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Ghaith HiaryView profile

Professor

• Computational Number Theory
• Analytic Number Theory
• Random Matrix Theory
• +3 more

Ghaith Hiary is a Professor and Vice Chair for Graduate Recruitment in the Department of Mathematics at The Ohio State University. He holds a PhD from the University of Minnesota (2008). His research focuses on computational and analytic number theory, with emphasis on the Riemann zeta function, L-functions, random matrix theory, and asymptotic analysis. Hiary's work bridges theoretical mathematics and high-performance computation. He develops efficient algorithms (e.g., amortized-complexity methods) to evaluate zeta functions at extreme heights (e.g., near t=10 28 ), implemented in C++/Mathematica. His research uses random matrix models to study zeta-function moments and employs techniques like van der Corput estimates and hybrid methods for explicit bounds. His publications demonstrate consistent focus on zeta-function computations, factorization algorithms, and arithmetic biases. Recent work (2022-2025) explores invariant measures, Lehman's method generalizations, and sign changes in random multiplicative functions, maintaining strong ties to analytic and probabilistic number theory. Hiary shares code and datasets via GitHub, including implementations of T 1/3 algorithms for zeta computations. He collaborates with institutions like the University of Waterloo and maintains numerical databases of zeta zeros.

Jia ZhangView profile

Professor

• Machine Learning
• Natural Language Processing
• Information Retrieval
• +10 more

Dr. Jia Zhang is the Inaugural Robert H. Dedman Jr. Endowed Department Chair and Professor of Computer Science at Southern Methodist University (SMU Lyle School of Engineering). She holds the Cruse C. and Marjorie F. Calahan Centennial Chair in Engineering and has a courtesy appointment in the Department of Operations Research and Engineering Management. Her research focuses on applying machine learning, natural language processing, and information retrieval to data science infrastructure, particularly scientific workflows, provenance mining, software discovery, knowledge graphs, cloud computing, immune AI, and applications in earth science and healthcare. Education: Ph.D. in Computer Science, University of Illinois at Chicago M.S. in Computer Science, Nanjing University B.S. in Computer Science, Nanjing University Dr. Zhang's work emphasizes data science infrastructure and machine learning for scientific workflows and knowledge graphs. Her recent publications highlight deep learning , graph neural networks , and optimization algorithms in cloud computing, cybersecurity, and environmental applications. Key trends include spatiotemporal modeling , hybrid neural architectures , and AI-driven service ecosystems . Scientific Awards: Best Paper Awards IEEE SCC (2011, 2017) Best Student Paper Awards IEEE ICWS (2014, 2018), IEEE ICCC (2018) Distinguished Paper Award ICSOC (2023) First Outstanding Service Award IEEE Technical Committee on Services Computing (2016) She has secured over $5 million in federal grants (as PI) and $11 million as PI/Co-PI from NSF, NASA, NIH, UTSW, Ericsson, SAP, and Google. Her lab (Caruth Hall 308) actively recruits research assistants. She previously served as a faculty member at Carnegie Mellon University, Northern Illinois University, and Nanjing University, and worked in industry as a software architect.

Paul GoulartView profile

Professor

• Robust and high-speed optimisation
• Control engineering
• Convex optimization
• +4 more

Professor Paul Goulart is a full Professor of Engineering Science at the University of Oxford and Tutorial Fellow at St Edmund Hall, positions he has held since 2014. He leads research and teaching in robust optimization, control systems, and high-speed numerical methods, with applications spanning fluid flows, traffic networks, and economics. Education SB & MSc, Aeronautics and Astronautics – Massachusetts Institute of Technology (MIT) PhD, Control Engineering – University of Cambridge (Gates Scholar, 2007) Research Interests Professor Goulart’s work lies at the intersection of control engineering and optimization . His core expertise includes: Robust and high-speed convex optimization Model predictive control (MPC) and control barrier functions Neural-network-based control and system identification Optimization over traffic and economic networks Real-time and embedded optimization solvers These interests are reflected in prolific publication output and active supervision of doctoral researchers. Publications & Trends From 2020 to 2025 Professor Goulart has co-authored more than thirty papers. A dominant theme is the development of fast, reliable algorithms for conic optimization and robust control , often leveraging machine-learning techniques to enhance scalability and real-time performance. Recent works emphasize safety certificates, GPU-accelerated solvers, and neural-network controllers for uncertain systems. Awards & Honors Gates Cambridge Scholar (2003) Advising & Grants Professor Goulart actively seeks DPhil students in control engineering and optimization . He leads the Control Group within the Department of Engineering Science and has been involved in multiple industrially funded projects, although specific grant identifiers are not provided in the supplied text. Laboratory & Teams He is a member of the Control Group , Department of Engineering Science, University of Oxford, and serves as Secretary to the Governing Body of St Edmund Hall (Michaelmas Term 2024).

• Biomaterials
• Peripheral Nerve Injury
• Neuromuscular Modeling and Repair
• +2 more

Suradip Das is a Research Assistant Professor in the Department of Neurosurgery at the Perelman School of Medicine, University of Pennsylvania, where he serves as a Senior Research Investigator. His work bridges neural engineering and regenerative medicine to address critical challenges in nerve and muscle repair. His academic training includes: B.Tech in Biotechnology from Heritage Institute of Technology (2010) PhD in Biosciences and Bioengineering from Indian Institute of Technology Guwahati (2016) Dr. Das specializes in biomaterials development , peripheral nerve injury models , neuromuscular interface engineering , and stem cell-based regeneration . His research pioneers innervated tissue-engineered muscle constructs, demonstrating how motor neurons and endothelial cells synergistically enhance skeletal myocyte maturation. He innovates custom mechanobioreactors that apply tensile forces to guide nanofiber alignment for optimal myofiber formation, significantly advancing volumetric muscle loss treatments. Analysis of his 15 most recent publications reveals a dominant focus on neuromuscular regeneration (75% of articles), with emerging exploration of psychedelic compounds in neural repair. His work consistently integrates human iPSC-derived models , multi-cellular co-cultures , and large-animal validation to address translational gaps. Key trends include optogenetic control of motor units (2023), porcine nerve injury models (2020), and the critical role of pre-innervation in creating pro-regenerative microenvironments (2020-2022). As a core member of the Cullen Lab, Dr. Das collaborates on developing biofabricated neural microtissues for delayed nerve fusion and rapid functional recovery. His research directly informs clinical strategies for peripheral nerve repair and muscle regeneration through rigorous mechanistic studies and innovative engineering solutions.

Foteini MourkiotiView profile

Associate Professor

• Muscle Stem Cell Biology
• Mechanobiology
• Aging
• +7 more

Foteini Mourkioti is an Associate Professor at the University of Pennsylvania's Perelman School of Medicine , with a joint appointment in the Graduate Groups of Cell and Molecular Biology and Bioengineering . She co-directs the Musculoskeletal Regeneration Program at the Penn Institute of Regenerative Medicine and leads the McKay Orthopaedic Research Laboratory . Research Interests : Muscle Stem Cell Biology Mechanobiology Muscle Regeneration Telomere Biology in Muscular Diseases Fibrodysplasia Ossificans Progressiva (FOP) Cardiomyopathy and Aging Key Research Contributions : Developed the Pax7EGFP mouse model for real-time muscle stem cell tracking Discovered telomere shortening as a critical factor in Duchenne Muscular Dystrophy Elucidated the role of NF-κB in muscle stem cell dysfunction Identified Piezo1's role in stem cell morphological states Characterized fibro-adipogenic progenitor dynamics in FOP Scientific Awards : NIH/NHLBI R01 grant recipient (2019) NASA grant awardee (2020, 2017) American Heart Association grant (2017) Muscular Dystrophy Association grant (2019) University Research Foundation grant (2018) Publications & Collaborations : Over 25 publications in high-impact journals like Science Advances , Nature Protocols , and Cell Reports . Collaborates with Penn Cardiovascular Institute and Pennsylvania Muscle Institute.

Phil G. CampbellView profile

Research Professor

• Growth Factor Bioavailability
• Musculoskeletal Tissue Repair
• Biomimetic Materials
• +2 more

Dr. Phil G. Campbell is a Research Professor at Carnegie Mellon University with joint appointments in Biomedical Engineering, Biological Sciences, and Materials Science & Engineering. His research explores growth factor bioavailability and biomimetic tissue engineering. Campbell's laboratory investigates cellular microenvironments, focusing on how growth factors interact with extracellular matrices and influence tissue regeneration. His work spans basic science of protein-material interactions and applied research in cardiac, skeletal, and corneal tissue engineering. He has co-authored over 15 peer-reviewed publications and holds 10 US patents. Campbell received the Benjamin Richard Teare Teaching Award in 2018 and contributes to the Molecular Biosensor and Imaging Center at CMU.

Jason WebberView profile

Senior Lecturer

• Extracellular Vesicles (EVs)
• Tumour Microenvironment
• Prostate Cancer
• +6 more

Dr. Jason Webber is a Senior Lecturer in Biomedical Sciences at Swansea University Medical School. He holds an honorary position as a Research Fellow at Cardiff University and is a board member of the UK Society for Extracellular Vesicles. His research focuses on extracellular vesicles (EVs), particularly their role in cancer progression and as biomarkers for aggressive tumors like prostate cancer. He completed his PhD at Cardiff University's Institute of Nephrology in 2009 and received a Prostate Cancer UK Career Development Fellowship (2014–2020). Dr. Webber's expertise includes EV biology, tumor microenvironment dynamics, and translational research. He actively contributes to teaching modules such as 'Genetics of Cancer' and 'Advanced Research Topics in Biomedical Science'. His work spans collaborations with institutions like Erasmus MC and the CIC bioGUNE in Spain. Key grants include funding for projects like 'Extracellular Vesicle Glycoproteins for Prostate Cancer Diagnosis (EVGlyProD)' and investigations into EV roles in bone metastasis and rare diseases like tuberous sclerosis complex. His research highlights EVs' dual role as functional mediators of tumor growth and potential biomarkers. Notable achievements include demonstrating EV-HSPG's role in stromal activation and developing methodologies for EV-based diagnostics. Dr. Webber supervises multiple PhD and MSc students, emphasizing mentorship in EV research and cancer biology.

• Mechanobiology
• Biomechanics
• Organ-on-chip
• +5 more

Associate Professor Arnold Lining Ju is a biomedical engineer at the University of Sydney's School of Biomedical Engineering, affiliated with multiple institutes including the Heart Research Institute and Sydney Nano Institute. He holds academic positions in both the Faculty of Engineering and Faculty of Medicine & Health. Education: BSc from Peking University, PhD from Georgia Tech and Emory University (USA). Honors include Snow Fellowship, Heart Foundation Future Leader Fellowship, and multiple awards for cardiovascular research innovation. Research focuses on mechanobiology and biomechanics of thrombosis, developing microfluidic devices and organ-on-chip systems. Key projects include AI-driven single-cell nanotools, 3D biofabrication, and anti-thrombotic peptide design. Leads interdisciplinary teams and collaborates internationally with institutions like Harvard and University of Texas. Teaching roles include coordinating advanced cellular biomechanics courses and supervising PhD/Masters students in biomedical engineering and physiology. Over 50 peer-reviewed publications, with contributions to Nature Materials, Nature Communications, and other top journals.

• Ophthalmology
• Corneal Diseases
• Keratoconus
• +3 more

Professor Gerard Sutton is an Honorary Professor in the Faculty of Medicine and Health at the University of Sydney, affiliated with the Save Sight Institute and Vision Eye Institute. He specializes in corneal and refractive surgery, combining clinical practice with research in keratoconus, corneal bioengineering, and global eye care. His work includes developing the Australian Corneal Bioengineering Centre and pioneering innovations like the Corneal Biopen for treating corneal defects. Research interests span clinical and laboratory-based studies, focusing on corneal transplantation, bioengineered treatments, and refractive surgery outcomes. Current projects include corneal bioengineering, keratoconus pathogenesis, and SMILE surgery clinical outcomes. He holds memberships in prominent ophthalmology societies like RANZCO and APPO. Awards: 2019 RANZCO John C. Parr Medal Lecture Award 2017 Sydney Research Centre ‘Big Idea’ Innovation Award 2015 XOVA Excellence in International Ophthalmology 2014 Asia Pacific Academy of Ophthalmology Achievement Award Grants & Funding: AU$35M BIENCO consortium (2023) for corneal blindness therapies AU$1.1M Corneal Biopen commercialization (2018) NHMRC Ideas Grant for bioengineered corneal layers (2019) His research group collaborates internationally, with projects addressing corneal transplantation equity, bioink development, and regenerative solutions for ocular surface diseases. Clinical affiliations include Sydney Eye Hospital and the Lions NSW Eye Bank.

Mathias DrtonView profile

Professor

• Graphical models
• Algebraic statistics
• Causal inference
• +3 more

Prof. Mathias Drton holds the Chair of Mathematical Statistics at the Technical University of Munich (TUM), within the Department of Mathematics and School of Computation, Information and Technology. His research focuses on graphical models, algebraic statistics, causal inference, and multivariate data analysis. He has authored numerous publications in top-tier journals and conferences, including work on conditional independence, sparse factor analysis, and causal discovery in linear models. Drton has supervised a large number of theses, mentoring students in areas like high-dimensional statistics, graphical models, and causal inference. He is actively involved in teaching advanced courses such as 'Graphical Models in Statistics' and 'Fundamentals of Mathematical Statistics.' His academic contributions span theoretical developments in statistical methodology and computational tools, including R packages like SEMID and symRC . Drton collaborates internationally, contributing to projects like the TUM-ICL Mathematical Sciences Hub and Exzellenzcluster MCQST. His work bridges algebraic methods with statistical challenges, addressing identifiability in latent variable models and robust graphical modeling under non-Gaussian assumptions. Recent research emphasizes causal structure learning under partial homoscedasticity, distribution-free independence tests, and multi-domain causal representation learning. Drton’s lab actively explores applications in genomics, epidemiology, and machine learning, leveraging both theoretical rigor and practical computational methods.

• Conservation ecology
• Population ecology
• Landscape ecology
• +3 more

Robert Fletcher is a Researcher at the University of Cambridge, affiliated with the Department of Zoology and the C-CLEAR Doctoral Training Partnership . His work focuses on applied ecology and conservation science, utilizing landscape and population ecology to address biodiversity challenges globally. Research Areas : Conservation biology, population ecology, landscape ecology, environmental informatics Collaborations : Partners in North America, Europe, Africa, and Southeast Asia Key Themes : Species extinction prevention, landscape conservation prioritization, and rapid biodiversity data delivery Email : rf497@cam.ac.uk Fletcher's interdisciplinary approach integrates fieldwork (e.g., Everglades endangered species, African elephants) with advanced modeling of habitat loss, fragmentation, invasive species, and climate change impacts. His recent work emphasizes: Drivers of species decline and recovery strategies Landscape management and restoration techniques Interdisciplinary collaborations with engineers, social scientists, and computer scientists His publications span topics like savanna ecosystem dynamics, community science applications, and conservation forecasting, reflecting a commitment to actionable science for global biodiversity preservation.

• Skeletal Muscle Growth
• Ribosome Biogenesis
• Exercise Physiology
• +4 more

Gustavo Nader, Ph.D., is a Professor of Kinesiology at The Pennsylvania State University's College of Health and Human Development, where he holds the Dorothy Foehr Huck and J. Loyd Huck Endowed Chair in Molecular, Cellular and Integrative Physiology. His research laboratory at 101 Noll Lab focuses on molecular mechanisms of skeletal muscle adaptation, employing human, animal, and cellular models to investigate ribosome biogenesis, transcriptional regulation, and muscle growth control in contexts ranging from exercise hypertrophy to cancer cachexia. Dr. Nader's research examines fundamental processes including: Ribosome biogenesis and its role in muscle growth regulation Epigenetic control of RNA Polymerase I activity Molecular pathways in mechanical overload-induced hypertrophy Tumor-induced muscle wasting mechanisms Biomimicry approaches inspired by hibernator physiology His work spans exercise physiology, cancer biology, and environmental stress responses. Analysis of his 15 most recent publications (2015-2025) reveals predominant themes in muscle hypertrophy mechanisms, cancer cachexia pathophysiology, ribosomal function analysis, and environmental stress impacts on muscle. His work consistently integrates molecular techniques with physiological models across species. Notable scientific recognitions include: Dorothy Foehr Huck and J. Loyd Huck Chair appointment (2024) Huck Institutes Leadership Fellowship (2025-2026) Dr. Nader leads an active research team investigating muscle plasticity, with current projects funded through the Huck Institutes of the Life Sciences. He collaborates extensively through Penn State's Integrative and Biomedical Physiology graduate program and Center for Cellular Dynamics.

Mehdi YazdiView profile

Lecturer

• Low-dimensional topology
• Geometry
• Dynamics
• +9 more

Mehdi Yazdi is a Lecturer in Pure Mathematics at King's College London, part of the Department of Mathematics within the Faculty of Natural, Mathematical & Engineering Sciences. His research focuses on low-dimensional topology, geometry, and dynamics, with particular emphasis on 3-dimensional manifolds, foliations, mapping class groups, and algorithmic aspects of topology. He holds a PhD from Princeton University (2017) and has held postdoctoral fellowships at the University of Oxford, including the Glasstone Research Fellowship in Science, Titchmarsh Research Fellowship, and a UKRI Postdoctoral Research Fellowship. Education: PhD in Pure Mathematics from Princeton University (2017). Prior to King's College, he was at Oxford from 2017–2021. Research interests include the study of geometric structures on manifolds, algorithmic problems in topology, and the interplay between dynamics and geometry. His work has contributed to understanding foliations, knot theory, and computational aspects of topological invariants. Publications span topics like the stability of foliations, Thurston norms, and computational complexity of knot genus, reflecting his expertise in both theoretical and algorithmic dimensions of geometry and topology. He is a member of the Geometry Group at King's, which explores areas such as algebraic geometry, cohomology theories, and symplectic geometry. His research also engages with broader questions in geometric analysis and low-dimensional dynamics.

• High Performance Computing
• Numerical Algorithms and Software
• High Performance Big Data Analytics
• +4 more

Panruo Wu is an Associate Professor in the Department of Computer Science at the University of Houston (UH). He joined UH in 2018 as an Assistant Professor, transitioning to his current rank. His research focuses on high-performance computing, numerical algorithms, parallel and distributed systems, and fault tolerance. He holds a Ph.D. in Computer Science from the University of California, Riverside (2016), advised by Zizhong Chen, and a B.S. in Mathematics from the University of Science and Technology of China (USTC). Research Interests: His work spans high-performance computing, numerical linear algebra, GPU acceleration, fault-tolerant systems, and scalable machine learning. Key projects include LATER (Linear Algebra on Tensor Cores), LibKernel (a scalable kernel machine framework), and Wukong (a serverless parallel computing framework). He emphasizes energy-efficient and hardware-aware algorithms. Publications: Dr. Wu's recent work includes advancements in QR factorization using tensor cores, symmetric eigenvalue decomposition optimizations, and fault-tolerant algorithms for heterogeneous systems. His research often addresses computational challenges in big data and exascale computing. Awards & Grants: Received NSF Grant No. 2146509. His work on high-accuracy matrix computations was a Best Paper Nominee at HPDC'20. He has authored over 30 peer-reviewed publications in top venues like SC, ICS, and IEEE TPDS. Students & Advising: Advises PhD students including Shaoshuai Zhang, Ruchi Shah, Benjamin Carver, and Ao Wang. His students have contributed to projects like LibKernel and fault-tolerant linear algebra libraries. Labs & Collaborations: Leads research in UH's high-performance computing group, collaborating with institutions like Jack Dongarra's Innovative Computing Lab (University of Tennessee) and industry partners on exascale computing initiatives.

Petter N. KolmView profile

Clinical Professor

• Quantitative Trading Strategies
• Delegated Portfolio Management
• Financial Econometrics
• +5 more

Petter N. Kolm serves as a Clinical Professor of Mathematics and Program Director at New York University, with his office located in Warren Weaver Hall (520). He can be contacted at petter.kolm@nyu.edu or 212-998-4855, and holds an editorial board position at the Journal of Portfolio Management. His academic qualifications include: Doctorate in Mathematics from Yale University M.Phil. in Applied Mathematics from the Royal Institute of Technology in Stockholm M.S. in Mathematics from ETH Zurich Dr. Kolm's research centers on quantitative finance, with primary focus areas including quantitative trading strategies, delegated portfolio management, financial econometrics, risk management, and optimal portfolio strategies. His work integrates advanced mathematical modeling with practical investment applications, bridging theoretical frameworks and real-world market dynamics through rigorous empirical analysis. Analysis of his 15 most recent publications reveals consistent emphasis on portfolio optimization techniques—particularly Bayesian methods and the Black-Litterman model—alongside significant contributions to algorithmic trading systems, factor-based equity portfolio construction, and machine learning applications for financial sentiment analysis. His scholarly output demonstrates evolution from foundational portfolio theory toward contemporary computational finance challenges. As Program Director, Dr. Kolm oversees academic programming and likely mentors graduate students in quantitative finance, though specific advisee details are not documented. His prior industry role at Goldman Sachs Asset Management provided direct experience in developing hedge fund strategies, informing his applied research approach. Dr. Kolm's professional trajectory includes significant industry engagement through his tenure in Goldman Sachs' Quantitative Strategies Group, where he developed quantitative investment systems. His current academic leadership position leverages this practical experience to shape quantitative finance education and research at NYU.