James C. Gee is a Professor of Radiologic Science in Radiology at the University of Pennsylvania's Perelman School of Medicine. He serves as Director of the Penn Image Computing and Science Laboratory and Co-Director of the Translational Biomedical Imaging Center , with affiliations in Bioengineering and Applied Mathematics graduate groups. His research focuses on biomedical image analysis, specialization in segmentation, registration, and morphometry applied to neurodegenerative diseases and multi-organ systems. Education : B.S. in Computer Science/Electrical Engineering (University of Washington, 1987), Ph.D. in Computer and Information Science (University of Pennsylvania, 1996) Research : Quantitative medical imaging methods, brain connectomics, neurodegeneration mapping, and translational imaging technologies Publications : 15+ recent works on AI-driven image analysis for Alzheimer's disease, cardiac amyloidosis, and radiomics applications Leadership : Directs MSE-DS Online Degree Program, co-chairs Radiology DCOAP Committee, and founded RISE (Radiology Initiative to Support Inclusive Excellence) His laboratory develops advanced computational tools like ITK-SNAP for biomedical imaging, with applications in both in vivo clinical imaging and ex vivo histology . The work spans cross-disciplinary collaborations in computer science, neuroscience, and clinical medicine.
Eddie C. Red is an Associate Professor of Mathematics and Computational Sciences at Morehouse College , where he currently serves as the Interim Dean of the Science, Technology, Engineering, and Mathematics (STEM) Division. He earned his B.S. from Morehouse College (class of 2000) , followed by his M.S. and Ph.D. from Florida Agricultural and Mechanical University . Dr. Red also completed post-doctoral education at Lawrence Berkeley National Laboratory . Interim Dean, STEM Division Former Chair, Mathematics and Computational Science Division Former Chair, Physics & Dual-Degree Engineering Department Dr. Red’s research interests bridge atomic physics, quantum mechanics, and computational modeling , with a focus on: Photoionization cross-sections Bound states in the continuum Velocity map imaging techniques Mathematical formulations for quantum operators His work has resulted in publications in Physical Review A, Communications Physics, and the Journal of Physics B , alongside numerous conference presentations. Dr. Red has led the NuMaSS (Nuclear, Materials, and Space Science) Summer Enrichment Program for K-12 students and directed the Research Experience with Diversification Laboratory , emphasizing student training and research. Scientific awards include: Principal Investigator for Department of Energy National Nuclear Security Administration awards Dr. Red has served on multiple faculty governance committees, including the Admissions Committee , Faculty Grievance Committee , and Faculty Research Committee .
Satish C. Boregowda is a Senior Lecturer at the School of Mechanical Engineering, Purdue University in West Lafayette, Indiana. His work focuses on thermodynamics-based analysis of human physiological systems, energy systems engineering, and renewable energy integration. He is affiliated with Purdue's Mechanical Engineering department and maintains an office in POTR 322A. Education & Professional Background : While specific educational details are not provided, his long-term research contributions since 1992 indicate advanced expertise in thermodynamics, biomedical engineering, and energy systems. His career spans over three decades with continuous publication activity. Research Interests : Dr. Boregowda’s core research combines thermodynamics with human physiology, developing metrics like the Objective Stress Index (OSI) to quantify stress responses. His work also addresses energy security through renewable integration, entropy analysis in biological systems, and thermal comfort modeling. He applies constructal theory, fractional calculus, and finite element methods to model human thermal regulation and environmental interactions. Publications Trends : His articles (1992–2025) show sustained focus on: 1) Thermodynamic modeling of human stress and thermal comfort, 2) Renewable energy grid integration strategies, and 3) Advanced computational methods for physiological systems. Recent works emphasize decarbonization pathways and energy policy implications. Grants & Advising : No specific grants or advisees are listed in the provided data. His research likely involves collaborations with aerospace and environmental engineering groups given his work on thermal systems in microgravity and HVAC applications. Labs & Teams : While no specific lab affiliations are mentioned, his research aligns with Purdue’s mechanical engineering initiatives in renewable energy, biomedical engineering, and thermal systems design.
Keisuke Ishihara is an Assistant Professor in the Department of Computational and Systems Biology at the University of Pittsburgh School of Medicine. His research focuses on engineering human brain and cardiac organoids using genetic, chemical, and computational approaches to uncover novel regulatory mechanisms and physical principles underlying tissue development. His lab is located at Biomedical Science Tower 3, with an office in room 10020A. Dr. Ishihara holds a PhD in Systems Biology from Harvard University. His work bridges synthetic biology, developmental biology, and biophysics to address fundamental questions in organogenesis and cellular morphogenesis. Recent research highlights include studies on BMP-mediated neural tube patterning in organoids and the biophysical dynamics of microtubule assemblies in large cells. Publications from his lab emphasize interdisciplinary approaches to understand cell size scaling, mitotic spindle dynamics, and self-organization in synthetic tissues. His team has contributed to advancements in organoid technology, uncovering dormant genetic programs and physical principles governing tissue architecture. Laboratory activities are centered at the University of Pittsburgh, collaborating with the School of Medicine's computational and systems biology initiatives. For more details, visit his lab website linked below.
Dr. John Shepherd is an Associate Professor in the School of Science at RMIT University, specializing in applied mathematics, numerical and computational mathematics, and their applications in engineering and environmental systems. His research focuses on analyzing nonlinear problems, particularly in bioreactor dynamics, fluid mechanics, and nuclear energy policy. He has contributed to studies on anaerobic digestion models, reactor stability, and the role of nuclear energy in climate change mitigation. Education: Doctorate in Applied Mathematics (not explicitly stated in text, inferred from title). His work bridges theoretical analysis and real-world applications, such as optimizing methane production in waste digesters and evaluating environmental policies for nuclear energy. He actively supervises research projects, including the analysis of anaerobic digester dynamics. Dr. Shepherd’s publications span interdisciplinary topics, emphasizing the intersection of mathematics, engineering, and environmental science. He engages with policy discussions on nuclear energy’s role in decarbonization, advocating for its integration into clean energy strategies. His research highlights the importance of multiscale analysis in understanding complex systems like bioreactors and fluid flows. Collaborations involve industry and international institutions, reflecting his commitment to practical solutions for sustainability challenges.
Prof. Vladimir Spokoiny is a leading figure in stochastic algorithms and nonparametric statistics at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) and Humboldt University of Berlin . His work bridges mathematical statistics with practical applications in finance, medicine, and machine learning. Born in 1959 in Moscow, USSR PhD from Lomonosov Moscow State University (1988) Habilitation from Humboldt University (1996) Head of WIAS research group since 2000 Professor at Humboldt University since 2002 Spokoiny's research focuses on adaptive nonparametric methods, high-dimensional data analysis, and statistical finance. His innovations in local homogeneity testing and propagation-separation methods have advanced volatility modeling, image analysis, and manifold learning. He employs Bayesian optimization frameworks and stochastic control techniques for financial instrument pricing. Recent scientific contributions include generalized bootstrap procedures for Bures-Wasserstein barycenters (2024), dimension-free Laplace approximation bounds (2023), and structure-adaptive manifold estimation (2022). His 19+ PhD students and editorial roles in top journals like The Annals of Statistics demonstrate sustained academic impact. International Statistical Institute member American Statistical Association fellow Institute of Mathematical Statistics member Bernoulli Society member
Dr. Sheena D'Arcy is an Associate Professor in the Department of Chemistry and Biochemistry at the University of Texas at Dallas (UT Dallas), affiliated with the School of Natural Sciences and Mathematics. Her research focuses on structural biology, protein dynamics, and the molecular mechanisms of gene transcription, particularly involving histone chaperones and nuclear transport proteins. She holds a PhD in Structural Biology from the University of Cambridge (2008) and a BS in Biochemistry and Biology from the University of Sydney (2003). Her work employs advanced techniques like hydrogen-deuterium exchange mass spectrometry (HDX-MS) and structural biology to investigate protein-RNA interactions, nucleosome assembly, and enzyme evolution. She leads the D'Arcy Lab, which explores topics such as TRAMP complex function, RanGTP signaling in histone transport, and conserved viral epitopes in coronaviruses. Dr. D'Arcy received a NIH ESI-MIRA grant (R35GM133751) to study nucleosome assembly mechanisms. Her research bridges molecular-level interactions with cellular processes, contributing to understanding epigenetic regulation and viral pathogenesis. She is currently not accepting undergraduate students but actively mentors graduate researchers in structural biology and biochemistry.
Juan Manuel Pérez Pardo is an Associate Professor in the Department of Mathematics at Universidad Carlos III de Madrid, where he has been a faculty member since 2019, progressing from Assistant Professor to his current position as Associate Professor since December 2022. His academic journey includes postdoctoral research at prestigious institutions including the Istituto Nazionale di Fisica Nucleare in Naples, Italy, and the Instituto de Ciencias Matemáticas in Madrid. Dr. Pérez Pardo earned his PhD in Mathematics from Universidad Carlos III de Madrid in 2013, following a Master's degree in Mathematical Engineering from the same institution and a Master's degree in Theoretical Physics from Universidad Complutense de Madrid. His undergraduate studies were in Physics at Universidad Complutense de Madrid. His research focuses on the intersection of functional analysis and quantum physics, particularly in three main areas: Functional Analysis : Applying functional analytical tools to quantum systems, with emphasis on quadratic forms associated with differential operators and evolution equations in Hilbert spaces. Quantum Systems with Boundary : Studying quantum dynamics when boundaries are present, combining operator theory, spectral theory, and differential geometry. Quantum Control on Infinite Dimensional Systems : Developing mathematical theory for controlling quantum systems that are infinite dimensional in nature, relevant to quantum computation technologies. His publication record shows a strong focus on quantum control theory, self-adjoint extensions of differential operators, and the mathematical foundations of quantum mechanics. Recent work (2022-2025) has concentrated on stability of non-autonomous Schrödinger equations, quantum controllability, and relativistic quantum systems. Dr. Pérez Pardo has received several prestigious awards including the Juan de la Cierva Fellowship and the QUITEMAD+ Postdoctoral Fellowship. His work on boundary dynamics driven entanglement was highlighted in Europhysics News and tagged as IOPselect by the Institute of Physics. He actively mentors students at all levels, currently supervising PhD candidate Ángel Aitor Balmaseda Martín on "Quantum Control at the Boundary." He has also supervised numerous Master's and Bachelor's students on topics ranging from numerical solutions of quantum control problems to modeling Josephson junctions. Dr. Pérez Pardo is a key member of the Q-Math Research Group at UC3M and has organized multiple international workshops on Information Geometry, Quantum Mechanics, and Applications. He also serves on the editorial board of the International Journal of Geometric Methods in Modern Physics.
Ashutosh Agrawal is a Professor at Texas A&M University whose research bridges biophysics and materials science. He leads the "Life at the Interface" research group, investigating engineering principles governing two-dimensional structures through the interplay of mechanics, geometry, and electrostatics. His work spans lipid-protein interactions in neurons to biomimetic topological materials design. His academic credentials include: Ph.D. in Civil and Environmental Engineering from University of California, Berkeley (2009) Master of Science in Civil and Environmental Engineering from Rice University (2003) Bachelor of Technology in Civil Engineering from Indian Institute of Technology Bombay (2001) Dr. Agrawal's research focuses on the mechanical behavior of biological interfaces with particular emphasis on: Electromechanics of Neuronal Signaling Interfacial Mechanics of Cellular Organelles Mechanics of Cellular Transport Electromechanics of Topologically Complex Plates and Shells His methodology integrates mathematical modeling, atomistic simulations, Monte Carlo techniques, and finite element analysis to explore cellular membrane functionality and develop novel biomaterials. Analysis of his 2015-2023 publications reveals consistent exploration of electromechanical phenomena in cellular structures, with recurring themes in lipid bilayer transitions, organelle dynamics, and topological material design. These works demonstrate interdisciplinary convergence between fundamental biophysics and engineering applications. His recognition includes: Teaching Excellence Award from University of Houston (2015) As an educator, he develops innovative teaching methodologies promoting hands-on learning of engineering principles across disciplines. While specific advisees aren't listed, his research group actively pursues collaborative projects in cellular biophysics and materials engineering. The "Life at the Interface" laboratory serves as an interdisciplinary hub investigating mechanical principles of cellular structures through computational and theoretical approaches.
Professor Dan Balint is the Head of the Mechanics of Materials Division in the Department of Mechanical Engineering at Imperial College London. He holds a Ph.D. in Engineering Sciences from Harvard University (2003), an S.M. in Applied Mathematics from Harvard (2001), and a B.S. in Engineering Mechanics from Michigan State University (1998). Prior to joining Imperial in 2006, he was a Research Associate at the Cambridge Centre for Micromechanics. His research spans theoretical and computational solid mechanics, with focus areas including: Micromechanics of crystalline materials (metals/ceramics) Dislocation-defect interactions and failure mechanisms Discrete dislocation plasticity methods Nuclear cladding materials and zirconium hydrides Thin film failure and metal forming processes Fracture mechanics and material size effects Recent publications (2022-2025) predominantly explore dislocation dynamics, zirconium alloy behavior under nuclear conditions, computational modeling of microstructural stresses, and machine learning applications in materials science. Common themes include thermomechanical degradation, crack initiation mechanisms, and multi-scale modeling approaches. Professor Balint serves as Associate Editor of the European Journal of Mechanics - A/Solids and consults for industrial partners including Rolls Royce, BP, and the US Air Force.
Heikki Handroos is a Full Professor of Mechanical Engineering at LUT University, leading the Laboratory of Intelligent Machines since 1993. He holds a DSc (Technology) from Tampere University of Technology and has served as Vice-Dean of the Faculty of Technology (2007-2009) and currently chairs the Collegiate Body of LUT University. His research focuses on mechatronics, robotics, control systems, and fluid power, with over 300 publications and 2,400+ citations. He has supervised 34 doctoral theses and 150+ MSc projects, managed R&D projects exceeding €20M, and co-founded four tech startups. His work spans industrial collaborations, digital twin applications, and innovative robotics for nuclear energy (e.g., DEMO reactor maintenance systems). He has held visiting professorships in the U.S., Japan, and Russia, and actively contributes to academic editorial roles and professional societies like ASME and IEEE.
Dr. Anna Baldycheva is a Senior Lecturer in Electronic Engineering at the University of Exeter, within the College of Engineering, Mathematics and Physical Sciences. She leads the interdisciplinary STEMM Laboratory, focusing on applied R&D in smart materials, photonics, AI, and IoT. With prior research experience at MIT, Trinity College Dublin, and Tyndall National Institute, she has established herself as an internationally recognized innovator and entrepreneur in emerging technologies. PhD in Electronic and Electrical Engineering, Trinity College Dublin (2008–2012) BSc (Hons) in Physics, St. Petersburg State University (2003–2008) Postgraduate Certificate in Academic Practice, University of Exeter (2016–2017) Postgraduate Certificate in Technology Management, Smurfit Business School (2009–2010) Her research spans Nano-Engineering, Opto-Electronics, Photonics, AI, and IoT , with a strong emphasis on real-world applications. She pioneers work in fluid opto-electronics , graphene nanocoatings , and AI-driven emotion recognition and early cancer detection . Her lab develops smart composite materials for flexible electronics, e-textiles, and structural applications, integrating machine learning into healthcare, education, and communications systems. The recent publications highlight a strong trend toward applied interdisciplinary innovation , combining materials science with AI and photonics for healthcare diagnostics, energy-efficient computing, and educational technology. Her work frequently bridges fundamental physics with commercialization potential, as seen in spin-out technologies like GSurf and the Electronic-Nose for lung cancer detection. Fellow, Royal Microscopical Society (RMS) Fellow, Higher Education Academy (FHEA) Expert, Future and Emerging Technologies, European Commission Featured in Forbes and Forbes Tech Council Editor-in-Chief, InSTEMM Journal Associate Editor, Nature Scientific Reports and Discover Nano Trustee, Royal Microscopical Society Founder, STEMM Global Scientific Society Founder, It’s Her! Women in STEMM Initiative Dr. Baldycheva actively supervises PhD students and has secured industrial collaborations with organizations such as Qinetiq and Lumentum. She leads multiple outreach initiatives, including STEMM Junior for underprivileged children, and serves on the committee for the Jocelyn Bell Brunel PhD Scholarship. She has raised significant research funding through national and international grants, though specific grant names are not listed. She leads the STEMM Laboratory , a multidisciplinary research group with divisions in Smart Composite Materials, Machine Learning & AI, and Opto-Electronics & Photonics. The lab emphasizes industry collaboration and technology transfer, having produced a university spin-out (GSurf) and multiple media-highlighted innovations.
David J. Brenner serves as Higgins Professor of Radiation Biophysics in Radiation Oncology and Environmental Health Sciences at Columbia University Medical Center. He directs both the century-old Center for Radiological Research and the Radiological Research Accelerator Facility (RARAF), leading interdisciplinary teams focused on radiation applications in medicine and safety. BA in Physics from Oxford University (1974) MSc in Radiation Physics from University of London (1976) MA in Physics Philosophy from Oxford University (1979) PhD in Physics from University of Surrey (1980) His research spans dual aspects of radiation: therapeutic applications in cancer treatment and risk assessment across diverse scenarios. Key initiatives include advancing carbon-ion therapy for pancreatic cancer, developing safe far-UVC light for pathogen elimination, and investigating low-dose radiation risks from medical imaging to nuclear terrorism. His team leverages RARAF's unique capabilities for mechanistic studies of radiation effects. Publications reveal dominant themes in radiation biophysics, with significant contributions to biodosimetry (RABiT platform), UV disinfection technology, and cancer risk modeling. Recent work emphasizes translational applications including medical countermeasures for radiation exposure and precision radiation oncology techniques. National Academy of Sciences Nuclear and Radiation Studies Board member National Council on Radiation Protection and Measurements member Radiation Research Society Failla Gold Medal recipient (2011) Oxford University Weldon Prize for mathematical biology (2015) Robert D. Moseley Award for Radiation Protection in Medicine Brenner leads multiple NIH-funded projects including biodosimetry development and UV disinfection research. His mentorship extends through directing Columbia's Radiological Research Accelerator Facility and training programs in radiological sciences. Current lab efforts focus on carbon-ion therapy mechanisms and 222-nm UV applications against drug-resistant pathogens, with active collaborations across oncology, microbiology, and physics disciplines.
Amir Bahadori serves as Professor and Nuclear Engineering Program Director in the Department of Mechanical and Nuclear Engineering at Kansas State University's Carl R. Ice College of Engineering, holding the Hal and Mary Siegele Professorship in Engineering. He directs the Radiological Engineering Analysis Laboratory (REAL) and established the Institute for Radiation Health Studies (IRHS) in 2024, focusing on radiation protection, space radiation environments, and radiation health effects. His educational background includes: Ph.D. in Biomedical Engineering, University of Florida (2012) M.S. in Nuclear Engineering Sciences, University of Florida (2010) B.S. in Mechanical Engineering and Mathematics, Kansas State University (2008) Bahadori's research spans radiation transport modeling, dosimetry, and risk assessment with applications in space exploration, medical physics, and radiation epidemiology. He develops computational frameworks for radiation exposure scenarios and biological response prediction, emphasizing space radiation protection for Artemis missions and chronic exposure studies through the Million Person Study collaboration. Analysis of his recent publications reveals dominant themes in space radiation measurement (Artemis missions), radiation epidemiology (Million Person Study innovations), and advanced detection systems (miniaturized neutron spectrometers). His work increasingly integrates big data approaches for radiation risk assessment and electrostatic shielding concepts for deep-space exploration. His scientific recognition includes: NASA Graduate Student Research Fellowship (2009) Certified Health Physicist designation Big 12 faculty fellowship (2022-2023) NCRP council election (2024) Two USPTO patents Bahadori secures substantial research funding from NASA for space radiation instrumentation, Department of Energy projects via the Kansas City National Security Campus, and collaborative epidemiological studies. He mentors nuclear engineering graduate students while leading interdisciplinary teams developing radiation protection solutions for aerospace and medical applications. His laboratory infrastructure includes the REAL with Beocat high-performance computing resources, radiation detectors, and a 3D printer, plus the IRHS with a Precision X-ray XRad320 irradiator and radon chamber. These facilities support collaborations across K-State colleges and external organizations for radiation health effect studies.
Dr Rita Borgo is a Professor in Data Visualization and Head of the Human Centred Computing Group at King's College London's Department of Informatics. She holds a leadership role within the Faculty of Natural, Mathematical & Engineering Sciences and is affiliated with the Centre for Urban Science and Progress (CUSP) London. Her research focuses on interdisciplinary visualization challenges, including human-computer interaction, AI trust calibration, and epidemiological modeling. Education details are not explicitly stated in the provided text. Her work spans over 58 publications, emphasizing visualization techniques for large datasets, trust in AI systems, and urban science applications. Key projects include RAMPVIS (visual analytics for pandemic response) and Trusted Autonomous Systems Hub (AI ethics and human-machine partnerships). Research interests include data visualization, human factors, generative AI, and policy simulation. Recent articles explore trust calibration in AI, time-series visualization, and ethical clinical decision support systems. She has led grants totaling £multi-million, including EPSRC-funded initiatives. Collaborations with organizations like ContactEngine Limited highlight her industry engagement. Labs/Teams: Leads the Human Centred Computing Group and contributes to CUSP's urban data initiatives. Supervised student work includes a notable BSc thesis by Munkhtulga Battogtokh. Current projects address visualization in nuclear policy, social media mental health correlations, and trustworthy autonomous systems.
