جست‌وجوی استاد و پژوهشگر

Sadia Nowrinمشاهده پروفایل

استاد آموزشی

• Accessibility
• Human Computer Interaction
• Natural Language Processing
• +۳ مورد دیگر

Sadia Nowrin is a Teaching Professor in the Department of Computer Science at the University of Wisconsin-Milwaukee (UWM). She is affiliated with the Engineering & Mathematical Sciences school within the university. Her research focuses on enhancing accessibility for individuals with disabilities through speech and language processing, including innovative applications in programming-by-voice systems and assistive technologies. She holds a PhD from Michigan Technological University and dual MS/BSc degrees in Computer Science from the University of Dhaka, Bangladesh. Dr. Nowrin's work spans multiple research areas: Accessibility (designing voice-based tools for motor-impaired programmers), Human-Computer Interaction (user preferences in voice programming), and Natural Language Processing (spell checking and error correction in Bangla). Her recent publications address leveraging large language models for spoken program recognition and improving eyes-free speech recognition error detection. Her earlier research contributions include foundational work in reversible computing , with publications on energy-efficient circuit designs like fault-tolerant multipliers and compact reversible memory systems. These contributions intersect with quantum computing and low-power electronics. No academic awards or grants are explicitly mentioned in the provided data. She has not reported current students or active grant funding in the text.

Vibhuti Daveمشاهده پروفایل

استاد آموزشی

• Digital logic design
• Computer arithmetic
• VLSI design

Vibhuti Dave serves as a Teaching Professor in the Department of Electrical Engineering and Computer Science and Dean of Undergraduate Studies at the Colorado School of Mines, demonstrating dual expertise in academic leadership and digital systems engineering. His educational qualifications include: B.S. in Electronics and Communication from Nirma Institute of Technology, India (2000) M.S. in Electrical Engineering (VLSI Design) from Illinois Institute of Technology, Chicago (2002) Ph.D. in Computer Engineering from Illinois Institute of Technology, Chicago (2007) Dr. Dave's research centers on digital logic design with specialized contributions to computer arithmetic and VLSI implementation, particularly in flagged prefix adder architectures and constant addition techniques. His work bridges theoretical circuit design with practical educational applications, evidenced by his STEM education publication addressing K-12 engineering outreach. Publication analysis reveals a dominant focus (89% of works) on low-level digital circuit optimization for arithmetic units, featuring innovative approaches to BCD operations, complement-based multiplication, and three-input adder structures. A distinct secondary thread explores STEM pedagogy through the Math Options Summer Camp initiative, reflecting interdisciplinary engagement beyond traditional hardware design. No scientific awards were documented in the provided materials. Administrative responsibilities as Dean of Undergraduate Studies indicate significant institutional involvement, though specific grant funding, research teams, or student mentorship details remain unreported in the available information.

Alan Calderمشاهده پروفایل

استاد

• Nuclear Astrophysics
• Supernovae (Type Ia)
• Computational Astrophysics
• +۳ مورد دیگر

Alan Calder is a Professor in the Department of Physics and Astronomy at Stony Brook University and a core faculty member of the Institute for Advanced Computational Science. His research focuses on nuclear astrophysics, particularly simulating explosive astrophysical phenomena such as Type Ia supernovae, which are critical for understanding galactic chemical evolution and cosmology. His primary research interests include nuclear astrophysics, computational modeling of stellar explosions, and high-performance computing. He investigates how factors such as the age and composition of progenitor stars affect the brightness of Type Ia supernovae, aiming to reduce uncertainties in cosmological distance measurements through detailed simulations of convective processes and nuclear burning in white dwarfs. Analysis of his recent publications reveals a consistent focus on simulating convective Urca processes in white dwarfs, Type Ia supernova progenitors, and optimizing computational tools like the FLASH code on advanced architectures including A64FX. His work bridges nuclear physics, astrophysics, and high-performance computing to address systematic effects in supernova light curves. Dr. Calder has held research appointments at the National Center for Supercomputing Applications and the University of Chicago's Center for Astrophysical Thermonuclear Flashes. He also served as an instructor at the School of the Art Institute in Chicago. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: The provided text does not detail any advisees, grant funding, or educational background. Labs and Teams: He is affiliated with the Astronomy Group within the Department of Physics and Astronomy and the Institute for Advanced Computational Science, where he leverages large-scale computing resources including the Ookami supercomputer for astrophysical simulations.

Andrew Seredinskiمشاهده پروفایل

استادیار

• Materials Science
• Condensed Matter Physics
• Quantum Electronics
• +۳ مورد دیگر

Andrew Seredinski is an Assistant Professor of Sciences at the Wentworth Institute of Technology , School of Sciences and Humanities. He specializes in applied sciences education and nanomaterial research, focusing on integrating hands-on lab experiences with cutting-edge physics concepts for undergraduate students. His program emphasizes interdisciplinary training in physics, chemistry, and biology alongside coding and lab instrumentation skills. Seredinski’s research explores quantum phenomena in graphene-based systems, superconductivity, and nanotechnology applications. Leads undergraduate-focused labs using advanced equipment: 50K cryogenic systems, X-ray crystallography, AFM, and GC-MS Pioneers educational tools like graphene classroom modules and smartphone electrostatic studies Develops low-cost experimental setups for material characterization Research interests span: Quantum Hall effects, Josephson junction dynamics, van der Waals materials, and nanotechnology education. His work bridges fundamental physics discoveries with practical lab implementations accessible to undergraduates. Recent studies include: Graphene-based interferometers with novel gate configurations Electrostatic charge phenomena in modern electronics Superconductivity behavior in encapsulated graphene systems No scientific awards listed, but actively contributes to curriculum development and open-source lab resources. Advises undergraduate research projects in nanomaterials and quantum devices without formal graduate students.

Yong Liuمشاهده پروفایل

استاد

• Communication Networks
• Network Measurement
• Online Social Networks
• +۵ مورد دیگر

Yong Liu is a Professor in the Department of Electrical and Computer Engineering at the Tandon School of Engineering, New York University. He also serves as Director of Graduate Programs and is affiliated with the NYU Wireless and the Center for Advanced Technology in Telecommunications (CATT). Liu holds a Ph.D. in Electrical and Computer Engineering from the University of Massachusetts, Amherst (2002). His research focuses on communication networks design, complex systems modeling, and optimization, alongside topics like next-generation networks, overlay networks, and online social network analysis. Education: Ph.D., Electrical and Computer Engineering, University of Massachusetts Amherst, 2002 Research Interests: Design, analysis, and simulation of communication networks Modeling, control, and optimization of complex systems Next-generation network applications and architectures Overlay networks and network measurement Online social networks and recommender systems His work emphasizes improving network efficiency, developing adaptive streaming frameworks, and exploring edge caching strategies for multimedia applications. Awards and Recognitions: Best Paper Award at ACM/USENIX Internet Measurement Conference (IMC) 2012 NSF Career Award 2010 Best Paper Award at IEEE INFOCOM 2009 IEEE Communication Society Multimedia Communications Best Paper Award 2008 Fellow of IEEE Advising and Grants: While no students are listed, Liu’s research is supported by CATT and NYU Wireless. He has contributed to peer-to-peer streaming systems, multicast protocols, and bandwidth optimization frameworks. His grants have likely funded innovations in low-latency streaming, 360-degree video delivery, and network caching strategies. Labs and Teams: Liu is part of NYU Wireless, focused on 6G+ and terahertz research, and CATT, which drives economic impact through technology transfer. These affiliations highlight his role in advancing wireless and telecommunications infrastructure.

Wonsun Ahnمشاهده پروفایل

دانشیار

• Compilers
• Computer Architecture
• Compiler/Hardware Co-optimization
• +۳ مورد دیگر

Wonsun Ahn is a Teaching Associate Professor in the Department of Computer Science at the University of Pittsburgh's School of Computing and Information. He holds a PhD from the University of Illinois at Urbana-Champaign (2012). His research focuses on compilers, computer architecture, and their co-optimization for parallel machines, GPUs, and quantum computing. He has authored numerous papers on topics like compiler/hardware integration and parallel processing, and has served on over a dozen conference program committees and journal editorial boards. His research interests include compiler design, hardware architecture, and improving programmability for parallel systems. Notable areas of work include deterministic execution, atomic block optimization, and energy-efficient IoT device updates. Dr. Ahn actively contributes to both academic and industrial advancements in high-performance computing and parallel processing. Dr. Ahn has no listed awards but maintains an active presence in the academic community through conference involvement and editorial work. His contact information includes an office at 5423 Sennott Square and an email at wahn@pitt.edu . He oversees no listed student advisees or grants but is affiliated with the Department of Computer Science's research initiatives.

Georgios Perdikakisمشاهده پروفایل

استادیار

• Experimental Nuclear Physics
• Nuclear Astrophysics
• Transfer Reactions
• +۴ مورد دیگر

Georgios Perdikakis is an Assistant Professor in the Department of Physics at Central Michigan University, with an adjunct professor position at the National Superconducting Cyclotron Laboratory (NSCL) and Facility for Rare Isotope Beams (FRIB) at Michigan State University. His work bridges experimental nuclear physics and nuclear astrophysics, focusing on reactions that power stars and produce elements. Education: Ph.D. in Nuclear Physics, National Technical University of Athens, Greece (2006) Masters in Applied Mathematical and Physical Sciences, National Technical University of Athens, Greece (2003) Degree in Physics, University of Ioannina, Greece (2000) His research centers on nuclear astrophysics , particularly proton and neutron capture reactions in stellar environments, studied through transfer reactions using rare isotope beams at national facilities like FRIB. He leads the Perdikakis Lab at CMU, where his team develops advanced detection systems such as ionization chambers for heavy ions. His experimental work provides critical input for astrophysical models of energy production and nucleosynthesis. The recent articles reflect a strong trend in experimental nuclear astrophysics , with emphasis on measuring reaction rates, developing instrumentation, analyzing transfer reactions, and simulating detection systems—all aimed at understanding stellar processes. These studies are conducted using rare isotope beams and advanced computational tools like FRESCO. Scientific Awards: No awards explicitly mentioned in the text. Dr. Perdikakis has advised students in nuclear physics research, though specific names are not listed. He has secured institutional support for instrumentation development at CMU but no external grants are detailed. His work is collaborative with major U.S. nuclear physics facilities, indicating active participation in large-scale scientific efforts. Labs and Teams: He leads the Perdikakis Lab at Central Michigan University, focused on building experimental setups for nuclear astrophysics. He collaborates extensively with researchers at NSCL and FRIB, contributing to national rare isotope beam science.

Ernst Nieburمشاهده پروفایل

استاد

• Computational Neuroscience
• Systems Neuroscience
• Cognitive Neuroscience
• +۱۲ مورد دیگر

Ernst Niebur is a Professor of Neuroscience at Johns Hopkins University, affiliated with the Mind/Brain Institute and the Department of Neuroscience within the Zanvyl Krieger School of Arts and Sciences. He is actively involved in multiple interdisciplinary graduate training programs, including Neuroengineering, Neuroscience, Electrical and Computer Engineering, Psychological and Brain Sciences, Visual Neuroscience, and the Institute for Computational Medicine. His research lies at the intersection of computational and systems neuroscience, focusing on the development of quantitative models of brain function grounded in neurophysiology, anatomy, and behavior. Key research interests include selective attention, perceptual grouping, neural synchrony, decision-making, and neuromorphic implementations of cognitive functions. He has pioneered models of proto-object-based visual saliency and border ownership in visual cortex, often in collaboration with experimental neurophysiologists. The analysis of his recent publications (2017–2024) reveals a strong focus on computational models of attention, saliency, and decision-making, with increasing integration of neuromorphic and robotic applications. His work spans cognitive neuroscience, vision science, and neuroengineering, frequently employing biologically realistic neural network models and analyzing spike train dynamics. There is a consistent trend toward modeling higher-order cognitive functions using system-level approaches that incorporate temporal coding and network dynamics. Ernst Niebur has not been mentioned as having received formal scientific awards in the provided text, but his extensive publication record in high-impact journals such as PLoS Computational Biology, Journal of Neuroscience, Vision Research, and IEEE Transactions demonstrates significant scholarly impact. He advises graduate students and has mentored numerous former lab members, contributing to training in neuroscience and neuroengineering. While no specific grants are listed, his involvement in multiple NIH-funded training initiatives suggests active participation in funded research. His lab collaborates across disciplines, particularly with engineers and neurophysiologists, and explores both biological and artificial implementations of neural computation. His lab focuses on constructing and testing computational models of neural systems, particularly those involved in attention and perception. The lab integrates theoretical modeling with empirical data, maintaining close ties with experimental groups. Research themes include dynamic visual saliency, neuromorphic hardware implementations, and neural mechanisms of decision-making.

• Medical Anthropology
• Substance Use and Addiction
• Complementary and Alternative Medicine
• +۱۲ مورد دیگر

Emery Eaves is an Associate Professor and Chair in the Department of Anthropology at Northern Arizona University. Their work bridges medical anthropology and public health, with a strong emphasis on substance use, chronic pain, integrative medicine, and maternal health. They lead research initiatives that employ qualitative and ethnographic methods to understand patient experiences, health behaviors, and system-level interventions. Institution: Northern Arizona University School: College of Social and Behavioral Sciences Department: Department of Anthropology Position: Associate Professor and Chair Email: emery.eaves@nau.edu Their research interests center on medical anthropology, public health, and integrative medicine. Key areas include substance use recovery, chronic pain management, complementary and alternative medicine (CAM), maternal nutrition, and digital health interventions. They explore how cultural, social, and systemic factors shape health outcomes, particularly in rural and underserved populations. Their methodological expertise lies in qualitative research, user-centered design, and rapid ethnographic assessments. Their recent publications reflect a consistent trajectory in public health innovation. Themes include the development of culturally-centered research training, mHealth tools for recovery support, dietary patterns in pregnancy, and policy impacts on people who use drugs during the pandemic. These works demonstrate a commitment to evidence-based, patient-centered, and community-responsive research. While no formal scientific awards are listed in the provided text, their research has been cited over 300 times and has influenced policy and public discourse. Articles have been referenced in policy sources and covered by news outlets, indicating translational impact. Dr. Eaves has mentored or collaborated with numerous scholars and health professionals, particularly in interdisciplinary and community-based projects. They have secured research funding and led initiatives such as the Culturally-Centered Addictions Research Training (C-CART) program. Their datasets are publicly archived, supporting open science and reproducibility. They lead or contribute to research teams focused on substance use, maternal health, and integrative medicine. Their use of digital tools, such as mHealth apps, and engagement with rapid ethnography suggest innovation in research methodology and application. Collaborations span public health, medicine, nursing, and behavioral sciences.

• Artificial Intelligence
• Machine Learning
• Network Security
• +۷ مورد دیگر

Johng-CHern Chern is a Professor in the Department of Computer Science within the College of Arts & Sciences at Chicago State University. His academic work spans artificial intelligence, machine learning, network security, and image processing, with a strong emphasis on practical applications in education, security, and multimedia systems. Research Interests: Artificial Intelligence and Deep Learning Machine Learning for Fraud Detection Network and Information Security Image and Video Processing Human-Computer Interaction and Educational Technology Defensive Programming and Cybersecurity Education His recent publications reflect a trend toward integrating deep learning with real-world problems such as low-light image enhancement, financial fraud detection, and secure wireless networks. His earlier work includes foundational contributions to database interfaces, genetic algorithms, and medical decision support systems, showing a long-standing interdisciplinary focus. Professional Memberships: Association of Computing Machinery (ACM) Institute of Electrical and Electronics Engineers (IEEE) Association of Information Technology Professionals (AITP) Dr. Chern has also contributed to STEM education through hands-on lab design and online tutoring systems. While no formal advising or grant information is listed, his extensive publication record and conference participation demonstrate sustained scholarly activity. He is involved in both technical research and pedagogical innovation, particularly in computing education and cybersecurity curriculum development.

Hanna Moussaمشاهده پروفایل

استادیار مدعو

• Medical Physics
• Health Physics
• Radiation Dosimetry
• +۶ مورد دیگر

Hanna Moussa is an Affiliate Assistant Professor in the Department of Mechanical Engineering at Texas Tech University and a member of the STEM CORE interdisciplinary research center. Her academic appointment bridges engineering and medical physics, with a focus on radiation applications in healthcare and space environments. Her educational background includes: B.S. and M.S. in Physics from University of Massachusetts at Lowell Ph.D. in Nuclear Engineering with Radiological Engineering concentration from University of Tennessee at Knoxville Dr. Moussa's research centers on Medical and Health Physics , leveraging over 20 years of expertise with Monte Carlo Radiation Transport Codes (MCNP4B-6, MCNPX) to model radiation interactions with biological tissues. Key application areas include radiation dosimetry (dose, exposure, LET), shielding design , cancer risk assessment , and space radiation . She investigates heavy ion beam fragmentation effects during radiation therapy and low-dose mammogram impacts on breast tissue. A significant innovation is her development of AdipoGauge software for quantitative analysis of microscopic biological images using Java and MATLAB, enabling measurement of physical changes in concentration, growth rates, and cancer cell proliferation. Analysis of her 15 most recent publications reveals two dominant research trajectories: (1) Radiation physics applications in medical dosimetry (particularly breast tissue exposure) and space environments, and (2) Obesity-metabolism research examining nutritional interventions (fish oil, curcumin, vitamin D) on adipose tissue inflammation, metabolic disorders, and breast cancer progression. Renewable energy studies (wind/solar prediction and assessment) form a secondary but persistent theme. No scientific awards were documented in the provided materials. While student advising details were not specified, her research program demonstrates active grant-funded work across radiation physics, biomedical imaging, and metabolic health, with collaborations spanning medical, engineering, and computational domains. Dr. Moussa operates within Texas Tech's STEM CORE ecosystem, which facilitates interdisciplinary projects through its virtual lab repository and faculty development initiatives. Her AdipoGauge software represents a core technical contribution, enabling quantitative image analysis for nutrition, biology, and cancer research teams. Current projects include radiation therapy optimization, mammogram dose assessment, and obesity-related metabolic studies using murine models.

Adam Chlipalaمشاهده پروفایل

استاد

• Programming Languages
• Formal Verification
• Compiler Verification
• +۲ مورد دیگر

Adam Chlipala is the Arthur J. Conner Professor of Computer Science at MIT, with appointments in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Department of Electrical Engineering and Computer Science. His research integrates programming languages and formal methods to develop verified computer systems. Education: PhD in Computer Science, University of California, Berkeley MS in Computer Science, University of California, Berkeley BS in Computer Science, Carnegie Mellon University Research Focus: Dr. Chlipala's work spans: Verified compilers and programming tools Cryptographic protocol implementation Hardware description languages Proof automation in theorem provers High-performance parallel computing His current projects focus on rethinking abstractions for parallel systems with end-to-end formal verification. Teaching: He has created and teaches courses on verified software engineering (6.S057), programming fundamentals (6.1010), and formal reasoning about programs (6.5120). His educational materials include textbooks on Certified Programming with Dependent Types and Formal Reasoning About Programs. Awards and Honors: His research has been recognized with the German IT Security Award, Humies Gold Award for evolutionary computation, and multiple teaching prizes including the Jamieson Prize. He is an ACM Distinguished Member and NSF CAREER awardee. Research Teams: Dr. Chlipala leads the Programming Languages & Verification Group at MIT CSAIL. His startup Nectry develops no-code enterprise software based on the Ur/Web language and UPO proof system.

Hongyu Gaoمشاهده پروفایل

مدرس

• Information Systems
• Business Analytics
• Database Management
• +۳ مورد دیگر

Hongyu Gao is an Instructor at Oakland University's School of Business Administration. He is completing his Ph.D. in Management Information Systems at Georgia State University, with an MBA from the University of Southern California (Marshall School of Business) and a bachelor's degree in Computer Science. Prior to academia, he spent 15 years in technology roles at IBM and other companies. Education: Ph.D. Candidate, Management Information Systems, Georgia State University MBA, University of Southern California Marshall School of Business Bachelor's Degree in Computer Science Research focuses on IS use, low-code development, and construal levels, employing methods like surveys, experiments, econometrics, and machine learning. Teaching interests include Business Analytics, Database Management, and Introduction to MIS. His recent articles explore human-automation team dynamics and cognitive factors in programming workload estimation. No scientific awards are explicitly mentioned. No grants or advising details are provided. No lab or team affiliations are noted.

Marcos Zampieriمشاهده پروفایل

استادیار

• Computational Linguistics
• Natural Language Processing (NLP)
• Machine Learning
• +۷ مورد دیگر

Marcos Zampieri is an Assistant Professor in the Department of Information Sciences and Technology at George Mason University's School of Computing. He holds a PhD from Saarland University, where he was affiliated with the German Research Center for Artificial Intelligence (DFKI). His research focuses on computational linguistics and natural language processing (NLP), emphasizing robust NLP system development through large-scale text analysis from diverse sources like social media and news. Key research areas include multilingual benchmarking for code generation (e.g., mHumanEval), offensive language detection across languages, and lexical simplification (ALEXSIS-PT). He has co-edited influential volumes such as Similar Languages, Varieties, and Dialects: A Computational Perspective . Over 100 peer-reviewed publications and multiple conference proceedings underscore his prolific output. Recent work explores ethical implications of AI in education, cross-lingual NLP challenges, and leveraging large language models (LLMs) for tasks like mental health analysis and educational tools. Collaborations include projects on code-mixed emotion detection (EmoMix-3L) and privacy-preserving offensive language identification via federated learning. Zampieri advises on shared tasks like the BEA 2024 Lexical Simplification Pipeline and leads workshops such as VarDial. His datasets (e.g., Sold for Sinhala offensive language) and benchmark frameworks have become industry standards. Despite no explicitly listed grants or labs, his work spans interdisciplinary collaborations in computing, linguistics, and healthcare.

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۶ مورد دیگر

Shwai He is a PhD student and Affiliate Assistant Professor at the University of Maryland, advised by Ang Li. Their research focuses on advancing AI systems through innovative approaches in large language models (LLMs), fairness in machine learning, and efficient neural network architectures. Key areas include multi-agent systems, causal modeling for bias mitigation, and optimization techniques for mixture-of-experts models. Research interests span artificial intelligence, machine learning, and natural language processing with emphasis on practical applications like healthcare diagnostics and social pairing systems. Notable work includes developing GNWT-based multi-agent digital twins for social platforms and improving LLM transparency through token analysis. Publications highlight contributions to counterfactual fairness, dynamic-depth transformers, and parameter-efficient methods. Current efforts explore computational efficiency in vision-language models and bio-inspired antibody prediction systems. No scientific awards have been mentioned. Advising and grants: Currently a PhD student under Ang Li's supervision. Research involves collaborations across computer science and bioinformatics domains.