جست‌وجوی استاد و پژوهشگر

Kimberly B. Rogersمشاهده پروفایل

دانشیار

• Social Psychology
• Sociology of Emotions
• Group Processes
• +۴ مورد دیگر

Kimberly B. Rogers is an Associate Professor of Sociology at Dartmouth College , where she has been employed since 2015. She is affiliated with the Quantitative Social Science Program and the Neukom Institute for Computational Science . Her research focuses on how inequalities are produced, maintained, and resisted through behavior and emotion dynamics in social interactions , with particular attention to status and power hierarchies , occupational inequality , and mental health outcomes . She teaches courses such as Introductory Sociology , Research Methods , and Status and Power in Social Interaction , integrating computational tools into her pedagogy. PhD in Sociology, Duke University (2013) MA in Sociology, Duke University (2008) MA in Psychology, Wake Forest University (2005) BA in Psychology, Randolph-Macon Woman's College (2003) Rogers' research spans three key areas: cultural consensus in identity sentiments , behavioral/emotional responses to inequality , and computational modeling of social processes . Her work reveals how micro-social mechanisms perpetuate or disrupt status hierarchies across contexts like occupational roles , racialized interactions , and digital collaboration . Recent publications examine technological co-diffusion , pandemic-induced identity shifts , and gendered occupational perceptions . Her scholarly output follows trends in computational social science and cross-cultural emotion analysis . She employs Bayesian affect control theory to model dynamic identity processes and uncertainty in interactions , while her 2025 work on violence against women demonstrates applications of general strain theory to contemporary social issues. Senior Faculty Grant (2023-24) , Dartmouth College Wilson Fellowship (2021-22) , Dartmouth College Outstanding Article Award (2017) , American Sociological Association Seed Funding Grant (2016-17) , Dartmouth Provost Doctoral Dissertation Grant (2010-11) , National Science Foundation Rogers has received multiple grants for collaborative projects like THEMIS.COG , examining identity and sentiment modeling in groups . She mentors students through engaged scholarship and social impact practicums , though specific advisees aren't listed. Her 2019-2020 involvement with Campus Compact and 2016 DCSI teaching grant highlight her commitment to community-engaged pedagogy .

Karina Gibertمشاهده پروفایل

استاد

• Data Science
• Artificial Intelligence
• Ethics in AI
• +۷ مورد دیگر

Karina Gibert is a Full Professor at Universitat Politècnica de Catalunya (UPC), specifically at the Faculty of Computer Science of Barcelona (FIB) in the Department of Statistics and Operations Research. With a permanent teaching position since 1990, she contributes to research and education with a focus on Data Science, Artificial Intelligence, Explainable AI, and Ethics in AI. Full Professor, UPC (since 1990) PhD in Informatics Engineering Postgraduate in Higher Education Teaching Director and co-founder of IDEAI research center Dean of the Official Professional College on Informatics Engineering of Catalonia Active in bridging the gender gap in STEAM through multiple initiatives Her research focuses on extracting strategic knowledge from data and intelligent systems with ethical and explainable perspectives. She has led various projects including Diet4You for personalized diets, INSESS-COVID19 for social vulnerability analysis, Top Rosies Talent for female AI development, and ciutadanIA for AI culture promotion. Her work spans health, environment, sustainability, tourism, and social technology applications. As an editor of Environmental Modeling and Software journal and active academic, she contributes to international conferences, working groups, and research collaborations. Her service includes membership on various ethics and AI strategy committees and advisory boards. Women Tech Award 2023 National Informatics Engineering Award in Digital Dissemination 2022 Ada Byron Award 2022 Honorific Mention of Creu Casas award 2021 donaTIC 2018 Award Finalist at AMETIC Awards 2021 Finalist of European Social Services Awards 2021

Hassan Khanمشاهده پروفایل

دانشیار

• Computer Security
• Applied Machine Learning
• Human-Computer Interaction
• +۳ مورد دیگر

Hassan Khan is an Associate Professor at the University of Guelph's School of Computer Science, with research spanning security, systems, and human-computer interaction (HCI). He is a member of the Centre for Advancing Responsible and Ethical Artificial Intelligence (CARE-AI). Research Interests: His work focuses on improving AI-driven mobile security systems through human-in-the-loop evaluations, addressing vulnerabilities in continuous authentication, shoulder surfing, and privacy in enterprise/repair settings. He explores how users interact with security mechanisms and designs interfaces to enhance usability. Scientific Recognition: He has received the NSERC Early Career Researcher Award and a NSERC Discovery Grant, with media coverage in outlets like Time Magazine, The Globe and Mail, and New Scientist. Teaching: Khan teaches courses such as Computer Security Foundations and Advanced Penetration Testing, emphasizing practical cybersecurity and AI systems architecture.

Sanjeev Baskiyarمشاهده پروفایل

استاد

• Scheduling and Cloud Computing
• Computer Architecture
• Real-time and Embedded Computing
• +۱۱ مورد دیگر

Sanjeev Baskiyar is a Professor in the Department of Computer Science and Software Engineering at Auburn University's College of Engineering. He has been actively involved in research, teaching, and academic leadership, with a strong focus on computer systems, real-time and embedded computing, scheduling, cloud and fog computing, and energy-aware architectures. Education: Ph.D., Electrical and Computer Engineering, University of Minnesota M.S., Electrical and Computer Engineering, University of Minnesota B.S., Electronics and Communications, Indian Institute of Science, Bangalore B.S., Physics (with honors), and distinction in Mathematics Dr. Baskiyar’s research interests span scheduling, real-time and embedded systems, computer architecture, fog/cloud computing, thermal/energy-aware computing, and STEM education. His recent work explores machine learning applications in scheduling and quantum computing for fake news detection. He has supervised over 25 graduate students, many of whom now hold academic and industry positions. His recent publications emphasize fog computing simulation, service placement, quantum-inspired fake news detection, and adaptive scheduling using machine learning. These works reflect a trend towards intelligent, scalable, and energy-efficient computing systems, particularly in distributed and edge environments. Scientific Awards and Honors: Walker Teaching Excellence Award, Auburn University, 2020 Summer Faculty Fellow, Air Force Research Labs, 2020 Nominated Best Teaching Assistant, University of Minnesota, 1992 Multiples Merit and State-merit Scholarships Honors in Physics and Distinction in Mathematics Dr. Baskiyar has successfully advised numerous MS and PhD students and secured over $2 million in research funding as Principal Investigator from the National Science Foundation, DARPA, NASA, and industry partners like Wind River Systems and Mentor Graphics. His grants focus on parallel computing education, real-time micro-architectures, and embedded systems. He has also served on editorial boards, program committees, and as a reviewer for NSF and IEEE journals. He has held leadership roles including Senator in the University Faculty Senate and Chair of the E-day Committee. Labs and Research Groups: While not explicitly named, Dr. Baskiyar leads a research group focused on computer systems, scheduling, and embedded computing, as evidenced by his long list of graduate student supervision and funded projects in fog, cloud, and real-time systems.

• Algorithmic and data justice
• Internet studies
• Technology and society
• +۹ مورد دیگر

Juan Carlos De Martin is a Full Professor of Computer Engineering at the Polytechnic of Turin, where he is also co-founder and co-director of the Nexa Center for Internet & Society. He holds a Faculty Associate position at the Berkman Klein Center for Internet & Society at Harvard University and is a member of the Scientific Council of the Treccani Institute and the Steering Committee of Biennale Democracy. He previously served as Vice Rector for Culture and Communication at the Polytechnic of Turin (2018–2023) and as president of its libraries (2007–2015). His research centers on the societal implications of digital technologies, with a strong emphasis on algorithmic and data justice, digital power, and the democratic challenges posed by modern technology. He advocates for a more democratic and ethical technological future, particularly critiquing the dominance of smartphones and promoting digital sovereignty. His recent publications reflect a clear trend toward ethical AI, data protection, and the social impact of algorithms. He has published on gender bias in language models, GDPR compliance tools, and non-discrimination audits in software, demonstrating a sustained commitment to fairness, transparency, and accountability in digital systems. Best Student Paper Award IEEE ISCC 2011 Best Student Paper Award IEEE ICME 2005 Fellow at Harvard University (Berkman Klein Center) (2011–2015, 2016–2024) Faculty Associate at Collège d'études mondos, France (2016) De Martin has advised PhD students like Marco Rondina on Responsible AI and has led numerous EU-funded research projects such as COMMUNIA and DECODE. He has also played a key role in public policy, serving on ministerial working groups on AI and online hate. He is the founder of the Biennale Tecnologia and has authored influential books on the future of universities and technology, all published under Creative Commons licenses. He leads the Nexa Center for Internet & Society, a multidisciplinary research group focused on the legal, economic, and social aspects of the Internet. The center fosters collaboration between computer scientists, legal scholars, and social scientists to address pressing digital challenges.

• Artificial Intelligence
• Human-Computer Interaction
• Computer Vision
• +۴ مورد دیگر

Prof. Dr. Julius Schöning is a Professor at the Faculty of Engineering and Computer Science , Osnabrück University of Applied Sciences. His research focuses on Artificial Intelligence , Human-Computer Interaction , and Computer Vision within agricultural contexts. 2019–Present: Professor, Hochschule Osnabrück 2018–2019: System Architect, ZF Friedrichshafen AG 2014–2018: Researcher, University of Osnabrück 2009–2013: Project Lead/System Engineer, CLAAS Harsewinkel Education: M.Sc. in Intelligent Embedded Microsystems (Freiburg), B.Eng. in Mechatronics (DHBW Stuttgart) His research spans smart agriculture , quantum NLP , and explainable AI systems , with recent work on vibrotactile warning systems, AI compliance frameworks, and hybrid dataset applications in farming. Publications emphasize interdisciplinary approaches bridging technology and agricultural practice . Scientific honors include: DAAD Stipendium for conference participation Best Paper Award (2018) IEEE GHTC Student Paper Contest Winner (2016) Sonderpreis für gute Lehre (2017) Finalist/Falling Walls Lab (2015)

• Database Management Systems
• Transaction Processing
• In-Memory Databases
• +۶ مورد دیگر

Andrew Pavlo is a Professor in the Computer Science Department at Carnegie Mellon University's School of Computer Science. His research focuses on database management systems, particularly in the areas of transaction processing, in-memory databases, and self-driving database systems. He leads a productive research group that has published extensively in top database venues including VLDB, SIGMOD, and CIDR. Pavlo's research interests span database management systems, transaction processing, in-memory databases, non-volatile memory databases, and self-driving database systems. His work often bridges theoretical database concepts with practical system implementation, focusing on performance optimization, query processing, and system architecture. Recent work has explored machine learning applications for database tuning, novel storage techniques, and innovative approaches to transaction processing. An analysis of his recent publications reveals a strong focus on self-driving database systems, with significant work on the Database Gym framework for training machine learning models to optimize database performance. His research also examines columnar storage formats, transaction scheduling, and novel approaches to user-defined function optimization. The work demonstrates a consistent trajectory toward making database systems more autonomous and efficient through a combination of systems techniques and machine learning. Pavlo has been instrumental in mentoring numerous PhD students who have become active contributors to the database research community. His research has been supported by significant grants that have enabled the development of innovative database technologies and frameworks. His research group operates within CMU's vibrant database ecosystem, collaborating with other researchers on projects related to database systems, storage engines, and query processing frameworks. The group maintains close connections with industry partners to ensure practical relevance of their research contributions.

• Plant Developmental Biology
• Epigenetics
• Plant Genetics
• +۵ مورد دیگر

Ueli Grossniklaus is an Ordinary Professor at the University of Zurich within the Faculty of Mathematical and Natural Sciences , affiliated with the Department of Plant and Microbiology . His work focuses on plant developmental biology, particularly epigenetic and genetic mechanisms governing reproduction and adaptation. Key Courses: Epigenetics, Plant Biology Workshop, Group Seminars on Current Research Laboratory Techniques: Advanced methods in plant cell mechanics, transcriptomics, and genome editing Research Interests span plant epigenetics, reproductive biology, and the interplay between environmental stress and genetic regulation. He investigates: Mechanistic control of gametogenesis and fertilization Epigenetic contributions to plant adaptation Evolutionary implications of asexual reproduction Biophysical forces in plant cell growth Publication Trends (2025–2018) reveal expertise in: Arabidopsis and fern model systems Epigenetic regulation (DNA methylation, histone dynamics) Apomixis and hybrid seed failure mechanisms Biomechanics of pollen tubes and carnivorous plants Genome editing tools (CRISPR) and long-read sequencing Scientific Collaborations include interdisciplinary projects on: Microfluidic devices for plant cell analysis Gene drive ecology and ethics 3D imaging of plant reproductive structures Advising and Grants focus on mentoring through research internships in developmental biology, genetics, and systems biology. His lab engages in: Epigenetic response to environmental stress Cell wall mechanics in reproduction Computational modeling of plant growth Laboratory Teams integrate plant biologists, bioengineers, and computational scientists to study: Mechanistic gene regulation Evolutionary developmental biology Microrobotics for cellular force measurement

Krishnendu Guhaمشاهده پروفایل

استادیار

• Embedded Systems
• Cybersecurity
• Artificial Intelligence
• +۴ مورد دیگر

Dr. Krishnendu Guha is an Assistant Professor and CONNECT Funded Investigator at the School of Computer Science and Information Technology, University College Cork. His research bridges embedded systems, cybersecurity, and quantum-safe hardware design with AI and bio-inspired strategies. PhD: University of Calcutta (Department of Science and Technology, Government of India) Postdoctoral: University of Florida Past Roles: Research Fellow at Intel India, Visiting Scientist at Indian Statistical Institute, Temporary Assistant Professor at NIT Jamshedpur His research focuses on embedded systems security , real-time security mechanisms , and quantum-safe hardware . He integrates AI (e.g., neural networks) and bio-inspired strategies (e.g., gecko crypsis behavior) into security frameworks for FPGAs and edge platforms. Recent publications highlight trends in blockchain for supply chains , quantum machine learning , secure FPGA architectures , and distributed AI systems . His work addresses energy efficiency, fault detection, and decentralized security in hardware. As a CONNECT Centre member, Dr. Guha contributes to advanced research in reconfigurable systems and cybersecurity. Grants and collaborations span quantum-safe design, cloud FPGA security, and hardware trojan mitigation.

Xinran Zhuمشاهده پروفایل

استادیار

• Learning Sciences
• Learning Analytics
• AI in Education
• +۳ مورد دیگر

Xinran Zhu is an Assistant Professor at the University of Illinois Urbana-Champaign College of Education, specializing in Learning Design & Leadership and Instructional Design, Technology, & Organization. Her research intersects learning sciences, learning analytics, and AI in education, focusing on designing technology-supported learning environments for authentic classroom settings. Ph.D. in Learning Sciences and Technologies, University of Pennsylvania (2024) M.A. in Educational Psychology, University of Connecticut Graduate studies in learning technologies, University of Minnesota Her research spans three main areas: (1) design and implementation of educational technologies, particularly social annotation tools for knowledge building; (2) AI integration in education to augment collaborative learning; and (3) computational discourse analysis using network analysis and NLP to generate actionable insights. Recent projects include SynthesisAI , a GenAI-powered chatbot for knowledge synthesis, and the Synthesis Lab , a precursor tool for integrating peer ideas in collaborative writing. Dr. Zhu teaches courses on ubiquitous learning, advanced learning technologies, and eLearning system design. She employs co-design methodologies to develop and implement technologies in both lab and real-world classroom settings, emphasizing student agency and ethical AI partnerships.

Amy Zavatskyمشاهده پروفایل

دانشیار

• Biomechanics
• Orthopaedic Biomechanics
• Gait Analysis
• +۴ مورد دیگر

Amy Zavatsky is a Reader in Engineering Science at the University of Oxford and Tutorial Fellow at St Edmund Hall, with faculty service since 1996. Her work bridges mechanical engineering and clinical orthopaedics, focusing on lower extremity biomechanics and gait analysis within the Department of Engineering Science. Education: BSc in Bioengineering, University of Pennsylvania DPhil in Engineering Science, University of Oxford (Thouron Award recipient) Research Focus: Prof. Zavatsky pioneers orthopaedic biomechanics research with emphasis on foot/ankle kinematics, knee osteoarthritis mechanisms, and gait compensations. Her work integrates theoretical modeling with in vitro experimentation to develop clinical applications for cerebral palsy, flatfoot, and running injuries. Current projects advance multi-segment foot modeling and cognitive-efficient data visualization for clinical gait analysis. Publication Trends: 2021-2025 works reveal three converging themes: (1) Open-source foot modeling ( OpenOFM ), (2) Data visualization for clinical decision-making, and (3) Sensor optimization using statistical methods. These publications consistently bridge engineering innovation with orthopaedic clinical practice through collaborations with the Oxford Gait Laboratory. Scientific Recognition: Philip Leverhulme Prize (2003) for outstanding early-career scholarship University Teaching Award (2008) for biomechanics instruction and MSc Biomedical Engineering development Departmental Teaching Awards: Silver (2021), Bronze (2022) Institution of Mechanical Engineers Thomas Stephen Prize (1993) Academic Leadership: Prof. Zavatsky directs undergraduate engineering tutorials at St Edmund Hall while teaching mechanical/civil/biomedical engineering courses. She previously served as Director of Graduate Studies (2016-17), Acting MSc Biomedical Engineering Director (2006-07), and Junior Proctor (2012-13). Her DPhil supervision targets lower-limb biomechanics projects requiring strong engineering fundamentals. Research Infrastructure: Based at the Institute of Biomedical Engineering (Nuffield Orthopaedic Centre), she collaborates extensively with the Oxford Gait Laboratory. Her biomechanics research group utilizes motion capture systems and multi-segment modeling to translate engineering principles into clinical rehabilitation protocols.

• Medical Imaging
• Deep Learning Applications
• Ultrasound Imaging
• +۳ مورد دیگر

Mehrdad Salehi is a researcher at the Chair of Computer Science Applications in Medicine at the Technical University of Munich (TUM) . His work focuses on the intersection of computer science and medical imaging, with expertise in ultrasound technology, deep learning, and surgical navigation systems. Key research areas include sonification of medical data, 3D ultrasound reconstruction, and machine learning-based segmentation. He has contributed to innovative projects like PRO-TIP calibration phantoms and ColibriDoc autonomous docking systems. His publications highlight trends in acoustic feedback mechanisms, neural radiance fields for medical imaging, and real-time image analysis. He can be reached at mehrdad.salehi@tum.de .

Arie E. Kaufmanمشاهده پروفایل

استاد

• Computer Graphics
• Visualization
• Virtual Reality
• +۴ مورد دیگر

Arie E. Kaufman is a Distinguished Professor in the Department of Computer Science at Stony Brook University, serving as Chief Scientist of the Center of Excellence in Wireless and Information Technology (CEWIT) and Director of the Center of Visual Computing (CVC). He additionally holds a Distinguished Professorship in Radiology, with a 40+ year career at Stony Brook since joining in 1985 and chairing the CS department from 1999-2009. His seminal research spans computer graphics, visualization, and virtual reality with biomedical applications, pioneering breakthroughs including 3D Virtual Colonoscopy (FDA-approved colon cancer screening), Cube hardware architectures (commercialized as VolumePro), the Reality Deck (1.5 billion-pixel immersive display), and foundational work in volume visualization. His interests focus on real-time rendering, medical imaging, and immersive analytics, with recent work integrating machine learning for healthcare and environmental risk visualization. Recent publications demonstrate continued leadership in high-resolution immersive displays (Silo), XR analytics with LLMs, storm surge visualization, and neural reconstruction techniques. His work bridges theoretical innovation with practical applications, particularly in pancreatic cancer prognosis and disaster preparedness. Major honors include: IEEE Visualization Career Award (2005) Fellow of the National Academy of Inventors (2017) ACM Fellow (2009) IEEE Fellow (1998) Long Island Technology Hall of Fame (2013) European Academy of Sciences membership (2002) As PI on 100+ research grants, Kaufman's work has generated 300+ refereed papers, 40+ patents, and extensive media coverage (New York Times, Science, Wall Street Journal). He leads the Center of Visual Computing with focus on translational research, including VolVis software (5,000+ installations) and Reality Deck deployments for big data analytics. His lab develops cutting-edge visualization infrastructure for medical diagnostics and environmental modeling, with current projects advancing immersive storm surge analytics, neural structure extraction, and VR-based risk communication systems. Future work emphasizes AI-enhanced visualization for precision medicine and climate resilience planning.

Jacob Gardnerمشاهده پروفایل

استادیار

• Machine Learning
• Bayesian Optimization
• Computational Biology
• +۳ مورد دیگر

Jacob Gardner is an Assistant Professor in the Department of Computer & Information Science at the School of Engineering and Applied Science, University of Pennsylvania. His research bridges machine learning and scientific discovery with emphasis on computational biology and molecular design. His primary research interests include: Machine Learning Bayesian Optimization Computational Biology Molecular Design Artificial Intelligence Gaussian Processes Analysis of his 2024-2025 publications reveals a dominant focus on Bayesian optimization techniques integrated with large language models for biological applications. Key trends include therapeutic design using knowledge distillation from scientific literature, RNA splicing prediction, antibiotic development, and scalable Gaussian process methods. His work consistently addresses dimensionality challenges in molecular modeling while improving computational efficiency for high-dimensional biological data. No scientific awards were mentioned in the provided text. No information regarding student advising or research grants was provided in the source material. His research appears supported by institutional initiatives including Penn AI, Innovation in Data Engineering and Science (IDEAS), and the Data Driven Discovery Initiative (DDDI).

Facundo M. Fernandezمشاهده پروفایل

استاد

• Analytical Chemistry
• Bioanalytical Mass Spectrometry
• Ambient Sampling/Ionization
• +۴ مورد دیگر

Facundo M. Fernandez is a Regents' Professor and Vasser-Woolley Chair in Bioanalytical Chemistry at the Georgia Institute of Technology, where he leads the Fernandez Research Group within the School of Chemistry and Biochemistry in the College of Sciences. His research spans multiple cutting-edge areas of analytical chemistry with significant applications in medicine, forensics, and basic science. Dr. Fernandez earned his M.Sc. in Chemistry (1996) and Ph.D. in Analytical Spectrometry/Metallomics (1999) from the Facultad de Ciencias Exactas y Naturales at Buenos Aires University, Argentina. His research program focuses on Bioanalytical Mass Spectrometry with particular emphasis on Ambient Sampling/Ionization & Molecular Imaging, Ion Mobility Spectrometry, Metabolomics, and Pharmaceutical Forensics. His work has pioneered new approaches in ambient ionization techniques that enable direct analysis of complex samples without extensive preparation. His recent publications reveal a strong trend toward spatial metabolomics, particularly in traumatic brain injury and ovarian cancer research, with increasing integration of machine learning approaches for data analysis. His work also extends to pharmaceutical quality control, exercise physiology through the MoTrPAC consortium, and prebiotic chemistry investigations. The interdisciplinary nature of his research is evident in collaborations across Georgia Tech's campus and with external institutions. NSF CAREER Award (2007) 3M Non-tenured Faculty Award (2008) CETL/BP Junior Faculty Teaching Excellence Award (2009) Ron A. Hites Award for Outstanding Research Publication (2010) Sigma Xi (GT Chapter) Best Faculty Paper Award (2010) Vasser-Wooley Faculty Fellow (2012) Dr. Fernandez has secured significant funding for his research, including NSF CAREER support, and leads projects related to metabolomics for ovarian cancer detection, pharmaceutical forensics through the CODFIN network, and participation in the large-scale Molecular Transducers of Physical Activity Consortium (MoTrPAC). His laboratory develops advanced instrumentation for mass spectrometry applications and maintains strong collaborations with the Integrated Cancer Research Center, the College of Computing, and the Center for Chemical Evolution at Georgia Tech.