis. He holds a Ph.D. in Computer Science from the University of Nebraska-Lincoln (1991), an M.S. from the University of Arkansas (1987), and a B.E. in Computer Science Engineering from Motilal Nehru National Institute of Technology (1983). His research focuses on Image Processing, Computer Vision, Digital Terrain Modeling, and Intelligent Information Retrieval. Notable contributions include the RISE image search engine and face perception databases. He has taught numerous courses, including Operating Systems, Image Processing, and Cloud Computing. His teaching philosophy emphasizes hands-on programming and problem-solving. He is active in ACM and AAAI, and his work spans academic leadership, software development, and interdisciplinary projects in environmental and forensic applications. His recent research explores geospatial analysis, urban decarbonization, and machine learning integration with environmental science. Despite no explicitly listed awards, his extensive publication record and leadership roles highlight his academic contributions.

David JuedesView profile

Professor

• Algorithms
• Complexity Theory
• Approximation Algorithms
• +4 more

David Juedes is a Professor of Electrical Engineering and Computer Science and Associate Dean for Academics at Ohio University's Russ College of Engineering and Technology. He also directs the Avionics Engineering Center and is part of the Center for Scientific Computing and Immersive Technologies. Juedes holds a Ph.D. from Iowa State University (1994) and has taught courses ranging from introductory computer science to advanced graduate topics like computational complexity and formal languages. His research focuses on algorithms, complexity theory, approximation algorithms, and computational biology. Notable contributions include work on secure embedded systems (e.g., d-GUARD and DAGGER frameworks) and parameterized algorithm analysis. He has advised multiple graduate and undergraduate students in areas like parameterized algorithms and bioinformatics. Juedes has received awards including ACM Senior Membership (2010) and the Russ College Outstanding Research Paper Award (2004). His work spans 30+ years with over 80 publications in top journals/conferences. He actively promotes STEM education through initiatives like cybersecurity workshops for K-12 teachers and curriculum development for real-time systems and CORBA-based resource management. Labs/Teams: Director of Avionics Engineering Center, Core member of Center for Scientific Computing and Immersive Technologies.

Pamela E. HarrisView profile

Professor

• Algebraic Combinatorics
• Representation Theory
• Graph Theory
• +4 more

Pamela E. Harris is a Professor of Mathematics in the Department of Mathematical Sciences at the University of Wisconsin-Milwaukee. She is also a cohost of the podcast Mathematically Uncensored and President and co-founder of Lathisms: Latinxs and Hispanics in the Mathematical Sciences. Education: PhD in Mathematics (2012), University of Wisconsin-Milwaukee; M.S. in Mathematics (2008), University of Wisconsin-Milwaukee; B.S. in Mathematics (2005), Marquette University; Associate Degrees in Sciences and Liberal Arts (2003), Milwaukee Area Technical College. Her research focuses on algebraic combinatorics, particularly representation theory of Lie algebras, with applications to parking functions, graph theory, and discrete mathematics. She is a leading advocate for diversity, equity, and inclusion in mathematics, mentoring underrepresented students and co-organizing symposia for SACNAS and the American Mathematical Society. Dr. Harris has authored over 65 peer-reviewed articles and coauthored books such as Asked And Answered: Dialogues On Advocating For Students of Color in Mathematics and Practices and Policies: Advocating for Students of Color in Mathematics . Her work includes developing community agreements and DEI frameworks for academic settings. Scientific Awards: MAA Deborah and Franklin Tepper Haimo Award (2023), MAA Northeast Section Award (2020), MAA Henry L. Alder Award (2019), Council on Undergraduate Research Mentor Award (2019), Karen Uhlenbeck EDGE Fellow (2020). She actively engages in promoting community-building initiatives and has contributed to national dialogues on mentorship, equity, and the intersection of mathematics with social justice.

Didem GözüpekView profile

Professor

• Graph Theory
• Approximation Algorithms
• Network Optimization
• +2 more

Didem Gözüpek is Professor in Computer Engineering at Gebze Technical University and Director of the Graph Theory and Network Optimization (GRANET) Research Laboratory. Her research examines combinatorial optimization problems in communication networks using graph-theoretic approaches. Her award-winning work includes contributions to equimatchable graph characterization, reload cost optimization, and cognitive radio network scheduling. Recent publications advance knowledge in packing coloring and structural graph theory. She leads TUBITAK-funded projects on domination in graphs and combinatorial optimization applications to urban systems.

Timothy SunView profile

Assistant Professor

• Graph Theory
• Combinatorics
• Theoretical Computer Science
• +3 more

Timothy Sun is an Assistant Professor of Computer Science at San Francisco State University (SFSU), serving as Graduate Coordinator and Advisor. His research focuses on combinatorics and theoretical computer science, particularly topological graph theory. He holds a Ph.D. (2019) and B.S. (2013) in Computer Science from Columbia University, advised by Xi Chen and Rocco Servedio in the Theory Group. He previously held positions at Emory University (2019–2020) and Columbia University (2018). His Erdős number is 3. Education: Ph.D. Computer Science, Columbia University (2019); B.S. Computer Science, Columbia University (2013, magna cum laude) Research emphasizes graph embeddings, genus calculations, and algorithmic design. Notable contributions include work on complete graph embeddings, cycle-finding algorithms, and Rubik’s Cube group commutators. Teaching includes Analysis of Algorithms I/II at SFSU and courses at Emory/Columbia. Publications span graph theory and topology, with recent work on Jungerman ladders, nonorientable genus calculations, and algorithm visualization tools like AAnim. Awards include three bronze medals in speedcubing at the 2009 World Championships. Advising activities include graduate student coordination at SFSU. No listed grants are detailed in the provided texts. Maintains a lab focused on theoretical computer science and algorithmic visualization.

Tom HayesView profile

Associate Professor

• Theoretical computer science
• Machine learning
• Markov chains
• +7 more

Tom Hayes is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, School of Engineering and Applied Sciences. His research focuses on theoretical computer science and machine learning, with particular emphasis on convergence rates for Markov chains, sampling algorithms, physics of algorithms, and distributed algorithms for radio-enabled sensor networks. Dr. Hayes holds a PhD in Computer Science from the University of Chicago. His academic journey has led him to specialize in probabilistic methods and theoretical foundations of computing. His research interests span theoretical computer science with applications to machine learning. He investigates fundamental questions about how algorithms behave, particularly focusing on Markov chains, random combinatorial structures, and distributed systems. His work bridges theoretical computer science with practical applications in networked systems and optimization problems. His research has significant implications for understanding algorithmic behavior in complex systems. Analysis of his recent publications reveals a consistent focus on theoretical aspects of distributed computing, graph algorithms, and probabilistic methods. His work shows increasing attention to energy efficiency in wireless networks and optimal mixing properties of Markov chains. The research demonstrates strong connections between theoretical computer science and practical applications in network design and analysis. Dr. Hayes actively contributes to the academic community through publications at major theoretical computer science conferences. His work appears regularly in proceedings of conferences like APPROX/RANDOM, reflecting his standing in the theoretical computer science community. He serves as an educator in the Computer Science department, teaching foundational courses including CSE 191 (Intro Discrete Structures) and CSE 331 (Algorithms and Complexity). His teaching emphasizes theoretical foundations while connecting concepts to practical applications in computer science.

Zi-Xia SongView profile

Professor

• Graph Theory
• Combinatorics
• Structural Graph Theory
• +4 more

Zi-Xia Song is a Professor in the Department of Mathematics at the University of Central Florida (UCF), where she has served since 2005 and was promoted to Full Professor in 2019. She advises both graduate and undergraduate students while maintaining active research and editorial roles. Education: Ph.D. in Algorithms, Combinatorics and Optimization from Georgia Institute of Technology (2004) under Robin Thomas Postdoctoral: Zassenhaus Assistant Professor at The Ohio State University Research Interests: Dr. Song's work centers on Graph Theory and Combinatorics , with deep specialization in structural and extremal graph theory. Her current investigations include: Hadwiger’s conjecture and related structural problems Ramsey theory (co-critical graphs, Gallai-Ramsey numbers) Erdos-Lovasz Tihany conjecture Star edge-colorings Turan and anti-Ramsey numbers in planar graphs Awards: Two Teaching Incentive Program (TIP) awards for instructional excellence One Research Incentive Program (RIA) award for field-advancing publications Advising and Funding: As sole Principal Investigator, Dr. Song has secured major external funding including: National Science Foundation Grant DMS-2153945 (current) National Science Foundation Grant DMS-1854903 (past) National Security Agency Grant H98230-09-1-0055 (past) She also serves on NSF review panels and mentors students across degree levels while advancing her research agenda through journal editorial work.

Alexander GolovnevView profile

Assistant Professor

• Computational Complexity
• Algorithms
• Pseudorandomness
• +2 more

Alexander Golovnev is an Assistant Professor at Georgetown University's Computer Science Department. His research focuses on computational complexity, algorithms, pseudorandomness, learning theory, and cryptography. He received his PhD from New York University in 2017, advised by Oded Regev and Yevgeniy Dodis, with postdoctoral positions at Columbia University, Yahoo Research, and Harvard University. His current teaching includes Matrix Rigidity (Spring 2025) and Introduction to Algorithms. He has developed a 5-Course Specialization on Discrete Mathematics and organized workshops on Matrix Rigidity and Fine-Grained Cryptography. Service includes program committees for CSR'22, FOCS'22, STOC'24, CCC'24, and ITC'25. Research interests span quantum computing reductions, lattice problems, circuit complexity, and fine-grained cryptography. His recent publications explore worst-case to average-case reductions, function inversion tradeoffs, and SNARK constructions. Awards include NSF CAREER Award (2024), Rabin Postdoctoral Fellowship (2018-2020), and IPEC excellent student paper award (2012). Current PhD/Master's advisees: Sidhant Saraogi (joint with Justin Thaler), Karthik Gajulapalli, Samuel King, and Satyajeet Nagargoje.

• Computer Vision
• Data Science
• Data Visualization
• +5 more

Michael D. Grossberg is an Assistant Professor in the Department of Computer Science at the City College of New York (CUNY). He is affiliated with the NOAA-CREST Institute and the Computational Science of Data Intensive Remote Sensing (CS:dir$) group. His research spans interdisciplinary fields including computer vision, data science, remote sensing, climate science, and medical imaging. Grossberg holds a BA in Mathematics from the University of Pennsylvania, a PhD in Mathematics from MIT, and has held academic positions at Columbia University before joining CCNY. Education: Bachelor of Arts in Mathematics, University of Pennsylvania Doctor of Philosophy in Mathematics, Massachusetts Institute of Technology Postdoctoral Fellow at Hebrew University (Jerusalem) Assistant Professor of Mathematics, Columbia University Instructor and Research Scientist in Computer Science, Columbia University Research Interests: Grossberg's work focuses on applying computational methods to solve challenges in science and engineering. Key areas include: Quantitative image restoration for satellite data (e.g., MODIS, VIIRS) Machine learning applications in climate modeling and sea ice classification Semi-automatic medical image segmentation for radiation treatment planning Data visualization tools for climate and remote sensing data Lossless compression algorithms for Earth science imagers His research is supported by grants from NIH, NOAA, NASA, and the Office of Naval Research. Grants & Collaborations: NIH P20 grant for medical image segmentation NOAA-funded projects on satellite data restoration and compression Climate research collaborations with Columbia University and Memorial Sloan Kettering Cancer Center Labs & Teams: Grossberg leads the CCNY research lab focusing on interdisciplinary projects. Collaborators include Irina Gladkova (NOAA-CREST), Gikas Mageras (MSKCC), and climate scientist Niko Krakauer. His lab supports student projects in web development, data science, and medical imaging through programs like the NOAA-CREST HIRES initiative.

• Quantum Topology
• Skein Modules
• Character Varieties
• +4 more

Adam Sikora is a Professor of Mathematics at the State University of New York at Buffalo, affiliated with the Department of Mathematics in the College of Arts and Sciences. His research focuses on quantum topology, skein modules, character varieties, and their interactions with algebra, number theory, and geometry. Education: PhD in Mathematics from the University of Maryland, College Park. Research Interests: Quantum topology, including skein modules and knot invariants Character varieties and their moduli spaces Interactions between topology, algebra, and number theory Low-dimensional topology and geometric group theory Recent work emphasizes categorification of skein modules, SL(n)-skein algebras, and applications to quantum invariants. His research also explores connections between topological structures and algebraic geometry. No scientific awards are explicitly listed in the provided materials. Advising and grants are not detailed in the texts, though his publications indicate active collaboration with researchers like J.H. Przytycki and Thang T.Q. Le.