Ajit Rajwade is a Professor at the Department of Computer Science and Engineering , Indian Institute of Technology Bombay. His research spans Artificial Intelligence , Compressed Sensing , and Medical Imaging , with affiliations to the Centre for Machine Intelligence and Data Science and the Koita Centre for Digital Health . Education : PhD in Computer and Information Science and Engineering, University of Florida (2010) MSc in Computer Science, McGill University (2004) BTech in Computer Engineering, University of Pune (2002) His research interests focus on intelligent data acquisition, particularly in neural network analysis , graph signal processing , and medical imaging . He develops compressed sensing algorithms for inverse problems like tomography and MRI reconstruction , alongside applying group testing to pandemic response. Scientific awards include the Prof. S. P. Sukhatme Award (2024) and Departmental Teaching Excellence (2019). His publications demonstrate expertise in image restoration , noise modeling , and epidemiological algorithms . He has advised PhD students like Sabyasachi Ghosh and Jerin Geo James , with a focus on computationally efficient methods in medical imaging and machine learning .
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۱-۱۵ از ۵۰۵ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Ming Hu is a Professor and University of Toronto Distinguished Professor of Business Operations and Analytics at Rotman School of Management, University of Toronto. He serves as Area Coordinator for the Operations Management & Statistics Area and holds editorial leadership roles including Editor-in-Chief of Naval Research Logistics and Associate Editor for multiple top journals. MS in Applied Mathematics, Brown University (2003) PhD in Operations Research, Columbia University (2009) His research focuses on sharing economy , social operations , and platform economics , examining how operational decisions can maximize societal benefit. Key areas include crowdfunding , two-sided markets , crowdsourcing , and group buying , with applications to DEI , sustainability , and AI-empowered operations . Recent work analyzes spatial operations in delivery systems, algorithmic fairness , and climate change adaptation in agricultural supply chains. His publications span top journals like Management Science and Operations Research , covering topics from blockchain traceability to quantum-inspired optimization . Scientific recognitions include: Wickham Skinner Early-Career Research Award (2016) Best Operations Management Paper in Management Science (2017) 2018 Poets & Quants Best 40 Under 40 MBA Professors As an Amazon Scholar (2022–) and Chair of Chain Analytics Institute (2023–), he bridges academic research with industry applications in AI-driven logistics and sustainable operations.
Anthony Rollett is a Professor in the Department of Materials Science and Engineering at Carnegie Mellon University , where he has been a faculty member since 1995. He serves as the Principal Investigator and Co-Director of the NASA-supported Institute for Model-Based Qualification & Certification of Additive Manufacturing (IMQCAM) and co-director of the Next Manufacturing Center . Prior to CMU, he held leadership roles at Los Alamos National Laboratory (1991-1995). Education: Ph.D., Materials Engineering, Drexel University (1987) MA, Metallurgy and Materials Science, Cambridge University (1977) Research Interests: Rollett’s work focuses on microstructural evolution and microstructure-property relationships in 3D using experiments and simulations. His expertise spans additive manufacturing , metal 3D printing , materials for energy systems , grain growth , recrystallization , and stereology , with techniques like high-energy diffraction microscopy (HEDM) and dynamic x-ray radiography (DXR) . Scientific Contributions: He has over 320 peer-reviewed publications and an h-index >80 . His recent articles highlight machine learning for laser processing , fatigue analysis of additively manufactured alloys, and design optimization for heat exchangers in supercritical CO2 and solar thermal applications . Scientific Awards: Fellow of ASM International (1996) Fellow of the Institute of Physics (UK) (2004) Fellow of The Minerals, Metals & Materials Society (TMS) (2011) Cyril Stanley Smith Award (TMS, 2014) Member of Honor, French Metallurgical Society (2015) US Steel Professor (2017) Francqui International Professor (2020-2021) International FAME Award (2023) Leadership & Impact: Rollett co-led the development of a NASA Space Technology Research Institute for additive manufacturing and established a new master’s program in additive manufacturing (2018). His research group is funded by industry , federal agencies , and Pennsylvania state grants . He also serves on the Basic Energy Science Advisory Committee and Defense Programs Advisory Committee for the Department of Energy.
Dr Adam Ritchie serves as a Senior Vaccinologist at the University of Oxford's Jenner Institute and Lecturer in Human Science at St Catherine's College. His work focuses on translating academic vaccine research into real-world impact through the development, manufacture, and clinical testing of candidates for rabies, Epstein-Barr virus (EBV), and SARS-CoV-2. Education: Holds a BSc, PhD, and Fellow of the Higher Education Academy (FHEA) qualification. His research spans vaccine development, clinical trial design, regulatory affairs, and public policy through Vax-Hub Global. Key interests include adenovirus-vectored platforms, scalable manufacturing processes, and addressing global health challenges in resource-limited settings. Analysis of his 2020-2025 publications reveals a cohesive research trajectory centered on ChAdOx1-vectored vaccines. Dominant themes include prime-boost regimens, intranasal delivery systems, cost-effectiveness modeling for low-income countries, and material science applications for vaccine stabilization. His work bridges laboratory innovation with implementation science, particularly in rabies prophylaxis and pandemic response. Ritchie actively contributes to the Douglas Research Group at the Jenner Institute and global vaccine initiatives through Vax-Hub. His collaborative work appears in high-impact journals including The Lancet, Nature Medicine, and Vaccine, with emphasis on clinical translation and equitable vaccine access.
Prof. Daniel Memmert is a Professor at the German Sport University Cologne, leading research in Sport Informatics and Sports Games within the Institute of Exercise Training and Sport Informatics. His work focuses on cognitive aspects of sports performance, decision-making, and data-driven analysis in football (soccer) and other sports. He has published extensively on topics like penalty kick strategies, home advantage dynamics, artificial intelligence applications in coaching, and route-setting in climbing. Memmert's research bridges sports science, computer science, and psychology, with over 550 publications and 41 projects to his name. He frequently engages with media, explaining complex sports phenomena to the public. Key Research Areas: Football analytics, cognitive psychology in sports, sports technology, decision-making under pressure Media Contributions: Over 50 media features discussing topics such as AI in coaching, referee bias, and athlete creativity Projects: Includes initiatives on sports data visualization, performance metrics, and prevention of sports betting addiction His work emphasizes translating academic findings into practical tools for athletes, coaches, and sports organizations, combining rigorous data analysis with real-world applications.
Chee-Wooi Ten is a tenured Professor in the Department of Electrical and Computer Engineering at Michigan Technological University, where he has served since 2010 and achieved tenure in 2016. He concurrently holds an Affiliated Professor appointment in Applied Computing and directs both the PSERC Site and ICC CPS Center. His institutional roles emphasize cyber-physical security integration within power infrastructure. His educational background includes: PhD in Electrical Engineering from University College Dublin (2009) MSc in Electrical Engineering from Iowa State University (2001) BSc in Electrical Engineering from Iowa State University (1999) Ten's research pioneers cyber-informed security engineering strategies for bulk power systems, focusing on quantifying rare events through system risk models and data science. His work bridges power grid interactions with robotics and transportation systems to advance decarbonization and electrification. Key methodologies include validating cyber-physical security frameworks against steady-state and dynamic grid approaches, with emphasis on attack/defense combinatorics and smart home technologies. This transdisciplinary approach supports the fourth industrial revolution's resilience requirements. His publication trends reveal strong focus on risk-aggregated substation testbeds using generative adversarial networks, cyber insurance models for power systems, and cascading failure analysis from switching attacks. Recent works increasingly integrate machine learning with physics-based modeling to address cybersecurity threats in inverter-based resource integration and distribution emergency operations. Ten has secured over $6.5M in active funding including: $2M DOE grant (MTU portion $105,000) for CyDERMS Center on DERs/Microgrids cybersecurity $704,409 CyManII award for secure digitalization in smart manufacturing $1.05M DOE ARPA-E grant for decarbonized freight transportation modeling NSF CyberCorps Scholarship for Service program ($3.38M) His grants consistently address risk management through data-driven and physics-based modeling, with industry partnerships through PSERC and utility collaborations. As ICC CPS Center Director, he leads research on cyber-physical security testbeds and coordinates the PSERC Summer Transformation School. His team develops validation frameworks for NERC CIP compliance while addressing practical pain points in OT cybersecurity for grid operators.
Han Huمشاهده پروفایل
استادیار
Dr. Han Hu serves as Assistant Professor in the Department of Mechanical Engineering at the University of Arkansas College of Engineering, holding the Twenty-First Century Professorship since 2025. He leads the NED3 research laboratory with active collaborations including Purdue University's Cooling Technologies Research Center and NASA Glenn Research Center. Education: Ph.D. in Mechanical Engineering, Drexel University (2016) B.S. in Theoretical and Applied Mechanics, University of Science and Technology of China (2011) His research integrates phase-change heat transfer with AI-driven methodologies, focusing on thermal management solutions for power electronics through multimodal sensing systems. Current projects include pumped two-phase cooling for microchannel heat sinks and machine learning applications for bubble dynamics analysis in pool/flow boiling scenarios, supported by NSF and NASA grants. Scientific Recognition: Twenty-First Century Professorship in Engineering (2025) University of Arkansas Outstanding Mentor (2022-2024) Multiple ASEE conference awards for student mentorship (2022-2024) Faculty Gold Medal and Mechanical Engineering Service Award (2023) Dr. Hu mentors seven Ph.D. students and numerous undergraduates, with his NED3 lab securing $2.5M in recent funding including NSF grants for immersion-cooled electric motors and NASA EPSCoR research on boiling heat transfer. His team collaborates with UA-PTC's Aerospace Center of Excellence and ZIN Technologies on practical thermal management applications. The NED3 laboratory operates advanced facilities for synchronized optical, acoustic, and thermal measurements, featuring high-speed thermal imaging systems and custom-built flow boiling test rigs validated through partnerships with power electronics industry leaders.
Joshua Gessمشاهده پروفایل
دانشیار
Joshua Gess is an Associate Professor in the Mechanical, Industrial, and Manufacturing Engineering department at Oregon State University's College of Engineering. He joined Oregon State in 2015 and serves as a co-principal investigator at the Enhanced Heat Transfer Laboratory, where he leads research in thermal management solutions for high-performance microelectronics. His educational background includes: PhD, Mechanical Engineering, Auburn University, 2015 MS, Mechanical Engineering, Auburn University, 2012 B.E., Mechanical Engineering, Vanderbilt University, 2005 Before academia, he worked as a mechanical engineer at SSOE Group (including consulting for Johns Manville) and Northrop Grumman where he focused on military communication equipment. Professor Gess specializes in advancing thermal management solutions for high-performance microelectronic equipment. His research spans multiple scales, examining single and two-phase heat transfer on the macro-scale with passive and active liquid immersion techniques, as well as on the micro and nano scale for complex embedded thermal management solutions. He combines fundamental heat transfer knowledge with novel experimental methods such as two-phase PIV and high-speed image capture to develop reliable and energy-efficient cooling solutions for demanding electronics systems. His publication record demonstrates a clear trajectory toward increasingly sophisticated thermal management solutions, with recent work focusing on additive manufacturing applications for cooling systems, semiconductor thermal management, and nuclear reactor cooling systems. His research has significant implications for data center energy efficiency, where even small improvements in cooling efficiency could save enormous amounts of energy that could be returned to the grid. Gess is deeply committed to mentoring graduate students, emphasizing the practical applications of engineering principles. He attributes his interest in engineering to childhood influences like the movie RoboCop and the TV series MacGyver, and finds the reality of engineering work just as gratifying as he'd imagined. He particularly values the moments when his graduate students "get it" and watching them grow with each new accomplishment. As a person with a disability himself, Gess is passionate about establishing more robust support systems for people with disabilities at Oregon State. He is working with the School of Public Health to start an adaptive sports program, with the goal of building infrastructure that allows anyone to feel welcome and pursue advanced degrees at the university.
Simo Hostikka is a Professor in the Department of Civil Engineering at Aalto University's School of Engineering. His research focuses on fire safety engineering , utilizing numerical fire simulations to address critical challenges in building and infrastructure safety. Key Expertise: Fire Dynamics Simulator (FDS) development, thermal radiation heat transfer, pyrolysis modeling, fire toxicity calculations, and probabilistic risk analysis. Leadership: Supervises advanced fire safety research and contributes to international fire safety standards. Research Trends: Recent publications emphasize fire toxicity modeling , hydrogen fire safety , radiation heat transfer , and fire retardancy of polymeric materials . His work bridges computational methods with real-world fire safety applications. Scientific Awards: Philip Thomas Medal of Excellence (2008, 2005) Sjölin Award (2012) Interflam Trophy (2007) Harmathy Award (2020, 2019) Dean’s Award for Best MSc Thesis (2020) Best Paper in Rakenteiden Mekaniikka (2009) Advising: Supervised Topi Sikanen, who received the Young Talent Award from the International Water Mist Association.
Michael Gasik is a Professor at the Department of Chemical and Metallurgical Engineering, School of Chemical Engineering, Aalto University. With over 30 years of experience in technology transfer, he has led initiatives across the EU, Japan, and the Middle East, including BC-Net (EC DG Enterprise). He serves as an expert for European bodies like EC/REA, COST, and ERC since 1993. His research spans biomaterials ceramic materials metals processing sustainable manufacturing additive manufacturing green energy systems and focuses on interdisciplinary applications in biomedical and environmental engineering. Recent research trends include advanced biomaterials for medical implants (e.g., PEO-coated magnesium alloys) multi-material 3D printing for industrial components green hydrogen production via HyS cycle optimization sustainable polymer composites photocatalytic nanomaterials blockchain-enabled recycling for electric vehicles Scientific accolades include 2023 EORS Ambassador for Finland 2015 National State Prize of Ukraine 2013 M.M. Dobrohotov Award 1997 JSPS Scholarship 1995 Best Doctorate Thesis Award 2007 Certificate of Appreciation for Functional Graded Materials He has secured funding through 10 EU projects, 2 IEA projects, and over 15 national projects, contributing to >300 publications and patents. His expertise extends to technology transfer leadership and peer review for journals and funding agencies in multiple countries.
Dr. Joshua Brinkerhoff is an Associate Professor in Mechanical Engineering at the University of British Columbia Okanagan Campus. He serves as the Associate Director for Research & Industrial Partnerships in the School of Engineering and leads the UBC-Okanagan Computational Fluid Dynamics Laboratory. His research spans computational fluid dynamics, turbomachinery, multiphase flows, hydrogen safety, wind energy, and biofluid mechanics. He teaches courses in mechanics of materials, alternative energy systems, turbulence, computational fluid dynamics, and aircraft design. PhD, Aerospace Engineering (Carleton University, Ottawa, ON) BEng, Aerospace Engineering (Carleton University) Dr. Brinkerhoff’s research interests include: Computational Fluid Dynamics (CFD) for laminar-to-turbulent transition and instability analysis Wind energy systems and turbine aerodynamics Hydrogen storage and safety protocols for transportation Biofluid mechanics for respiratory diseases and aneurysm modeling Multiphase flows in industrial and environmental contexts His publications focus on CFD simulations for: Aerosol dispersion and mitigation in indoor environments Wind farm interactions and atmospheric gravity waves Cavitation and phase transitions in cryogenic and LNG systems Heat transfer optimization in industrial and thermal systems Instability dynamics in buoyancy-driven and swept flows Turbulent structures in fluidized beds and reactors Dr. Brinkerhoff has no listed scientific awards in the provided data but has extensive contributions to renewable energy, hydrogen safety, and medical fluid dynamics. His laboratory develops open-source tools like TOSCA for large-eddy simulations and investigates practical applications in urban air quality, dental aerosol control, and turbine wake modeling.
Ben Bloem-Reddyمشاهده پروفایل
استادیار
- Machine Learning
- Causal Inference
- Bayesian Methods
- +۳ مورد دیگر
Ben Bloem-Reddy is an Assistant Professor in the Department of Statistics at the University of British Columbia (UBC), Vancouver Campus. His research focuses on statistical theory and applications in machine learning, particularly in causal inference, Bayesian methods, neural networks, and probabilistic models. He advises current students Quanhan (Johnny) Xi, Kenny Chiu, and Gian Carlo Diluvi. His work bridges foundational statistical theory with practical machine learning challenges, including causal discovery, model identifiability, and uncertainty quantification. Recent research explores topics such as latent variable models, generative processes, and symmetry in data and algorithms. His contributions span interdisciplinary areas like particle physics applications and information theory-based compression techniques. Ben’s research trends emphasize advancing theoretical guarantees for modern machine learning systems while addressing real-world problems. His publications frequently intersect with algebraic topology (e.g., cocycles in causal inference) and nonparametric methods. He maintains an active lab within the Department of Statistics, fostering collaborations across UBC’s academic ecosystem. No scientific awards are explicitly listed in the provided information. His advising and grant activities focus on statistical methodology development, as evidenced by his student supervision and published work. His office is located in ESB 3168, and he can be reached at benbr@stat.ubc.ca.
Weiyu Xu is a Professor at the University of Iowa, affiliated with both the Department of Electrical and Computer Engineering and the Department of Applied Mathematical and Computational Sciences. He joined the College of Engineering in 2012 and leads the Intelligent Information Processing Lab (IIPL). Ph.D., Electrical Engineering, California Institute of Technology, 2009 M.S., Electrical Engineering, California Institute of Technology, 2006 M.S., Electronic Engineering, Tsinghua University, 2005 B.E., Information Engineering, Beijing University of Posts and Telecommunications, 2002 His research focuses on compressive sensing, information theory, signal processing, network optimization, and deep learning applications in medical imaging and cybersecurity. He has made significant contributions to adversarial attack robustness, distributed optimization algorithms, and medical imaging techniques for OCT segmentation and brachytherapy. Recent publications highlight trends in Adversarial machine learning Medical imaging algorithms Compressed sensing for diagnostics Optimization in wireless communication He has also contributed to federated learning over tree networks and theoretical guarantees for sparse signal recovery. Weiyu Xu's lab, IIPL, integrates deep learning with classical optimization and signal processing. His work bridges foundational theories (e.g., information-theoretic robustness) with real-world applications in healthcare (e.g., cancer treatment planning) and communication systems (e.g., MIMO channel estimation).
Caryl E. Sortwell is a Professor of Translational Neuroscience and Edwin A. Brophy Endowed Chair in Central Nervous System Disorders at Michigan State University's College of Human Medicine. She leads the Sortwell Lab within the Neuroscience Program and Grand Rapids Research Center, focusing on Parkinson's disease (PD) therapeutics. Education : B.S. in Psychology/Pre-medicine (University of Illinois, 1987), Ph.D. in Anatomy and Cell Biology/Neurobiology (University of Illinois at Chicago, 1994) Positions : Assistant/Associate Professor at Rush University Medical Center (1997-2005), Associate Professor at University of Cincinnati (2005-2009), Professor at MSU College of Human Medicine (2009-present) Her research investigates alpha-synuclein pathology in PD using preformed fibril models to study neurodegeneration, neuroinflammation, and therapeutic interventions. She explores neurotrophic factors like BDNF, gene therapies targeting CaV1.3 channels, and deep brain stimulation mechanisms. Her work emphasizes precision medicine approaches to optimize treatment outcomes. Scientific contributions include methodological advancements in neurochemical sensing with diamond electrodes and viral vector delivery systems. Key collaborations include research with Dr. Joe Patterson on alpha-synuclein genetic consequences. Technical Expertise : Immunohistochemistry, stereotactic surgery, in vivo neurotoxicant models, protein analysis (Western blot/ELISA), droplet digital PCR, and neuroinflammatory profiling
Inigo Flores Ituarteمشاهده پروفایل
استاد پژوهشی
- Digital Design and Manufacturing (D2M)
- Sustainable Manufacturing
- Optimization Driven Design
- +۷ مورد دیگر
Inigo Flores Ituarte is a Research Professor at Tampere University's Faculty of Engineering and Natural Sciences, affiliated with the Automation Technology and Mechanical Engineering department. He leads the Digital Design and Manufacturing (D2M) research lab, focusing on sustainable manufacturing and twin-transition strategies integrating digital and green technologies. His work emphasizes optimization-driven design, additive manufacturing innovations, and AI-driven expert systems to enhance energy efficiency and reduce environmental impacts. Key research pillars include: Pillar 1: Twin-transition in Engineering Design and Manufacturing Processes, addressing sustainable manufacturing and intelligent systems Pillar 2: Development of open D2M systems and Process-Structure-Property-Performance (PSPP) linkages in advanced materials His research explores multi-disciplinary optimization combining model-based simulations and data-driven techniques. Notable contributions include generative AI integration in CAD systems, cognitive manufacturing systems, and cost-effective process monitoring using CNN-based methods. Inigo's work emphasizes environmental sustainability, with a focus on reducing manufacturing's energy consumption (54% of global use) and CO2 emissions. He advocates for interconnected material systems, smart manufacturing processes, and AI-assisted decision-making to achieve cognitive intelligence in industrial operations. His D2M lab's overarching goal is to maximize product/process performance while improving cost-effectiveness and minimizing environmental footprints. Recent projects include railway bogie demonstrators via multi-material deposition and sensor systems leveraging IoT and ChatGPT integration.