Find Academic Supervisors

• Microelectronics
• Nanotechnology
• VLSI Design
• +7 more

Sumeet Gupta is the Elmore Associate Professor of Electrical and Computer Engineering at Purdue University's Elmore Family School of Electrical and Computer Engineering. His research focuses on device-circuit co-design in emerging nanotechnologies, spintronics, and low-power VLSI design. He leads interdisciplinary efforts in ferroelectric devices, neuromorphic computing, and energy-efficient hardware for AI applications. Education: B.Tech from IIT Delhi (2006), M.S. and Ph.D. from Purdue University (2008, 2012). Research Interests: Ferroelectric and spintronic materials for next-gen computing Non-Boolean computing architectures Compute-in-memory accelerators Low-power and variation-tolerant VLSI design Domain wall dynamics in thin films Neuromorphic engineering Key Contributions: Over 50+ peer-reviewed publications on ferroelectric transistors, crossbar array optimizations, and fault-tolerant neural network hardware. His work bridges material science, device physics, and circuit design to enable energy-efficient computing systems.

• Quantum Information
• Quantum Computation
• Quantum Optics
• +2 more

Professor Ignacio Cirac is Director at the Max Planck Institute for Quantum Optics and leads the Theory Division. His pioneering work in quantum information theory has fundamentally advanced quantum computing and quantum simulation frameworks. Research breakthroughs include: Developing theoretical foundations for quantum computers and quantum networks Creating new algorithms for quantum communication Designing quantum simulation methods for many-body systems Establishing theoretical tools for quantum entanglement characterization His group develops concepts for quantum gates and algorithms implemented by experimental physicists worldwide. Current investigations focus on quantum simulation of solid-state systems using ultracold atoms in optical lattices, advancing understanding of magnetism and superconductivity. Major Awards: Wolf Prize in Physics (2013) Niels Bohr Medal (2013) Prince of Asturias Prize (2006) Benjamin Franklin Medal (2009) Quantum Electronics Prize (2005)

• Neuroscience
• Circadian Neuroscience
• Sensory Neuroscience

Anna Biller serves as a Visiting Scientist at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, affiliated with the Sensory and Circadian Neuroscience research group led by Dr. Spitschan. Her work is conducted within the institute's framework at Max-Planck-Ring 10, 72076 Tübingen, with office location 1.01b and contactable via +49 7071 601 269 or +49 7071 601 1678. Her research centers on the neural mechanisms governing circadian rhythms and sensory processing, specifically exploring how biological timing systems interact with visual and perceptual pathways. This work spans Circadian Neuroscience and Sensory Neuroscience, with implications for sleep disorders, light therapy applications, and environmental adaptation studies. The interdisciplinary approach combines neuroimaging, behavioral analysis, and computational modeling to decode temporal-sensory integration in the brain. The Sensory and Circadian Neuroscience group under Dr. Spitschan investigates 24-hour biological cycles through experimental and theoretical frameworks. Dr. Biller contributes to projects examining photic entrainment, neural plasticity across circadian phases, and sensory processing variations during sleep-wake transitions, utilizing the institute's advanced imaging facilities and collaborative networks.

Christoph RinneView profile

Researcher

• Prehistoric Archaeology
• Neolithic Europe
• Megalithic Monuments
• +16 more

Christoph Rinne is a Research Associate in Archaeoinformatics at the Institute of Pre- and Protohistoric Archaeology, Christian-Albrechts-Universität zu Kiel. He has been a key figure in computational archaeology and digital documentation since 2008, contributing to major projects such as SFB 1266 and the DFG Priority Programme on Early Monumentality. His work integrates field archaeology, geophysics, and advanced data modeling. His research focuses on Neolithic and Bronze Age Europe, particularly the Funnel Beaker and Wartberg cultures. He specializes in megalithic monuments, settlement landscapes, and digital methodologies including GIS, CAD, and database development. His field projects span Germany, Mallorca, and Portugal, often involving student training in applied computational archaeology. The 15 most recent publications reveal a strong trend toward interdisciplinary research, combining traditional excavation data with radiocarbon modeling, ancient DNA, paleoenvironmental analysis, and digital reconstruction. His work increasingly addresses socio-environmental transformations, connectivity, and health in prehistoric societies, reflecting a broadening scope from material culture to systemic societal change. Rinne is actively involved in academic training, having developed tutorials on AutoCAD, QGIS, Zotero, and SQLite for archaeologists. He leads DFG-funded subprojects and collaborates with international teams on cutting-edge bioarchaeological research. His leadership roles include subproject leadership in SFB 1266 and the Haldensleben-Hundisburg research initiative. He has secured continuous research funding and mentors students through field internships and collaborative publications. Rinne leads or co-leads several research teams, including those at Niedertiefenbach, Es Rossells (Mallorca), and the Haldensleben-Hundisburg region. These teams combine field archaeologists, geophysicists, and digital specialists to investigate long-term landscape use and societal change.

Christopher MasonView profile

Professor

• Computational Biology
• Genomics
• Space Biology
• +7 more

Christopher Mason is a Professor at Weill Cornell Medicine's Graduate School of Medical Sciences. His research focuses on computational and experimental genomics, particularly in understanding the genetic elements that orchestrate human brain development and disease mechanisms. Affiliated with programs in Physiology, Biophysics & Systems Biology and Computational Biology . Develops molecular maps of genetic, epigenetic, and translational activity to create a 'molecular recipe' for brain development. Investigates space biology through initiatives like the 10-phase, 500-year plan to reengineer biology for extraterrestrial habitation. His recent work spans wastewater sequencing for pandemic surveillance, spaceflight-induced biological changes, and multi-omic analyses of diseases like glioblastoma and lymphoma. Publications emphasize bioinformatics , single-cell analysis , and space omics .

• Convex Analysis
• Variational Calculus
• Quantum Information Theory
• +3 more

Stephan Weis is a Research Fellow in the ROBOPROX project at the Department of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague. He collaborates with prominent researchers including Didier Henrion, Milan Korda, and Martin Kružík in the fields of convex analysis and variational calculus. Dr. Weis completed his academic training with a Doctoral Thesis titled Exponential Families with Incompatible Statistics and Their Entropy Distance from Erlangen, Germany in 2010, preceded by a Diploma Thesis Invariants for the Ideal Boundary of a Tree and a Master Thesis Dynamics on Graphs both from 2004. His research spans multiple interconnected domains with a primary focus on the mathematical foundations of quantum information theory. He has made significant contributions to understanding convex structures in quantum state spaces, numerical ranges of operators, and maximum-entropy principles. His work demonstrates deep connections between pure mathematics (particularly convex geometry and operator theory) and quantum information applications. Analysis of his publication timeline reveals a consistent research trajectory focused on the geometry of quantum states, with recent work (2023-2025) extending into matrix systems, face lattices of density matrices, and open mappings in operator algebras. His publications appear in high-impact journals including Advances in Operator Theory, Journal of Convex Analysis, SIAM Journal on Applied Algebra and Geometry, and Journal of Mathematical Physics. Dr. Weis has presented his research at numerous international conferences including IWOTA (International Workshop on Operator Theory and Applications), STOC (ACM Symposium on Theory of Computing), and specialized workshops on numerical ranges and quantum information theory across Europe and beyond. His collaborative work spans multiple institutions and research groups, with recent projects focusing on quantum coin flipping protocols, convex analysis applications to quantum states, and geometric approaches to quantum information problems. The interdisciplinary nature of his research bridges mathematics, physics, and theoretical computer science.

Tobias RiedView profile

Assistant Professor

• Partial differential equations
• Calculus of variations and optimal control
• Statistical mechanics
• +4 more

Tobias Ried is a tenure-track Assistant Professor in the School of Mathematics at Georgia Institute of Technology, where he conducts research at the intersection of partial differential equations, mathematical physics, and statistical mechanics. Prior to joining Georgia Tech, he served as a group leader in Felix Otto's research group at the Max Planck Institute for Mathematics in the Sciences in Leipzig, Germany. His work is supported by NSF grant DMS-2453121 and focuses on fundamental problems in kinetic theory, optimal transport, and micromagnetics. Ried's research interests span a wide range of mathematical topics with strong connections to physical applications. His primary focus lies in partial differential equations and their applications to problems in statistical mechanics and mathematical physics. He has made significant contributions to the theory of kinetic equations including the Boltzmann and Kac models, optimal transport theory with applications to economics and machine learning, and micromagnetics with relevance to materials science. His work often combines analytical techniques from calculus of variations with insights from probability theory and functional analysis. Analysis of Ried's publication record reveals a strong trend toward interdisciplinary mathematical research that bridges theoretical mathematics with concrete physical applications. His early work focused on kinetic theory and nonlinear wave phenomena, particularly examining smoothing properties of solutions to Boltzmann-type equations. More recently, his research has expanded into optimal transport theory, where he has investigated regularity properties of transport maps and Wasserstein barycenters, and micromagnetics, where he has established precise scaling laws for domain branching phenomena. This evolution demonstrates a consistent focus on variational methods applied to complex physical systems. Ried has established productive collaborations with prominent researchers in mathematical physics including Dirk Hundertmark, Felix Otto, and Michael Loss. His work has appeared in top-tier mathematics journals such as Communications in Mathematical Physics, Inventiones Mathematicae, and Archive for Rational Mechanics and Analysis. While specific awards are not documented in the available information, his research has generated significant scholarly impact with his publications cited over 60 times according to zbMATH Open. Ried maintains an active research program supported by NSF funding, with recent work exploring singular stochastic partial differential equations, variational problems related to spectral inequalities, and the mathematical foundations of micromagnetic phenomena. His research group at Georgia Tech likely focuses on advancing the theoretical understanding of complex systems through rigorous mathematical analysis, though specific details about students and postdoctoral researchers are not provided in the available documentation.

David QuigleyView profile

Assistant Professor

• Prostate Cancer Genomics
• Epigenomics
• Cancer Therapy Resistance
• +7 more

David Quigley is a faculty researcher at the University of California San Francisco (UCSF), where he leads research on prostate cancer genomics and therapy resistance. His work focuses on understanding how genomic and epigenomic alterations in tumors influence patient outcomes and treatment response in advanced prostate cancer. Education: BA in Computer Science, Carleton College, 1998 MA in Biomedical Informatics, Columbia University, 2006 PhD in Genetics, University of Oslo, 2014 Dr. Quigley's research lies at the intersection of cancer biology, genomics, and computational methods. He uses large-scale genome sequencing and machine learning to identify non-coding structural variants, epigenetic changes, and transcriptional drivers associated with resistance to targeted therapies in metastatic prostate cancer. His recent work includes mapping accessible chromatin, studying AR signaling resistance, and developing predictive models for clinical outcomes. His recent publications (2024–2025) span high-impact journals such as Nature Genetics , Nature Cell Biology , Cancer Discovery , and Journal of Clinical Oncology , reflecting a strong focus on epigenomics, therapy resistance, spatial profiling, and health disparities in prostate cancer. Collaborative in nature, his research involves multi-institutional teams and integrates experimental and computational approaches. Scientific Awards: National Merit Scholar B.A. Magna Cum Laude M.A. with honors AACR Scholar in Training Award Prostate Cancer Foundation Young Investigator Award (2018) BRCA Foundation Young Investigator Award (2024) Robert Sutherland Award, PacRim Breast and Prostate Cancer Meeting (2024) Outstanding Faculty Mentorship Award, UCSF Students of the Graduate Division Dr. Quigley is the Principal Investigator on a DOD-funded project (2024–2027) aimed at discovering transcriptional drivers in therapy-resistant prostate cancer and a co-PI on a Prostate Cancer Foundation grant using machine learning to advance drug development. He is actively involved in mentoring and collaborative science, contributing to major research consortia such as the SU2C/PCF West Coast Prostate Cancer Dream Team. His lab integrates clinical data, tumor genomics, and advanced computational models to improve risk stratification and therapeutic strategies for prostate cancer patients. Labs and Research Teams: His research is conducted in close collaboration with the laboratory of Dr. Felix Feng at UCSF, a leading group in prostate cancer genomics. He is part of the SU2C/PCF West Coast Dream Team and contributes to the Benioff Initiative for Prostate Cancer Research.

• Partial Differential Equations
• Interface Evolution Problems
• Fluid Mechanics
• +5 more

Sebastian Hensel is a Hausdorff Postdoc at the Hausdorff Center for Mathematics , University of Bonn, focusing on partial differential equations and interface evolution problems. He earned his PhD under Prof. Julian Fischer at the Institute of Science and Technology Austria (IST Austria). Education: PhD, Master's, and Bachelor's in Mathematics from IST Austria, Humboldt-Universität zu Berlin, and Freie Universität Berlin Research interests: Interface evolution (multiphase mean curvature flow, Mullins-Sekerka equations), fluid mechanics (Navier-Stokes systems with interfaces), stochastic homogenization, and stochastic PDEs Notable work: Weak-strong uniqueness principles, Allen-Cahn approximations, and convergence rates analysis His publications explore geometric flows, two-phase fluid dynamics, and stochastic homogenization, with methodological advances in energy approaches and interface stability. He has participated in numerous international conferences and workshops.

• Quantum Chromodynamics (QCD)
• Nuclear Theory
• Quark-Gluon Plasma
• +3 more

Rob Pisarski is a Distinguished Scientist in the Nuclear Theory group within the Physics Department at Brookhaven National Laboratory (BNL). His research focuses on Quantum Chromodynamics (QCD) under extreme temperature and density conditions, including the development of effective theories for the QCD critical temperature and the study of cold dense quark matter ('quarkyonic' matter). He holds a Ph.D. in Physics from Princeton University (1980), where his thesis on Nonlinear Sigma Models of Symmetric Spaces was supervised by Nobel laureate David Gross, and a B.S. in Physics ( summa cum laude ) from Yale University (1975), where he received the Wohlenberg Prize in Physics. His research explores theoretical aspects of QCD phase transitions, quark-gluon plasma dynamics, and emergent phenomena in dense nuclear matter. Key areas include chiral symmetry restoration, moat regimes in QCD, shear/bulk viscosity in quark matter, and quantum algorithms for simulating gauge theories. Pisarski's recent articles (2023-2025) predominantly address QCD thermodynamics, quantum computing applications in field theory, and neutron star physics. Trends include matrix models for viscosity calculations, variational quantum eigensolvers for the Schwinger model, anomalous meson-glueball interactions, and quarkyonic matter implications for astrophysics. Awards and recognitions include: Senior U.S. Scientist Award, Alexander von Humboldt Foundation (2003) Fellow, American Physical Society (2000) Wohlenberg Prize in Physics, Berkeley College (Yale) Sabbatical at Niels Bohr Institute (2003-2004) He currently leads research at BNL's Nuclear Theory group and has held key roles including Deputy Director for Theory at the RIKEN/BNL Research Center (1999-2000). No explicit grant or advising details are mentioned in the source text. Pisarski collaborates extensively within BNL's Physics Department and maintains editorial responsibilities as an Associate Editor for Physical Review D since 1993. His work interfaces with experimental programs at RHIC and theoretical initiatives in high-density QCD.

Mathias TrabsView profile

Professor

• Nonparametric Statistics
• High-dimensional Statistics
• Statistics for Stochastic Processes
• +3 more

Professor Mathias Trabs is a faculty member at the Karlsruhe Institute of Technology (KIT), where he has been serving as a Professor since 2021. He is affiliated with the Department of Mathematics, specifically within the Institute of Stochastics. Previously, he held positions as Heisenberg professor at Universität Hamburg (2021) and Assistant professor at Universität Hamburg (2016-2021). His research spans several key areas in modern statistics and probability theory. Professor Trabs specializes in Nonparametric and high-dimensional Statistics, Statistics for stochastic processes, Statistical inverse problems, Statistical Learning, and Stochastic (partial) differential equations. His work bridges theoretical statistics with practical applications in physics, machine learning, and high-energy experiments. Analysis of his recent publications reveals a strong focus on the intersection of statistical theory and machine learning, particularly in generative models, neural networks, and high-dimensional data analysis. His work also demonstrates significant contributions to the mathematical foundations of stochastic processes and their applications in physical sciences. Professor Trabs has supervised numerous doctoral students including Lea Kunkel, Thea Engler, Jan Rabe, Sebastian Bieringer, Maximilian F. Steffen, and Florian Hildebrandt. His research has been supported by various projects including the Data Science in Hamburg - Helmholtz Graduate School for the Structure of Matter (DASHH), DFG project TR 1349/3-1 on high-dimensional statistics, and the LD-SODA research project. He is actively involved in academic leadership, serving as Deputy speaker of the KIT Center MathSEE (Mathematics in Sciences, Engineering, and Economics), and as a member of the steering boards of both the DMV-Fachgruppe Stochastik (Probability and Statistics Group of the German Mathematical Society) and the KIT Graduate School Computational and Data Science (KCDS).

Lin LinView profile

Professor

• Numerical Analysis
• Quantum Chemistry
• Quantum Algorithms
• +3 more

Lin Lin is a Professor in the Department of Mathematics at the University of California, Berkeley, and a Senior Faculty Scientist at Lawrence Berkeley National Laboratory. His research bridges computational quantum many-body problems, quantum algorithms, and numerical analysis, with affiliations to the Computational Research Division and CAMERA (Center for Advanced Mathematics for Energy Research Applications). Research Interests: Quantum chemistry, quantum algorithms, numerical analysis, and computational quantum physics. Scientific Awards: Sloan Research Fellowship (2015), NSF CAREER (2017), DOE Early Career (2017), SIAM CSE Early Career (2017), PECASE (2019), ACM Gordon Bell Team (2020), Simons Investigator (2021), and APS Outstanding Referee (2025). Contact: linlin@math.berkeley.edu | Office: 817 Evans Hall. Publications span quantum algorithms, Hamiltonian simulation, and computational methods in quantum chemistry. His seminars, like the Quantum Many-Body Seminar (Math 290) , engage students and researchers in cutting-edge topics such as quantum control, tensor networks, and open quantum systems. He leads the UC Berkeley / LBNL Applied Math Seminar and is an invited speaker at the 2026 International Congress of Mathematicians.

• Bifurcation Theory
• Chaos Theory
• Energy Harvesting
• +4 more

Michele Bonnin is an Associate Professor at the Politecnico di Torino , Department of Electronics and Telecommunications (DET). He contributes to teaching in Electromagnetism and Circuit Theory and Electrical Engineering courses across Computer Engineering , Electronic Engineering , and Physical Engineering programs. External Lecturer, University of Turin (2011-2017) Teaching activity at Turin Polytechnic University in Tashkent (2024) His research spans Nonlinear Dynamics , Energy Harvesting , and Stochastic Processes , focusing on: Phase Noise in Oscillators Memristor-Based Systems Ultra-Low-Voltage Circuit Reliability Stochastic Averaging Frameworks Recent work explores Nonlinear Multi-DOF Mechanisms for vibration energy harvesting and Edge of Chaos Theory in biological oscillator models. His 2025 articles highlight Memristor Amplification , SRAM Variability , and MEMS Optimization . Scientific Awards: BEST PAPER OF THE YEAR (2004), International Journal of Circuit Theory and Applications He serves as Associate Editor for Nonlinear Engineering and Computation , and contributes to doctoral programs in Sustainable Development and Climate Change (2021-2024). His research group LiNCS (Linear and Nonlinear Circuits & Systems) drives projects like RECOMMEND (2024-2027) and COMBlaser (2015-2017).

Arshak PetrosyanView profile

Professor

• Partial Differential Equations
• Free Boundary Problems
• Calculus of Variations
• +3 more

Dr. Arshak Petrosyan is a Professor of Mathematics and Associate Department Head at Purdue University. He holds a PhD from the Royal Institute of Technology (KTH), Sweden, under the supervision of Henrik Shahgholian. His research focuses on free boundary problems, partial differential equations (PDEs), and their applications in combustion and finance. Key areas include regularity theory for elliptic and parabolic PDEs, obstacle problems, and fractional Laplacian operators. Petrosyan has held positions at Purdue since 2003, progressing from Assistant to Professor, and mentored several PhD students and postdoctoral researchers. His educational background includes a Diploma from Yerevan State University (1997) and postdoctoral work at the University of Texas at Austin under Luis Caffarelli. Petrosyan’s work spans theoretical advancements in PDE analysis, with contributions to geometric and energetic criteria for free boundary regularity. He has co-authored influential papers on topics like the Signorini problem, fractional obstacle problems, and combustion models. Advising and collaborations include co-advising PhD students like Mariana Smit Vega Garcia and Wenhui Shi, as well as postdoctoral researcher Tung To. His research trends emphasize free boundary regularity, fractional calculus, and applications in applied mathematics. Despite no explicit mention of scientific awards, his extensive publication record reflects significant scholarly contributions.

• Earth remote sensing
• Global Navigation Satellite Systems (GNSS)
• Bistatic radar
• +7 more

James L. Garrison is a Professor in the Department of Aeronautics and Astronautics at Purdue University, with a courtesy appointment in Electrical and Computer Engineering. He is a University Faculty Scholar (2022-2027) and leads the Radio Navigation Lab. His research focuses on Earth remote sensing using GNSS and Signals of Opportunity (SoOp), including oceanography, soil moisture, snow/ice properties, and ionospheric studies. He contributed to NASA's CYGNSS mission, which uses GNSS reflections to monitor tropical storms. Education: PhD (University of Colorado Boulder, 1997), MS (Stanford University, 1990), BS (Rensselaer Polytechnic Institute, 1988). Research Interests: Development of novel instruments and algorithms for remote sensing, including bistatic radar, GNSS reflectometry, and ionospheric probing. Applications span agriculture, hydrology, and disaster monitoring. His work bridges space-based systems with terrestrial environmental science. Awards: National Academies Keck Futures Initiative (2012) Institute of Navigation Early Achievement Award (2002) NASA Exceptional Space Act Award (2000) Advising & Grants: Led the NASA Instrument Incubator Program (IIP) grant for airborne soil moisture sensing. Collaborates with JPL on snow/ice sensing and Scripps Institution on hurricane humidity profiling. Labs/Teams: Director of the Radio Navigation Lab, member of the Purdue Climate Change Research Center (PCCRC) executive committee, and faculty affiliate of the Ecological Sciences and Engineering (ESE) program.