جست‌وجوی استاد و پژوهشگر

• Pain Management
• Interventional Pain Procedures
• Chronic Pain
• +۳ مورد دیگر

Michael Sabia, MD, serves as Associate Professor of Anesthesiology at Cooper Medical School of Rowan University (CMSRU), where he holds dual leadership roles as Division Head of Pain Management and Fellowship Program Director at Cooper University Hospital in Camden, NJ. His academic appointment and clinical responsibilities position him at the forefront of pain medicine education and practice. Dr. Sabia's training pathway includes: Medical School: New York Medical College, Fifth Pathway Program (Valhalla, NY) Internship: Cooper University Hospital (Camden, NJ) Residency: Anesthesiology, Cooper University Hospital (Camden, NJ) Fellowship: Pain Medicine, Beth Israel Medical Center (New York, NY) His research program centers on interventional solutions for intractable pain, with particular emphasis on spinal cord stimulation techniques, radiofrequency ablation protocols, and management of post-surgical pain syndromes. Clinical expertise extends to complex regional pain syndrome and urogenital pain disorders, informed by pharmacological research on ketamine mechanisms. Publication trends reveal a strategic progression from foundational clinical research (2011 translational modeling study) toward educational leadership, culminating in two authoritative textbooks that establish standardized approaches to interventional pain procedures. This trajectory demonstrates growing influence in both clinical practice guidelines and pain medicine pedagogy. Professional recognition includes multiple consecutive 'Top Physician' designations from South Jersey Magazine: South Jersey Magazine Top Physicians (2012, 2013, 2014) Top Docs designation (2012-2014) Medtronic Fellowship Award Marion Skriloff Scholarship Fund award Resident of the Quarter at Cooper University Hospital As Fellowship Program Director, Dr. Sabia oversees comprehensive training that integrates clinical rotations, research participation, and educational development. His division maintains active collaborations with anesthesia, neurology, and physical medicine departments to deliver multidisciplinary pain care while advancing procedural techniques through ongoing clinical innovation. Professional engagement spans society leadership roles including Treasurer of Camden County Medical Society and Executive Membership in the Society of Academic Anesthesiology Associations, reflecting commitment to both local practice standards and national specialty advancement through organizations like the American Society of Anesthesiologists and American Academy of Pain Management.

Eran Rabaniمشاهده پروفایل

استاد

• Theoretical and computational chemistry
• Nanomaterials
• Quantum dots
• +۷ مورد دیگر

Prof. Eran Rabani is a distinguished researcher and professor holding dual appointments at Tel Aviv University's School of Chemistry and the University of California, Berkeley's Department of Chemistry. At UC Berkeley, he holds the prestigious Glenn T. Seaborg Chair in Physical Chemistry and serves as a Faculty Scientist at Lawrence Berkeley National Laboratory. His research bridges theoretical chemistry, computational physics, and nanomaterials science, with significant contributions to understanding quantum phenomena at the nanoscale. Prof. Rabani earned his Ph.D. in Theoretical Chemistry from The Hebrew University in 1996, followed by postdoctoral research at Columbia University. His academic career progressed from Senior Lecturer to full Professor at Tel Aviv University, where he has maintained a continuous appointment since 1993. His educational background includes a summa cum laude B.Sc. from the Special Program "Amirim" at The Hebrew University. Rabani's research program centers on three interconnected pillars: Optoelectronic Properties of Nanomaterials , where his group develops computational models to describe exciton fine structure and phonon interactions in nanocrystals; Quasiparticle Dynamics , investigating electron transfer processes in nanoscale systems; and Stochastic Electronic Structure Methods , pioneering computational approaches that dramatically reduce the complexity of quantum simulations. His work combines theoretical innovation with practical applications in renewable energy, sensing technologies, and quantum information processing. Analysis of Rabani's recent publications reveals a strong emphasis on quantum confinement effects, exciton dynamics, and the development of stochastic computational methods that enable simulations of previously intractable systems. His research demonstrates increasing interdisciplinary collaboration, particularly with experimental groups working on quantum dots, perovskites, and other nanomaterials, with a clear trajectory toward solving real-world problems in energy conversion and quantum technologies. Prof. Rabani's contributions have been recognized with numerous prestigious awards: International Association of Advanced Materials Fellow (2023) Humboldt Research Award (2022) Vebleo Fellow for Prominence and Leadership in Science (2021) Glenn T. Seaborg Chair in Physical Chemistry (2017) Baker Symposium Speaker at Cornell University (2016) Kavli Frontiers of Science Alumni (2015) Marko & Lucie Chaoul Chair for Theoretical and Computational Nanoscience (2013) His research program is supported by substantial funding from major agencies including the National Science Foundation, Department of Energy, and Israel Science Foundation. Current grants (2021-2025) total over $2.5 million, focusing on semiconductor nanowires, computational materials science, and optoelectronic materials. As Director of The Sackler Center for Computational Molecular and Materials Science at Tel Aviv University, he leads a vibrant research group that bridges theoretical innovation with experimental validation. Prof. Rabani directs The Sackler Center for Computational Molecular and Materials Science at Tel Aviv University and has served in various administrative roles including Vice President for Research and Development. His research group maintains strong collaborations with experimentalists worldwide, creating an intellectual community focused on advancing fundamental understanding of nanoscale phenomena while exploring practical applications in energy, sensing, and quantum technologies.

Sapna Sarupriaمشاهده پروفایل

دانشیار

• Molecular Simulations
• Statistical Mechanics
• Computational Chemistry
• +۵ مورد دیگر

Sapna Sarupria is an Associate Professor in the Department of Chemistry at the University of Minnesota with adjunct appointments at Michigan Technological University (Physics) and Clemson University (Chemical and Biomolecular Engineering). Her research develops cutting-edge computational methods to solve complex problems in condensed matter systems, with applications spanning sustainable energy, biotechnology, and public health. Her academic background includes: PhD in Chemical Engineering from Rensselaer Polytechnic Institute (2009) MS in Chemical Engineering from Texas A&M University (2004) Professor Sarupria's work centers on surface-driven phenomena using molecular modeling and statistical mechanics. The SAMPEL Lab (Simulations and Advanced Methods for Probing Energy Landscapes) pioneers rare event sampling techniques to study previously intractable processes like ice nucleation and protein-surface interactions. Current projects address critical challenges in water purification membranes, enzymatic reactions, and vaccine stabilization, combining method development with real-world applications in energy and biotechnology. Her research bridges computational chemistry with materials science and biophysics through innovative simulation approaches. Recent 2025 publications demonstrate strong integration of machine learning with molecular simulation, particularly in polymorph prediction (LeaPP framework) and solvent-inclusive hybrid methods. Key themes include nucleation kinetics, virus-excipient interactions for biologics, and thermodynamic stabilization mechanisms. These works span computational chemistry, biophysics, and materials science, with consistent focus on developing transferable methodologies for condensed phase phenomena. Professor Sarupria actively mentors students through the SAMPEL Lab's inclusive environment, currently advising 8 PhD candidates with diverse backgrounds. Her leadership extends to departmental DEI initiatives and national roles in AIChE and ACS. The lab maintains robust collaborations with experimental groups at multiple institutions, translating computational insights into practical solutions for membrane technology and biologic formulation. Students gain expertise in high-performance computing while contributing to projects with direct societal impact in water sustainability and vaccine development.

Olivier Serreمشاهده پروفایل

استاد

• theoretical computer science
• automata theory
• formal languages
• +۷ مورد دیگر

Olivier Serre is a CNRS Research Director working at the Institute for Research in Fundamental Computer Science (IRIF), a joint research unit of CNRS and University of Paris. Since September 2021, he serves as Deputy Scientific Director at the Institute for Information Sciences and Technologies (INS2I) at CNRS. His research focuses on theoretical computer science with particular emphasis on automata theory and formal verification frameworks. Dr. Serre completed his education at ENS Cachan (1999-2003) and earned his PhD in Computer Science from Paris-Diderot University (now University of Paris) in 2004. Following a postdoctoral position at RWTH Aachen, he joined LIAFA (now IRIF) as a research fellow in 2005 and became a CNRS Research Director in 2016. His academic journey reflects deep engagement with foundational theoretical problems and their practical verification applications. His research centers on automata theory and formal languages, with particular expertise in games and logic, infinite structures, and verification of higher-order functional programs. Dr. Serre has made significant contributions to collapsible pushdown systems, recursion schemes, and parity games, bridging theoretical foundations with practical applications in program verification. His work demonstrates exceptional depth in developing decision procedures for complex verification problems previously considered intractable. Dr. Serre's extensive publication record in premier theoretical venues shows consistent contribution to advancing the state of the art. His research trajectory reveals a clear evolution from foundational automata theory toward increasingly sophisticated systems involving higher-order computation and imperfect information, with notable breakthroughs in establishing decidability results for complex verification problems.

Pierre-Antoine Thouveninمشاهده پروفایل

استادیار

• Signal Processing
• Inverse Problems
• Hyperspectral Image Unmixing
• +۵ مورد دیگر

Pierre-Antoine Thouvenin is an Assistant Professor at Centrale Lille, a prestigious engineering school within the University of Lille community in France. He is a member of the SigMA team from the CRIStAL laboratory (Centre de Recherche en Informatique, Signal et Automatique de Lille), where he conducts research on inverse problems with applications to remote sensing and astronomy. His academic journey began with an Engineering degree in Electronics and Signal Processing from INP - ENSEEIHT Toulouse in 2014, followed by a Master of Science in "Signal, Image, Acoustics" from the same institution. He completed his Ph.D. in "Signal, Image, Acoustics" from Institut National Polytechnique de Toulouse between 2014 and 2017, with research focused on modeling spatial and temporal variabilities in hyperspectral image unmixing. Thouvenin's research interests span several interconnected areas in signal processing and computational imaging. His primary focus is on solving inverse problems, particularly in the context of radio-interferometric imaging for astronomy and hyperspectral image unmixing for remote sensing applications. He has made significant contributions to developing advanced algorithms for handling spectral variability in hyperspectral data and for image reconstruction in radio astronomy. His work often combines Bayesian statistical methods with optimization techniques to address challenging high-dimensional problems. A distinctive aspect of his research is the development of distributed and parallel computational methods that enable processing of extremely large datasets that would be intractable with conventional approaches. An analysis of his recent publications reveals a strong trend toward developing distributed and parallel computational methods for large-scale inverse problems. His work increasingly integrates machine learning approaches, particularly neural networks, with traditional signal processing techniques. There's a clear progression from theoretical developments in hyperspectral unmixing to practical applications in astronomy, particularly through his involvement in the ORION-B project where he applies statistical methods to infer physical conditions in star-forming regions. His most recent work demonstrates sophisticated integration of spatial regularization techniques with Bayesian inference for astrophysical parameter estimation. Prix Léopold Escande from Institut National Polytechnique de Toulouse (2017) - awarded to the best PhD theses defended at INPT Prix de l'Institut National Polytechnique de Toulouse (2014) - awarded for outstanding academic achievement during engineering studies Thouvenin is actively involved in mentoring the next generation of researchers. He currently co-supervises the PhD thesis of Pierre Palud on "Statistical methods for model inversion and spatial distribution of physico-chemical properties of the molecular cloud Orion B" as part of the CNRS 80|Prime project OrionStat. His research is supported through various academic collaborations and projects, including the ORION-B project led by Jérôme Pety, which involves molecular line observations from the IRAM-30m Large Program. He has established productive international collaborations, particularly with researchers at Heriot-Watt University in Edinburgh where he worked as a Research Associate from 2017-2019. Thouvenin is a key member of the SigMA team within the CRIStAL laboratory, a joint research unit between Centrale Lille, INRIA, and University of Lille. His work often intersects with the ORION-B project, where he collaborates with astrophysicists to develop statistical methods for inferring properties of Galactic and extra-galactic star forming regions. This interdisciplinary environment fosters innovation at the intersection of signal processing, statistics, and astronomy. He has developed expertise in translating complex statistical methodologies into practical computational tools that address real-world challenges in both remote sensing and astronomical imaging.

• Bayesian Statistics
• Approximate Bayesian Computation
• Statistical Modeling
• +۶ مورد دیگر

Christopher Drovandi is a Professor at Queensland University of Technology and a Chief Investigator in the Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS). His research spans statistical methodology development and applications across diverse fields including ecology, biomedicine, and environmental science. Dr. Drovandi's primary research interests focus on advancing Bayesian statistical methods, particularly in the areas of: Approximate Bayesian Computation (ABC) and likelihood-free inference Synthetic likelihood methods Sequential Monte Carlo algorithms Bayesian experimental design Statistical computing for complex models His recent work demonstrates a strong emphasis on addressing model misspecification in Bayesian inference, developing robust computational methods for intractable likelihoods, and applying advanced statistical techniques to solve real-world problems in ecology, biomedicine, and environmental science. Drovandi has made significant contributions to both the theoretical foundations and practical applications of modern Bayesian statistics. Dr. Drovandi has received research funding through multiple Australian Research Council grants and collaborates extensively with researchers across disciplines. His work has been published in top-tier statistical and interdisciplinary journals including the Journal of the American Statistical Association, Bayesian Analysis, and PLOS Computational Biology.

• Centromeres
• Genomics
• Epigenetics
• +۴ مورد دیگر

Nicolas Altemose is an Assistant Professor in the Department of Genetics at Stanford University School of Medicine, where he leads research on centromere structure and function critical for chromosome segregation during cell division. His lab pioneers computational genomics and single-molecule sequencing to decode highly repetitive centromeric DNA regions, investigating protein distributions, epigenetic modifications, and mechanisms linking centromere dysfunction to chromosomal abnormalities, infertility, and cancer. This work bridges molecular biology with advanced genomic technologies to address historically intractable genomic regions. Scientific Awards: Pew Biomedical Scholar (2024) Dr. Altemose directs the Altemose Lab (http://altemoselab.stanford.edu), focusing on developing novel methodologies to study repetitive DNA structures and their implications for human disease pathogenesis through interdisciplinary genomic approaches.