جستجوی استاد راهنمای دانشگاهی

• Wearable and Implantable Antennas
• RF Sensing
• Dielectric Spectroscopy
• +۶ مورد دیگر

Dr. Tuba Yılmaz Abdolsaheb is an Associate Professor in the Electronics and Communication Engineering Department at Istanbul Technical University (ITU), with a Marie Sklodowska Curie Research Fellowship. She specializes in microwave imaging, biomedical engineering, and medical device development, particularly in applications like breast cancer diagnosis and hyperthermia treatment. Her research focuses on wearable/implantable antennas, dielectric spectroscopy, and energy harvesting technologies. Education: PhD (Queen Mary University of London, 2013), MSc (Mississippi State University, 2009), BSc (Istanbul Technical University, 2007). Research Interests: Wearable/Implantable Antennas, RF Sensing, Dielectric Spectroscopy, Microwave Tomography, Wireless Power Transfer. Her work bridges engineering and medicine, addressing challenges in non-invasive diagnostics and therapeutic technologies. Notable Projects: Principal Investigator for TUBITAK-funded projects (e.g., microwave imaging for breast cancer, hyperthermia systems) and a Marie Curie grant (MIDxPRO). Collaborates on biomedical device development, including portable hyperthermia devices and tissue characterization systems. Awards: URSI Young Scientist Award (2017), Marie Curie Fellowship (2016), and multiple travel/poster awards recognizing her contributions to antenna design and biomedical applications. Lab/Teams: Engaged in ITU’s Medical Devices Research Group, contributing to interdisciplinary projects in bioelectromagnetics and clinical engineering.

• Behavior Neuroendocrinology
• Aquaculture
• Fish Physiology
• +۳ مورد دیگر

Bengt Erik Höglund is an Adjunct Professor at the Department of Natural Sciences, University of Agder. He holds a PhD from Uppsala University (2001) and has extensive postdoctoral experience (2001-2007) followed by a senior researcher role at the Technical University of Denmark (2007-2014). His research focuses on behavior neuroendocrinology in fish and crustaceans, emphasizing stress physiology, coping styles, and aquaculture welfare. He has coordinated courses in human physiology at UiA since 2005 and supervised four PhD students (2011, 2013) and two master’s students (1999, 2011). His recent work explores chronic stress impacts on fish neuroendocrine profiles, environmental acidification effects, and cardiac morphological development in salmon. Key themes include stress resilience, environmental signaling, and behavioral adaptations to anthropogenic changes. Collaborative projects involve hydropower impacts, predator cue responses, and aquaculture system dynamics. Notable contributions include studies on depression-like profiles in salmon, hydrogen sulphide dynamics in recirculating systems, and neuroendocrine indicators of allostatic load. He has participated in interdisciplinary initiatives like the Blekeprosjektet (2014–2017) and projects on hydropower-induced behavioral selection in salmon.

Mayank Chadhaمشاهده پروفایل

استادیار مدعو

• Structural Health Monitoring
• Applied Mechanics
• Machine Learning
• +۷ مورد دیگر

Mayank Chadha is an Assistant Adjunct Professor in the Department of Structural Engineering at the University of California, San Diego. He holds a Ph.D. and M.S. in Structural Engineering from UC San Diego and a B.E. in Civil Engineering from PSG College of Technology, Anna University. His research focuses on integrating applied mechanics, machine learning, and Bayesian methodologies to address challenges in structural health monitoring (SHM), risk analysis, and optimal sensor design. He also explores the application of physics-constrained machine learning in hydrology and battery degradation modeling. Education: 2019: Ph.D. in Structural Engineering, UC San Diego 2023: Postdoctoral Fellowship, UC San Diego 2014: B.E. in Civil Engineering, PSG College of Technology Dr. Chadha’s research interests include structural health monitoring, applied mechanics, uncertainty quantification, and the development of decision-making frameworks for engineering systems. He has pioneered work on Bayesian model optimization, sensor placement strategies, and value-of-information analysis. His interdisciplinary approach bridges theoretical mechanics with practical data-driven solutions for modern engineering problems. His recent work emphasizes hybrid physics-based machine learning models for streamflow forecasting and battery RUL prediction, demonstrating the fusion of computational efficiency and physical principles. He has authored numerous articles on optimal sensor design, VoI metrics, and risk-informed decision-making in SHM systems. Scientific Awards: Gold medal for CBSE 12th exams (2010) Central Government Fellowship (2014) Gold medal for Civil Engineering proficiency (2014) In addition to academia, Dr. Chadha co-founded LogSpi LP, a quantitative investment hedge fund. He teaches courses on mechanics and signal processing, emphasizing foundational engineering principles and their real-world applications. His research also extends to the development of higher-order geometrically exact beam theories, with applications in computer graphics and shape sensing. He actively collaborates with the U.S. Army Corps of Engineers on projects involving inland waterway infrastructure and risk-based sensor design.

• Ancient DNA Analysis
• Population Genetics
• Evolutionary Anthropology
• +۳ مورد دیگر

Pere Gelabert is an Assistant Professor in the Department of Evolutionary Anthropology at the Faculty of Life Sciences. His research focuses on ancient DNA analysis, population genetics, and interdisciplinary studies of human evolution and prehistoric societies. He has been involved in major projects such as 'Unveiling the Shadows: Illuminating Late Pleistocene Human-Carnivore Interactions in Europe' and 'Social genomics in Late Antique and Early-Medieval societies'. No educational background information is explicitly provided in the text. His research interests include: Analysis of ancient DNA to reconstruct population structures and ancestry Investigations into Late Pleistocene human-animal dynamics and hunter-gatherer societies Genomic studies of Neandertals and other hominin species Applications of sedimentary DNA (sedaDNA) in archaeological contexts Genetic epidemiology of ancient pathogens like Plasmodium Interdisciplinary approaches combining genomics with bioarchaeology He has received notable awards including: HEAS Seed Grant (2022) PCA Best Article 2020 Prize for 'Social genomics in Late Antique and Early-Medieval societies' (2023) While no formal advisees are listed, his research projects indicate leadership in academic grants. Grants include two active research funding projects focusing on Pleistocene human-carnivore interactions and social genomics in historical societies. His work involves collaborations across institutions and continents, with a focus on archaeological sites and museum collections. He regularly presents findings at scientific conferences and public lectures, including recent talks on sedaDNA applications and Neandertal site cataloging.

Bahar Haghighatمشاهده پروفایل

استادیار

• Robotics
• Control Systems
• Artificial Intelligence
• +۱۱ مورد دیگر

Bahar Haghighat is a Tenure Track Assistant Professor in Robotics and Automation at the Faculty of Science and Engineering, University of Groningen. She leads the Distributed Autonomous Intelligent Systems (DAISY) Lab as Principal Investigator and contributes to academic governance as a Member of the Faculty Council. Her professional affiliations include the Royal Netherlands Institute of Engineers (KIVI), the Institute of Electrical and Electronics Engineers (IEEE), and editorial roles with Nature Portfolio Journal Robotics and Springer Nature Journal Autonomous Robots. Her educational background includes: PhD in Robotics, Control, and Intelligent Systems from the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland (2018) Master's degree in Electrical Engineering/Digital Electronics from Sharif University of Technology (SUT), Tehran, Iran Bachelor's degree in Electrical Engineering/Physics (double major) from Sharif University of Technology (SUT), Tehran, Iran Dr. Haghighat's research focuses on building novel miniaturized robotic swarms and algorithmic frameworks for sensing, surveying, and inspection applications. Her work spans mechatronics, electronics, embedded systems, embedded artificial intelligence and machine learning, and distributed systems. She envisions developing surface, aquatic, and aerial miniaturized robot swarms and small-scale intelligent devices for basic research and commercial applications including inspection of complex structures, environmental monitoring, space exploration, and search-and-rescue operations. Her recent publications demonstrate a strong focus on swarm robotics, particularly using particle swarm optimization techniques for multi-robot coordination, surface inspection tasks, and spacecraft hull inspection. Her research shows an interdisciplinary approach combining mechatronic design with advanced algorithms for self-assembly and collective decision-making in resource-constrained robotic systems. Her notable scientific achievements include: EPFL's PhD research award of Gilbert Hausmann for the best PhD thesis in mechanical engineering, electricity, and physics (2019) EPFL distinction of excellence for a PhD thesis in Robotics, Control, and Intelligent Systems (2018) Swiss National Science Foundation Postdoc Mobility Fellowship (2019) Swiss National Science Foundation Early Postdoc Mobility Fellowship (2017) Third place in EPFL's "My Thesis in 180 Seconds" competition (2017) EECS Rising Star recognition (2021 at MIT and 2019 at UIUC) Dr. Haghighat has served as Program Co-Chair for The International Symposium on Distributed Autonomous Robotic Systems (DARS) and has held visiting scholar positions at MIT and Harvard University. Her research has received media attention for applications in Mars rover technology and drone swarms for defect detection. She leads the DAISY Lab, which focuses on distributed autonomous intelligent systems for various inspection and monitoring applications.

Dirk Sudholtمشاهده پروفایل

استاد

• Randomised Algorithms
• Algorithmic Analysis
• Combinatorial Optimisation
• +۵ مورد دیگر

Dr. Dirk Sudholt is a Full Professor at the University of Passau and a Visiting Professor at the University of Sheffield. He holds a Ph.D. from Technische Universität Dortmund and has held postdoctoral positions at the International Computer Science Institute (ICSI) in Berkeley and the University of Birmingham. His research focuses on randomized algorithms, algorithmic analysis, and combinatorial optimization, with expertise in the theoretical analysis of bio-inspired search heuristics like evolutionary algorithms and ant colony optimization. His work emphasizes rigorous runtime analysis to understand algorithmic performance and design principles. Education: PhD in Computer Science, Technische Universität Dortmund (2008) Diploma in Computer Science, Technische Universität Dortmund (2004) Research Interests: Runtime analysis of evolutionary algorithms Algorithmic design for multimodal optimization Noise robustness in metaheuristics Parallel and distributed evolutionary computation Grants: SAGE: Speed of Adaptation in Population Genetics and Evolutionary Computation (EU FP7, 2014–2016) Teaching: University of Passau: Courses on algorithms, evolutionary computation, and randomized algorithms

• Microrobotics
• Biomedical Engineering
• Biohybrid Systems
• +۴ مورد دیگر

Veronika Magdanz is an Assistant Professor in Systems Design Engineering at the University of Waterloo since 2022, specializing in microrobotics for medical applications. Her research focuses on biohybrid systems, such as leveraging biological components like sperm cells to develop innovative medical solutions, alongside bioinspired magnetic microrobots controlled via wireless magnetic fields. Education: She earned a Doctorate in Biology from TU Dresden (2016) and a Master of Science in Biotechnology from TU Braunschweig (2010). Her postdoctoral work included a Humboldt Fellowship at the Institute for Bioengineering of Catalonia, where she explored flexible magnetic microrobots and 3D bioprinting of muscle tissue. Research Interests: Her work spans microrobotics, biohybrid systems, magnetic actuation, bioprinting, and medical robotics. She pioneers applications such as sperm-driven microrobots for targeted drug delivery and wireless-controlled soft robots for clinical interventions. Grants & Awards: She secured over $900K in government funding for her research. Her lab focuses on advancing biomedical robotics and has contributed to breakthroughs in sperm cell dynamics and magnetic microactuation. Labs/Teams: Her research involves collaborations across disciplines, including bioengineering, materials science, and robotics, with a focus on translating innovations into clinical applications.

• Robotics
• Swarm Robotics
• Collective Decision Making
• +۳ مورد دیگر

Eliseo Ferrante is an Assistant Professor at the Faculty of Science, Department of Artificial Intelligence, Vrije Universiteit Amsterdam. He is also affiliated with the Network Institute. His research focuses on swarm robotics, collective decision-making, and autonomous systems, contributing to UN Sustainable Development Goals. He teaches courses such as 'Learning Machines' and 'Collective Intelligence.' His research explores topics including robot swarms in challenging environments, evolutionary algorithms for adaptive robotics, and morphological evolution in robots. Key contributions include methods for robust swarming in GNSS-denied areas and optimized control strategies for evolvable morphologies. Dr. Ferrante has supervised 2 PhD theses and contributed to datasets on collective motion models and modular robotics. His work emphasizes practical applications of AI in robotics, with a focus on resilience and adaptability in complex systems.

Z. Jack Tsengمشاهده پروفایل

استادیار

• Paleontology
• Evolutionary Biology
• Functional Morphology
• +۳ مورد دیگر

Z. Jack Tseng is an Assistant Professor in the Department of Integrative Biology at the University of California, Berkeley. He leads the Functional Anatomy and Vertebrate Evolution Laboratory (FAVE Lab), focusing on vertebrate evolution, functional morphology, and biomechanics. His research spans carnivoran evolution, saber-toothed cats, and paleobiogeography, often utilizing CT scans and biomechanical simulations. University of California, Berkeley - Department of Integrative Biology His work explores the interplay between form and function in vertebrates, with particular emphasis on: Carnivoran evolutionary trajectories Mechanical adaptations in skulls and jaws Intercontinental dispersal patterns Biomechanical trade-offs in skeletal systems Jack Tseng’s research has yielded significant media coverage and collaborations, including studies on ancient otter migrations and beardog phylogeny. He employs advanced imaging and computational methods to unravel evolutionary mysteries, contributing to understanding of: Paleoecological corridors Convergent evolution Dentition and dietary specialization Extinct predator niches Virtual fossil reconstruction Adaptive landscapes in mammals

• Variational Calculus
• Partial Differential Equations
• Large Deviations Theory
• +۳ مورد دیگر

Dr. Michiel Renger is a researcher at the Department of Mathematics, Technische Universität München (TUM), within the School of Computation, Information and Technology. His research focuses on variational calculus, partial differential equations, large deviations theory, non-equilibrium thermodynamics, and chemical reaction networks. He has contributed to advancing the understanding of macroscopic fluctuation theory, gradient flows, and their applications in stochastic systems. Teaching responsibilities include courses on higher mathematics for engineering students at TUM and specialized lectures on large deviations and convex analysis at TU Berlin. His work bridges theoretical mathematics with applications in physics and engineering, emphasizing interdisciplinary approaches. Renger’s publications span peer-reviewed journals in mathematics and physics, with a focus on rigorous probabilistic and analytical methods. He holds a PhD in Mathematics from Technische Universiteit Eindhoven (2013) and has collaborated on projects in collaboration engineering, addressing challenges in collaborative modeling and organizational design. His research also extends to applied problems like node counting in wireless networks and statistical consulting for industry.

• Artificial Intelligence
• Machine Learning
• Algorithm Selection
• +۴ مورد دیگر

Lars Kotthoff is the Templeton Associate Professor and Derecho Professor at the University of Wyoming's School of Computing, Department of Electrical Engineering and Computer Science. He leads the MALLET lab, focusing on meta-algorithmics, learning, and large-scale empirical testing. His research integrates AI and machine learning to develop robust systems, particularly in algorithm selection, configuration, and automated machine learning (AutoML). He has held sabbaticals and collaborations globally, including at the University of Warsaw and NASA Ames. Awards include the Templeton Endowed Chair and Open Source Machine Learning Award. His work bridges computational mechanics, materials science, and optimization heuristics. Research interests include Bayesian optimization for materials science, automated parameter tuning, and interpretable machine learning models. Key projects include optimizing laser-induced graphene production and developing the mlr3 framework. Grants include NASA EPSCoR funding for in-space manufacturing and a Microsoft grant for biomedical imaging. He advises graduate and undergraduate students, mentors Google Summer of Code projects, and organizes workshops/conferences like COSEAL and Dagstuhl seminars. Publications span automated algorithm design, performance benchmarking, and interdisciplinary applications. His work emphasizes making machine learning accessible to non-experts through tools like Auto-WEKA and the mlr3 ecosystem. Current projects include NASA-funded advanced electronics manufacturing and collaborations with institutions worldwide.

Jean-Michel Aneمشاهده پروفایل

استاد

• Plant-Microbe Symbiotic Interactions
• Nitrogen Fixation
• Agricultural Sustainability
• +۳ مورد دیگر

Dr. Jean-Michel Ane is the Kellet Professor of Bacteriology & Agronomy at the University of Wisconsin-Madison. His research focuses on plant-microbe symbiotic interactions, particularly nitrogen fixation in legumes and cereals. He leads the Plant-Microbe Symbiosis Lab and holds affiliations with the Microbiology Doctoral Training Program and Plant Breeding programs. Education B.S. Molecular and Cellular Biology, University of Lyon (1995) M.S. Plant Cellular and Molecular Biology, University of Toulouse (1997) Ph.D. Plant Cellular and Molecular Biology, University of Toulouse (2002) Research Interests Dr. Ane's work bridges fundamental biology and agricultural applications. His lab studies molecular mechanisms of symbiosis in Medicago truncatula and crops like soybean and sorghum. Key areas include: Engineering nitrogen-fixing microbes for cereal crops Signal transduction in symbiotic signaling pathways Ecological roles of plant-microbe interactions Recent Article Trends His 2023-2025 publications emphasize synthetic biology approaches for nitrogen fixation, symbiotic signaling pathways, and applications in sustainable agriculture. Major themes include engineering diazotrophs, analyzing single-cell transcriptomes, and optimizing symbiotic systems for crops. Awards 2015 Vilas Mid-Career Investigator Award 2014 Rothermel Bascom Professorship 1998 French National Education Agrégation Grants & Advising Dr. Ane has secured major grants supporting symbiosis research. He mentors 2 graduate students and oversees a lab of postdocs/researchers including Burcu Alptekin, Rubens Diogo, and Junko Maeda. His work spans collaborative projects with institutions worldwide. Labs/Teams His lab operates in the Microbial Sciences Building, focusing on cutting-edge techniques like mass spectrometry imaging and synthetic biology to advance symbiotic research.

• Molecular Microbiology
• Genomics Surveillance
• Antimicrobial Resistance
• +۵ مورد دیگر

Jessica Agius is a Postdoctoral Research Fellow at the Centre for Infectious Diseases and Microbiology - Public Health and the Sydney Infectious Diseases Institute , University of Sydney. Her work integrates molecular epidemiology and genomics surveillance to tackle infectious disease threats. Education : BAnVetBioSc (Hons I, 2016), PhD (2021) from University of Sydney Research Interests include: Molecular Microbiology Genomics Surveillance Antimicrobial Resistance One Health Publications highlight her focus on SARS-CoV-2 genomic variability, Enterococcus pathogenesis in reptiles, and adenovirus diversity in wildlife. Her work bridges in vitro and clinical cohort studies. Scientific Awards : Best Poster & Presentation (2018, Marie Bashir Institute) Academic Achievement Award (2016, Australian Society for Parasitology) Grants include Holsworth Wildlife Research Endowment and National Environmental Science Program funding. She supervises honours students on topics spanning reptile health and antimicrobial resistance.

Anke Frankمشاهده پروفایل

مدرس

• Ecology
• Conservation Biology
• Wildlife Management
• +۵ مورد دیگر

Dr Anke Frank is a Lecturer in Ecology at Charles Sturt University's School of Agricultural, Environmental and Veterinary Sciences. She holds a PhD in Terrestrial Ecology from the University of Sydney (2010) and a teaching qualification from the University of Bonn. Her research focuses on predator-prey dynamics, introduced species impacts, and Indigenous-led 'right-way science' collaborations with the Budjiti people of Paroo River Country. She collaborates internationally through the Centre for Australian Studies (University of Cologne). Research Interests: Ecological impacts of invasive species Chemical ecology and predator-prey interactions Biodiversity conservation in dryland ecosystems Indigenous knowledge integration in ecological management Pathogen roles in wildlife ecosystems Teaching: Engages undergraduate/graduate students in ecology, conservation, and environmental statistics across multiple universities. Specializes in experiential learning through fieldwork and community events like International Bat Night. Collaborations: Works with global institutions (e.g., Leibniz Association, IPBES) to address UN Sustainability Goals and biodiversity targets. Active in cross-disciplinary initiatives like DroughtNet and Biodesert projects in South Africa. Labs/Teams: Collaborates with Dr. Greg Doran (fox scent research) and Assoc. Prof. Andrew Peters (wildlife disease ecology). Leads right-way science initiatives with Budjiti elders and CAS partners.

Amlan Chatterjeeمشاهده پروفایل

دانشیار

• High-Performance Computing
• Big Data
• Graph Compression
• +۵ مورد دیگر

Dr. Amlan Chatterjee is an Associate Professor in the Department of Computer Science at California State University, Dominguez Hills. His work focuses on high-performance computing, big data analytics, and GPU-based graph compression techniques. He has held academic roles since 2015, including Assistant Professor (2015-2021) and currently serves as Associate Professor. His research explores efficient computation on large datasets using multi-core architectures and GPUs, alongside cloud computing optimization and IoT applications in aviation and health monitoring. Education: Ph.D., Computer Science, University of Oklahoma, 2014 M.S., Computer Science, State University of New York, 2009 B.Tech., Computer Science & Engineering, West Bengal University of Technology, 2007 Research Interests: Dr. Chatterjee's research spans graph compression, social network analysis, cloud resource optimization, and IoT-driven solutions for aviation safety and health monitoring. He has mentored students in projects like GPU-based big data processing and cloud computing efficiency. Awards: Graduate Computer Science Scholarship (University of Oklahoma, 2012-13) Computer Science Advisory Board Scholarship (2012) Phillips Petroleum Scholarship (2010-11) Top Undergraduate Rank (1st/68 students) Academic Contributions: He has served on numerous committees, including the Research Chair for Untenured Faculty (2016-17), IEEE conference session chairs, and accreditation boards. His teaching includes courses on data structures, operating systems, and introductory computer science.