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Alex MogilnerView profile

Professor

• Computational Biology
• Cell Biophysics
• Mathematical Biology
• +5 more

Alex Mogilner is a Professor of Mathematics and Biology at New York University's Courant Institute and Department of Biology. His research focuses on computational and mathematical modeling of cellular processes, including cell motility, mitosis, actin dynamics, and galvanotaxis. He collaborates closely with experimentalists to bridge theoretical and empirical cell biology. Education: Ph.D., Applied Mathematics, University of British Columbia, Canada (1995) Ph.D., Physics, USSR Academy of Sciences (1990) M.Eng., Engineering Physics, Ural Polytechnic Institute, USSR (1985) Research Interests: Mathematical modeling of molecular machines in cells Mitotic spindle dynamics and chromosome segregation Actin-myosin contraction mechanisms Galvanotaxis and electrotaxis in cell migration Cellular biophysics and mechanochemical processes Selected Publications Highlights: Developed models for mitotic spindle assembly and error correction Investigated mechanisms of cell polarization and turning Studied actin network contraction and cytoskeletal dynamics Explored galvanotactic cell migration in electric fields Labs/Teams: Leads a computational modeling lab at NYU, collaborating with experimental groups globally in cell biology, biophysics, and systems biology.

Jacquelien ScherpenView profile

Professor

• Automation & Control Systems
• Nonlinear Control Systems
• Smart Energy Systems
• +3 more

Jacquelien Scherpen is a Professor at the University of Groningen, currently serving as Rector Magnificus. She holds a position in the Engineering and Technology institute Groningen (ENTEG) within the Faculty of Science and Engineering. Her academic journey includes a PhD in Applied Mathematics from the University of Twente (1994) and post-doctoral roles at Delft University of Technology before joining Groningen in 2006. She has been a leader in systems and control research, with roles as Scientific Director of ENTEG (2013–2019) and Director of the Groningen Engineering Center (2016–2023). Her research focuses on model reduction, nonlinear control, smart energy systems, and distributed control applications in smart grids. Key achievements include the Automatica Best Paper Prize (2020), Knight of the Order of the Netherlands Lion (2019), and the Prince Friso Engineer of the Year Award (2023). She has held leadership roles in organizations like the European Control Association (EUCA) and is a Fellow of IEEE. Her professional activities include editorial roles in journals like the IEEE Transactions on Automatic Control and the International Journal of Robust and Nonlinear Control. She has organized major conferences, including the European Control Conference (ECC) 2021 and 2023. Her work bridges theoretical advancements with practical applications, emphasizing sustainability and engineering innovation.

Tony LindebergView profile

Professor

• Computer Vision
• Computational Neuroscience
• Medical Image Analysis
• +4 more

Tony Lindeberg is a Professor of Computer Science—Computational Vision at KTH Royal Institute of Technology, affiliated with the Division of Computational Science and Technology. He teaches the course Image Analysis and Computer Vision (DD2423). His research focuses on scale-space theory, early vision, and computational modeling of biological and auditory vision systems. Key contributions include theories on receptive fields, time-causal spatio-temporal models, and feature detection algorithms. Research interests span computational neuroscience, medical image analysis, and spatio-temporal recognition. Lindeberg has pioneered work on scale-invariant image features, affine transformations, and Galilean diagonalization for motion analysis. He is the author of the foundational book Scale-Space Theory in Computer Vision (1993). His work bridges computer vision and biological vision systems, with applications in gesture recognition, dynamic texture analysis, and neural networks. He leads the Vision Lab and Computational Brain Science Lab at KTH, emphasizing theoretical rigor and practical algorithms for visual perception tasks.

Paul FranzonView profile

Professor

• Quantum Information Science
• Machine Learning & AI Hardware
• 3D Integration
• +4 more

Paul Franzon is the Cirrus Logic Distinguished Professor and Associate Department Head for Graduate Affairs at the Department of Electrical and Computer Engineering, North Carolina State University. He holds a PhD and Bachelor's in Electrical Engineering and a Bachelor's in Physics/Mathematics from the University of Adelaide, Australia. His research focuses on quantum information science, machine learning-driven hardware design, 3D integration, and high-speed systems. Education: PhD in Electrical Engineering, University of Adelaide (1988) Bachelor's in Electrical Engineering, University of Adelaide (1984) Bachelor's in Physics and Mathematics, University of Adelaide (1982) Research Interests: Quantum computing and algorithm optimization AI-driven design automation for 3D integrated circuits High-speed communication systems Hardware security and FPGA acceleration Awards & Honors: IEEE Fellow (2006) Alcoa Foundation Distinguished Engineering Research Award (2005) NC State Alumni Distinguished Undergraduate Professor Award (2003) NSW Australia Expatriate Scientist Award (2003) Advising & Grants: Advised PhD student Priyank Kashyap (2023 graduate) Recipient of NSF Young Investigators Award (1993) Labs & Collaborations: Center for Advanced Electronics Through Machine Learning (CAEML) IEEE EPS Society (Associate Editor)

• Control Theory
• Applied Mathematics
• Computational Mechanics
• +7 more

Goong Chen is a Professor at Texas A&M University (TAMU) within the College of Arts & Sciences. His research focuses on Control Theory, Applied Mathematics, and interdisciplinary applications in computational mechanics, fluid dynamics, and quantum systems. He holds a Ph.D. from the University of Wisconsin (1977) and a B.S. from National Tsing-Hua University (1972). His research interests span computational biomechanics, forensic modeling, nanofluidics, and mathematical physics. Recent work includes modal analysis of animal motion, crash mechanics of aircraft, and forensic reconstruction of disasters. He has contributed to theoretical advancements in PDEs, nonlinear dynamics, and quantum computing. Chen’s articles address cutting-edge topics like thermoelastic plates, Volterra equations, and DFIM systems. He has pioneered numerical methods for complex systems using OpenFOAM and finite element techniques. His computational models have been applied to real-world scenarios such as submarine implosions and chemical warfare forensics. No academic awards are explicitly listed, but his extensive publication record reflects significant contributions to applied mathematics and engineering. He leads research teams focused on interdisciplinary challenges in computational science and engineering.

• Statistical Signal Processing
• Pattern Recognition
• Machine Learning
• +5 more

Ulisses Braga-Neto is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, part of the College of Engineering. He holds a Ph.D. from The Johns Hopkins University (2002), with earlier degrees including an M.S. from the Federal University of Pernambuco (1992). His research focuses on statistical signal processing, pattern recognition, and machine learning, with applications in bioinformatics, materials informatics, and environmental modeling. He leads the TAMIDS Scientific Machine Learning Lab and has authored over 100 publications. Key research areas include physics-informed neural networks for environmental and engineering problems, error estimation in classification systems, and gene regulatory network inference. His recent work emphasizes machine learning applications in agriculture (e.g., cotton detection in corn fields using UAS), CO2 sequestration modeling, and wildfire prediction. He has contributed to foundational texts like Error Estimation for Pattern Recognition (Wiley-IEEE, 2015). Prof. Braga-Neto's interdisciplinary approach bridges computer science, engineering, and biology. His lab develops algorithms for data-poor environments, with applications in genomics, proteomics, and metagenomics. He advises graduate students through Texas A&M's ECE program, emphasizing rigorous statistical methods alongside machine learning innovation.

Linda KatehiView profile

Professor

• Microwave and Millimeter-Wave Circuits
• MEMS Devices
• Terahertz Applications
• +5 more

Linda Katehi is a Professor of Electrical & Computer Engineering and Materials Science & Engineering at Texas A&M University, holding the O'Donnell Foundation Chair II. She is a Member of the National Academy of Engineering and American Academy of Arts and Sciences. Her research focuses on advanced electromagnetic systems, MEMS devices, and embedded intelligent sensors. Katehi earned her Ph.D. in Electrical Engineering from UCLA (1984), with prior degrees from UCLA and the National Technical University of Athens. Education: Ph.D., Electrical Engineering, UCLA (1984) M.S., Electrical Engineering, UCLA (1981) B.S., Electrical and Mechanical Engineering, National Technical University of Athens (1977) Research Interests: Katehi pioneers innovations in microwave circuits, MEMS-based reconfigurable systems, terahertz technology, and neuromorphic sensors. Her work emphasizes integrating artificial intelligence into hardware for adaptive sensing platforms. Recent projects include flexible electronics, time-domain system analysis, and sustainability in urban infrastructure. Awards & Recognition: Ramo Simon Founder’s Award (2015) Charter Fellow, National Academy of Inventors (2013) Leading Women in STEM Award (2012) Rudy E. Henning Mentoring Award (IEEE, 2011) Lab & Teams: Directs the Intelligent Electromagnetic Sensors Lab (IEMSL), advancing embodied intelligence in electronics. Her team develops AI-embedded sensors and reconfigurable systems for applications in healthcare, communications, and environmental monitoring. Collaborates across disciplines to address global sustainability and equity challenges.

Roberto BertolussoView profile

Senior Lecturer

• Systems Biology
• Cancer Research
• Computational Biology
• +3 more

Roberto Bertolusso is a Senior Pfeiffer Lecturer in the Department of Statistics at Rice University. He has held this position since 2013, focusing on teaching probability, statistics, and data science courses. His research integrates computational and systems biology approaches to study cancer mechanisms. Bertolusso earned his Ph.D. and M.S. in Statistics from Rice University and holds a graduate degree in Industrial Engineering from Universidad de Buenos Aires. His academic background includes significant contributions to cancer biostatistics and systems biology, highlighted by his participation in the AACR Methods in Cancer Biostatistics Workshop (2015) and a CPRIT-funded training program (2013–14). His publications span epidemiological modeling, orthopedic outcomes, and computational cancer research, reflecting interdisciplinary expertise. Education: Ph.D. & M.A. in Statistics, Rice University Graduate Level in Industrial Engineering, Universidad de Buenos Aires Teaching Focus: Probability theory, regression analysis, SAS programming, and data science methodologies. Research interests emphasize systems biology applications in cancer, stochastic modeling of biological systems, and computational methods for medical data analysis. His work bridges statistical theory with clinical and biomedical challenges, as seen in studies on viral infection dynamics and tumor growth modeling. Recent publications reflect both his cancer research and collaborative work in orthopedic surgery outcomes, showcasing a commitment to interdisciplinary problem-solving. Awards include recognition for methodological contributions to cancer clinical trial design and biostatistical training initiatives.

Sharon LubkinView profile

Professor

• Biological Modeling
• Continuum Mechanics of Tissues
• Morphogenesis
• +4 more

Sharon Lubkin is a Professor in the Department of Mathematics at North Carolina State University (NCSU). Her research focuses on modeling biological systems, continuum mechanics of tissues, and morphogenesis. She is affiliated with the Quantitative and Computational Developmental Biology research cluster and the NCSU/UNC Department of Biomedical Engineering. Dr. Lubkin holds roles such as SIAM representative to the Joint Committee on Women in Mathematics (2017-23) and former Publications Chair of the Society for Mathematical Biology (2004-2016). Education: Ph.D. in Applied Mathematics from Cornell University (1992). Research Interests: Modeling biological systems Continuum mechanics of soft tissues Mechanobiology and drug delivery Biomechanics of morphogenesis Collaborations with experimental biologists and engineers Funding: Supported by the Simons Foundation, NSF, and NIH. Advises students in Biomathematics, Applied Mathematics, Biomedical Engineering, and Mechanical Engineering. Professional Activities: National SIAM committee roles Leadership in mathematical biology organizations Active in promoting interdisciplinary collaborations

Christos GagatsosView profile

Assistant Professor

• Quantum Technologies
• Quantum Sensing
• Quantum Communications
• +10 more

Christos Gagatsos is an Assistant Professor in the Department of Electrical and Computer Engineering and a member of the Wyant College of Optical Sciences at the University of Arizona. He joined the university in 2018 as a postdoctoral research associate, was promoted to Assistant Research Professor in 2020, and became an Assistant Professor in ECE in 2023. Prior to this, he was a postdoctoral research fellow at the University of Warwick, UK. His educational background includes: PhD in Engineering Sciences and Technology, Université Libre de Bruxelles and École Polytechnique, Belgium (2014) MSc in Physics of Elementary Particles, University of Athens, Greece (2010) BSc in Physics, University of Athens, Greece (2007) Christos Gagatsos's research lies at the intersection of quantum information, quantum sensing, and quantum communications, with a strong theoretical focus on bosonic systems. His work explores fundamental concepts such as entanglement, non-Gaussianity, and Bayesian estimation in quantum systems. He is particularly interested in pushing the limits of quantum-enhanced sensing, including optical phase and transmissivity estimation, and in developing theoretical frameworks for quantum detection and discrimination. His teaching interests include quantum information, quantum optics, probability theory, and applied mathematics. The recent trend in his publications reflects a deep engagement with Bayesian methods in quantum parameter estimation, quantum change point detection, and the characterization of quantum states through measures like Wigner entropy. His work spans both fundamental quantum theory and practical applications in sensing and communication, often bridging classical and quantum approaches. He advises several graduate students across departments, including Boyu Zhou (Physics), Ali Cox (Physics), Qipeng Qian (Mathematics), and Leo Bia (Optical Sciences). While no formal scientific awards are listed in the provided text, editorial recognition such as an Editor’s Pick in APL Quantum highlights the impact of his research. Christos Gagatsos leads a research group focused on theoretical quantum information, actively collaborating with quantum research groups across the University of Arizona, Arizona State University, and international institutions in the USA and Europe. His lab investigates quantum sensing, communications, and foundational aspects of quantum mechanics using bosonic platforms, fostering a collaborative and interdisciplinary research environment.

Jeppe Revall FrisvadView profile

Associate Professor

• Computer Graphics
• Digital Image Synthesis
• Realistic Rendering
• +7 more

Jeppe Revall Frisvad is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), within the Visual Computing group. His work bridges computer graphics, material science, and applied optics, focusing on realistic rendering and material appearance modeling. Ph.D. in Computer Graphics, DTU Informatics (2008) M.Sc. in Engineering (Applied Mathematics), DTU (2004) Education in University Teaching, LearningLab DTU (2008–2009) His research centers on computing material appearance from physical and chemical properties, developing faster and more accurate physically based rendering methods. Key areas include light scattering, bidirectional reflectance distribution functions (BRDF), anisotropy, and translucency modeling. Applications span computer games, movies, digital prototyping, architectural visualization, and training simulators. His recent publications (2024–2025) reflect a strong trend in digitizing material appearance, especially for 3D printing and food science, using spectrophotometry and optical validation. The work combines computer graphics with interdisciplinary applications in food structure and biological imaging, emphasizing measurement, modeling, and simulation. Scientific Awards: Research travel prize from AEG Elektronfonden (2006) IGDA scholarship for GDCE 2005 DTU Ph.D. scholarship (2004) He actively supervises Ph.D. students and leads multiple research projects, including those on organ-on-chip imaging, cheese quality analysis, and optical modeling of teeth. He collaborates across disciplines and institutions, with external research stays at UC San Diego and the University of Otago. He is involved in projects integrating AI with 3D imaging and material digitization. Jeppe is a key member of the Visual Computing research environment at DTU, contributing to both fundamental rendering algorithms and practical applications in industry and science.

• Serious Games
• Healthcare Technology
• Gamification
• +4 more

Simon McCallum is an Associate Professor at NTNU’s Faculty of Information Technology and Electrical Engineering. Born in New Zealand, he transitioned from commercial game development in Norway to academia in 2009. His research focuses on Serious Games, particularly in healthcare contexts, gamification, and virtual reality applications. He holds a PhD from the University of Otago (2007), where he studied Computer Science, Mathematics, Psychology, and Philosophy. McCallum has contributed to over 30 publications, including works on cognitive health gaming, software engineering education, and AR applications. He teaches courses such as IMT4307 (Serious Games Research) and IMT3603 (Game Programming). His key projects include the Smartkuber AR game for cognitive screening and the Traction Trebuchet historical engineering study. McCallum has collaborated with institutions like the University of Otago and has engaged in outreach through conferences and media appearances, promoting game technology in healthcare and education.

Bruno LemaitreView profile

Professor

• Immunology
• Innate Immunity
• Toll-like Receptors (TLRs)
• +7 more

Bruno Lemaitre is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Life Sciences and the Global Health Institute (UPLEM). He also contributes to teaching in the Doctoral Program in Molecular and Cellular Life Sciences (EDMS), the School of Humanities (SHS), and the School of Basic Sciences (SV-SSV). He leads the Lemaitre Lab, focusing on immunology and host-pathogen interactions. Full Professor, EPFL – Global Health Institute (UPLEM) Full Professor, EPFL – School of Life Sciences (SV-SSV) Full Professor, EPFL – Doctoral Program (EDMS) Full Professor, EPFL – School of Humanities (SHS) Member, EPFL Committee of Academic Evaluation (CEAE) His research spans immunology, evolutionary psychology, and the sociology of science. Key areas include innate immunity, Toll-like receptors, Drosophila host defense, and the influence of narcissism on scientific success. He has published extensively on how personality traits shape research culture and ethics. The most recent 15 articles reflect a strong interdisciplinary trend, combining molecular immunology with psychological and sociological themes. While early works focus on TLRs and Drosophila immunity, recent publications explore narcissism, obesity, scientific discovery myths, and the cultural impact of personality. This indicates a broadening research scope from molecular biology to the human dimensions of science. Scientific awards and recognitions include: EMBO Member (2007) Bruno Lemaitre supervises a dynamic group of PhD students, both current and past, and is involved in significant educational initiatives, including MOOCs on immunology and authored textbooks. He has also contributed to public discourse through interviews and media appearances. His laboratory, the Lemaitre Lab, is a hub for research on infection and immunity, and he plays a role in academic governance through committee memberships.

Mingyi HongView profile

Associate Professor

• Optimization
• Machine Learning
• Signal Processing
• +7 more

Mingyi Hong is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Minnesota , where he leads the OptimAI-Lab . His work bridges optimization theory , machine learning , and signal processing , with a focus on foundation models like LLMs and diffusion models. Education : Not explicitly mentioned in the text Current Projects : NSF grants on bilevel optimization, LLM unlearning, and inverse reinforcement learning Research Themes : Bilevel Optimization : Applications in LLM alignment, unlearning, and wireless systems LLM Safety : Unlearning, alignment with human feedback, robustness Diffusion Models : Inference-time alignment, adversarial training Distributed Optimization : Privacy-preserving algorithms, federated learning Recent Publications highlight trends in LLM unlearning (BLUR, LUME), optimization theory (Barrier Functions, νSAM), and diffusion models (Direct Noise Optimization). His group has secured NSF , AWS , Cisco , and Open Philanthropy grants. Scientific Recognition : IEEE Fellow (2025) SPS Best Paper Award (2022, 2021, 2018) Doctoral Dissertation Fellowship (2024) IBM Pat Goldberg Memorial Award (2022) He mentors PhD students like Siliang Zeng and Xinwei Zhang , and collaborates with institutions including Michigan State University , Amazon , and NIH on projects spanning UHF MRI technology to climate-smart agriculture .

Mingfeng WangView profile

Senior Lecturer

• Continuum Robotics
• Legged Robotics
• Soft Robotics
• +5 more

Dr. Mingfeng Wang is a Senior Lecturer in Robotics and Autonomous Systems at Brunel University London, affiliated with the Department of Mechanical and Aerospace Engineering within the College of Engineering, Design and Physical Sciences. His research focuses on specialized robotic systems including continuum, legged, soft, precision farming, and miniaturized robots. Chartered Engineer (CEng) with Engineering Council UK Fellow of the Higher Education Academy (FHEA) Member of IEEE, IEEE-RAS, IMechE, and IFToMM Editorial roles: Associate Editor of International Journal of Advanced Robotic Systems (JCR-Q3); Associate Editor of Frontiers in Robotics and AI (JCR-Q2); Editor of Information Processing in Agriculture (JCR-Q1), Biomimetic Intelligence and Robotics (JCR-Q1), and STEM Education Research expertise includes: Continuum Robotics : Design of extra-slender continuum robots (diameter-to-length ratio Legged Robotics : Parallel mechanism-based biped and hexapod robots for extreme environments Miniaturized Robotics : Active locomotion and drug delivery in capsule endoscopes Soft Robotics : Compliant end-effectors and bio-inspired designs Precision Farming : Laser weeding systems and agricultural automation Key scientific awards: BRIEF award (2022) TAROS Best Paper Post Nomination (2022) IFToMM Asian-MMS Best Paper Award (2014) Recent publications focus on: Cochlear implant surgery robotics Passive compliance in train fluid servicing Snake-biomimetic sealing surfaces Parallel kinematic manipulators Capsule endoscope image enhancement Professional services include conference organization (TAROS 2023/2024 Steering Committee; TAROS 2024 Programme Chair) and journal refereeing for IEEE-ASME Transactions on Mechatronics and Scientific Reports.