جست‌وجوی استاد و پژوهشگر

Chongzhi Zangمشاهده پروفایل

دانشیار

• Computational Biology
• Cancer Genomics
• Epigenetics
• +۷ مورد دیگر

Chongzhi Zang is an Associate Professor at the University of Virginia School of Medicine with primary appointment in the Department of Genome Sciences (formerly Center for Public Health Genomics). He holds additional faculty appointments in the Departments of Public Health Sciences, Biomedical Engineering, and Biochemistry and Molecular Genetics. Dr. Zang is also a faculty member in the UVA Cancer Center and the Data Science Institute, where he serves as the inaugural Director of Computational Genomics. His educational background includes a B.S. in Physics from Peking University (2005), a Ph.D. in Physics from The George Washington University (2010), and postdoctoral training in Computational Biology at Harvard University (2016). Dr. Zang's research focuses on computational biology and functional genomics, with particular expertise in cancer epigenomics. His lab develops computational methods and data science approaches to study how genes work in chromatin and how they dysfunction in diseases like cancer. Key research areas include algorithm development for high-throughput genomic data analytics, integrative modeling of gene regulatory networks, and analysis of chromatin architecture in mammalian cell systems. His recent publications demonstrate significant contributions to understanding transcriptional regulation, phase-separated condensates, chromatin accessibility analysis, and computational methods for single-cell multiomics data. The research shows a strong trend toward developing innovative computational tools that bridge molecular biology and data science to address fundamental questions in gene regulation and cancer biology. University of Virginia Research Excellence Award (2020) NIGMS Maximizing Investigators' Research Award (MIRA) (2019-2024) NCI Career Transition Award (2017-2020) Leukemia and Lymphoma Society Fellow Award (2012-2015) Dimitris N. Chorafas Foundation Prize (2010) School of Medicine Dean's Award for Excellence in Research (2024) Vivian Pinn Scholar by UVA School of Medicine (2024) Dr. Zang actively mentors a large research team including postdoctoral associates, graduate students, and undergraduates. His lab has secured substantial grant funding including NIH R35 MIRA, R21, and R01 grants, as well as pilot funding from the UVA Cancer Center. He has developed several widely-used computational tools including BART (Binding Analysis for Regulation of Transcription), BARTweb, BART3D, and IGN normalization methods that are used by researchers worldwide. The Zang Lab for Computational Biology and Functional Genomics is located in the Medical Center's West Complex and maintains active collaborations across UVA and with external institutions. The lab is highly productive with numerous publications in top journals including Nature, Nature Genetics, and Nature Immunology, and has developed significant expertise in single-cell genomics, chromatin architecture analysis, and computational methods for cancer genomics.

• Marketing
• Consumer Behavior
• Organizational Behavior
• +۷ مورد دیگر

Anthony Patterson is a Professor of Marketing at Lancaster University Management School (LUMS), part of Lancaster University. His research focuses on critical marketing theory, employing literary theory, post-structuralism, and practice theory to explore themes like hauntology, technocapitalism, and work-family dynamics. He has published in top journals such as Journal of Consumer Research and Journal of Service Research . Recent work emphasizes improving well-being and organizational inclusion for working parents. Patterson leads projects funded by the ESRC, including initiatives on flexible working policies and family-friendly organizational practices. His research groups include the Academy for Gender and Social Justice and the Centre for Consumption Insights . Key activities include keynote speeches on radical research writing and academic challenges, as well as external PhD examinations at institutions like the University of Galway and Warwick. Patterson advises PhD student Xiaoxi Ding and collaborates on interdisciplinary projects addressing societal issues through a marketing lens. Publications span topics from self-tracking technologies to brand resurrection, reflecting his interdisciplinary approach. His work bridges marketing theory with real-world applications in areas like sustainability, gender equity, and pandemic-era labor dynamics.

• Material discovery and design
• Density functional theory
• Artificial intelligence
• +۱۲ مورد دیگر

Dr Sherif Abbas is a Research Fellow at the Applied Artificial Intelligence Institute (A2I2) within Deakin University, Australia. Since 2021 he has held this role after being awarded the competitive Alfred Deakin Postdoctoral Research Fellowship at the Institute for Frontier Materials. His work is positioned at the intersection of material science, physics, chemistry and artificial intelligence, leveraging cutting-edge AI methodologies to solve complex challenges in energy storage, sensing and computational materials discovery. Education PhD in Physics, University of Sydney (2017) Research Interests Abbas’s research focuses on the accelerated discovery and rational design of advanced functional materials through the synergistic use of density-functional theory (DFT) and state-of-the-art machine-learning techniques. Specific thrusts include: Rechargeable battery chemistries (Li-ion, solid-state, Al-rich cathodes) Solar-energy-harvesting and photovoltaic materials Supercapacitor and superionic conductor design Gas-sensing surfaces and CO₂-capture frameworks Superconducting, ferroelectric and multiferroic compounds 2D van der Waals heterostructures and their optoelectronic applications His methodological toolkit spans Bayesian optimisation, generative models, graph neural networks and physics-informed machine-learning potentials that enable multiscale simulation from the atomic level to device performance. Publication Trends Across 103 outputs (2019–2025), Abbas demonstrates a clear trajectory toward physics-informed AI for materials. There is a marked concentration on energy-storage interfaces (solid-state electrolytes, dendrite suppression) and on low-dimensional systems where quantum confinement and van der Waals interactions govern functionality. Recent work increasingly couples rigorous first-principles data with scalable ML surrogates, underscoring a shift from static property prediction to dynamic, device-relevant simulations. Scientific Awards & Fellowships Alfred Deakin Postdoctoral Research Fellowship (Deakin University, 2021–present) Doctoral Supervision & Funding Abbas currently co-supervises two doctoral candidates: Thuy Linh La: "Enhancing Scalability of Machine Learning Models for Material Simulation" Hajer Abdulhafid Mohamed Derbi: "Applied Artificial Intelligence in Dental Field" Both projects are embedded within Deakin’s Applied Artificial Intelligence Initiative and benefit from internal fellowship funds and external ARC linkage grants coordinated by A2I2. Laboratory & Entrepreneurial Activities He is an integral member of the cross-disciplinary teams at A2I2, collaborating closely with the Institute for Frontier Materials and external partners across Australia. In parallel, he founded mathpractice.xyz (2023–present), an educational technology venture aimed at democratising advanced mathematics and AI training resources for students and early-career researchers.

Reinoud Lavrijsenمشاهده پروفایل

دانشیار

• Nanomagnetism
• Spintronics
• Energy-Efficient Electronics
• +۳ مورد دیگر

Reinoud Lavrijsen is an Associate Professor in the Department of Applied Physics at Eindhoven University of Technology (TU/e). He holds a PhD and MSc from TU/e and has conducted postdoctoral research at the University of Cambridge. His work focuses on nanomagnetism, spintronics, and energy-efficient magnetic devices, particularly in controlling magnetization dynamics without external magnetic fields. He leads research on synthetic multiferroic heterostructures and all-optical switching in Co/Gd-based systems. Affiliations: TU/e (Department of Applied Physics), ICMS Affiliated Member, Center for Care & Cure Technology. Education: PhD and MSc in Applied Physics (TU/e), Postdoctoral Research (University of Cambridge Cavendish Laboratory). His research explores novel materials and device architectures for low-power electronics, including magnetic racetrack memories and magneto-photonic integration. Lavrijsen has authored over 150 publications and secured prestigious grants like NWO Rubicon and Veni awards. He actively participates in international conferences and serves as a referee for journals like Nature Communications and Physical Review Letters . Awards: Best Teacher Master 2021 (TU/e) Teacher of the Year 2022 (National) NWO Rubicon Award (2010) NWO Veni Award (2012) Current Projects: Leading the Black Holes on a Chip project (2021–2027), exploring quantum phenomena in nanomagnetic systems. He also supervises 53 graduate students and teaches courses like Nanomagnetism and Nanospintronics . Labs/Teams: Active in the Physics of Nanostructures group and collaborates internationally on spintronics and materials science.

Bart Dhoedtمشاهده پروفایل

استاد

• Distributed Machine Learning
• Edge Computing
• Neuromorphic Computing
• +۲ مورد دیگر

Bart Dhoedt is a Professor at Ghent University's Department of Information Technology, affiliated with the Internet Technology and Data Science Lab (IDLab). He teaches courses on algorithms, advanced programming, software development, and distributed systems. His research bridges distributed machine learning, edge computing, and hardware-efficient AI. Research interests focus on Distributed Machine Learning (parallel processing across systems), Edge Computing (decentralized data processing), Neuromorphic Computing (brain-inspired hardware), Sensor Fusion (multimodal data integration), and Representation Learning (efficient feature extraction). Recent publications emphasize active inference, robotic navigation, and object-centric AI. Publications (2017-present) show strong trends in robotic autonomy (navigation, manipulation), active inference (Bayesian modeling), and multimodal world models , with applications in industrial automation and cognitive systems. No awards or grants are documented. He leads research at IDLab, collaborating on embedded AI and distributed systems. No advised students or external affiliations are mentioned.

Yuki Okaمشاهده پروفایل

استاد

• Neuroscience
• Neural Circuits
• Homeostasis
• +۳ مورد دیگر

Yuki Oka is a Professor of Biology at the California Institute of Technology (Caltech) and an Investigator at the Heritage Medical Research Institute (HMRI). They hold a B.A. from the University of Tokyo (2002) and a Ph.D. (2007). Oka joined Caltech as an Assistant Professor in 2014, becoming a full Professor in 2020. They were a Chen Scholar (2019–2022) and have been an HMRI Investigator since 2021. Research focuses on the neural and molecular mechanisms underlying homeostatic regulation, particularly how the brain integrates internal body states and external sensory inputs to maintain fluid balance. Key areas include thirst regulation, sodium appetite, and gut-brain communication. Techniques employed include genetics, optogenetics, and single-cell RNA sequencing to dissect neural circuits and molecular pathways. Recent work highlights discoveries in organ-specific sympathetic innervation, neural pathways for sodium consumption, and improved single-cell RNA sequencing methods. The lab investigates brain regions like the lamina terminalis and hindbrain structures, exploring interactions between water and sodium appetite circuits. Media recognition includes coverage in The New York Times and NPR for studies on thirst mechanisms. Oka’s research bridges fundamental neuroscience with implications for understanding disorders related to fluid and electrolyte imbalance.

• Criminology
• Virtual Reality Applications
• Offender Decision-Making
• +۵ مورد دیگر

Jean-Louis van Gelder is a Director at the Max Planck Institute for the Study of Crime, Security and Law (Freiburg, Germany) and a Full Professor at the Institute of Education and Child Studies, Leiden University (Netherlands). His work bridges criminology, psychology, and technology to study offender decision-making and develop behavioral interventions. Education: PhD (Psychology, VU University Amsterdam) PhD (Law, University of Amsterdam) M.A. (Law, University of Amsterdam) M.A. (Psychology, University of Amsterdam) Research Focus: Van Gelder explores how short-term mindsets , peer dynamics , and harsh environments influence criminal behavior. He pioneers the use of virtual reality (VR) and 360º immersive scenarios to simulate real-world crime contexts and test interventions. Projects: He leads initiatives like the 360º Virtual Scenario Method , Virtual Burglary Project , and FutureU —a VR-based intervention to enhance future self-connection in offenders. His collaborations span Leiden University, University of Portsmouth, and Jacobs Center for Productive Youth Development (University of Zurich). Affiliations: External Research Associate, University of Portsmouth Research Collaborator, Jacobs Center for Productive Youth Development Publications: His recent work examines VR's role in criminology, the link between childhood adversity and cognitive processes, and digital interventions for mental health and delinquency reduction. Contact: sek-kriminologie@csl.mpg.de | +49 761 7081-701

Wessie Lingمشاهده پروفایل

استاد

• Transcultural Fashion Studies
• Chinese Dress History
• Museum Curation
• +۳ مورد دیگر

Professor Wessie Ling serves as Professor of Transcultural Arts and Design at London Metropolitan University's School of Art, Architecture and Design, where she directs CREATURE (The Centre for Creative Arts, Cultures and Engagement). Her career spans academic leadership roles at Northumbria University and University of the Arts London, alongside international research fellowships at Mahidol University and the National Museum of World Cultures. Her research centers on transcultural fashion dynamics, particularly Chinese dress history and global fashion systems. Key interests include: Cultural production and identity construction in fashion Museum curation of non-Western artifacts Trans-East Asian fashion exchanges (China-Japan-Korea) Visual art practice exploring fashion's intangible assets Analysis of her recent publications reveals consistent focus on decolonizing fashion narratives, examining how artifacts like the cheongsam function as sites of cultural negotiation. Her work bridges academic scholarship with visual art installations addressing consumer culture, postcolonialism, and global capitalism. Notable scientific contributions include: Rita Bolland Fellowship (2018/9) for fashion-textile research ASEAN Research Fellowship (2018) Design History Society Publication Grant (2018) AHRC-funded projects on transnational design histories Professor Ling actively advises cultural institutions including the National Museum of World Cultures and Centre for Contemporary Chinese Art (CFCCA), where she serves on the Artistic Committee. Her external examiner roles at Royal College of Art and Edinburgh University demonstrate significant academic influence. She maintains active studio practice with exhibitions at Victoria & Albert Museum and Tropenmuseum, operating under the artist name WESSIELING. Her research infrastructure includes leadership of CREATURE center and collaborations with institutions like Shanghai Jiao Tong University and Fu Jen Catholic University. Current projects examine China laundry bags' socio-cultural history and global fashion's relationship with ethnographic museums.

Agiakloglou Christosمشاهده پروفایل

استاد

• Time Series Analysis
• Econometrics
• Macroeconomics
• +۲ مورد دیگر

Professor Christos Agiakloglou is a faculty member at the Department of Economics, University of Piraeus. He holds a PhD in Econometrics and Time Series Analysis from the University of Illinois at Urbana–Champaign, two Master's degrees in Finance and Economics from the University of Illinois and Florida Atlantic University, and a Bachelor's in Economics from the University of Macedonia. His research spans time series analysis, econometrics, macroeconomics, and industrial organization. Education: PhD, University of Illinois at Urbana–Champaign (Econometrics & Time Series Analysis) MSc in Finance, University of Illinois at Urbana–Champaign MA in Economics, Florida Atlantic University Bachelor in Economics (with honors), University of Macedonia His publications focus on econometric theory, spurious regression, unit root testing, and time series modeling. Notable works include studies on AR(1) processes, fractional integration, and causality in macroeconomic variables. Professor Agiakloglou has received the Robert E. Demarest Memorial Award for Excellence in Teaching at the University of Illinois. He teaches undergraduate and graduate courses in econometrics, statistical methods, and quantitative analysis.

Shikha Singhمشاهده پروفایل

استادیار

• Algorithmic Game Theory
• Algorithms & Data Structures
• Theoretical Computer Science
• +۳ مورد دیگر

Shikha Singh is an Assistant Professor of Computer Science at Williams College. She holds a PhD from Stony Brook University (2018) and an Integrated BSc & MSc from IIT Kharagpur (2013). Her research focuses on algorithmic game theory, algorithms with predictions, and data structure optimization. She has received tenure at Williams College and was recognized for her work on adaptive filters at ESA 2021 and NeurIPS 2023. Education: PhD, Stony Brook University (2018); Integrated MSc & BSc, IIT Kharagpur (2013) Research Interests: Algorithmic game theory, adaptive and I/O-efficient algorithms, data structures with predictions. She explores how incentives influence algorithm outcomes and designs efficient algorithms for big data challenges. Key Contributions: Her work on online list labeling with predictions (NeurIPS 2023) and incremental shortest path algorithms (ICALP 2025) highlights her focus on predictive algorithms. Collaborations include visits to Carnegie Mellon University and Dagstuhl seminars. Awards: COCOA 2017 Best Paper Runner-Up, NeurIPS 2023 Spotlight Advising: Advised David Lee on adaptive filters (ESA 2021). Active in program committees for Euro-Par, TAMC, and ALENEX. Labs/Teams: Collaborates with Benjamin Moseley on scheduling and data structure research. Part of Williams College’s vibrant CS department.

Adam D. Groceمشاهده پروفایل

استاد

• Cryptography
• Theoretical Computer Science
• Database Privacy
• +۳ مورد دیگر

Adam D. Groce is a Professor of Computer Science at Reed College , specializing in cryptography, differential privacy, and rational cryptography. He obtained his PhD in Computer Science from the University of Maryland in 2014 under the supervision of Jonathan Katz, after completing bachelor’s degrees in mathematics and political science at MIT . Research Interests Database privacy and differential privacy, with a focus on practical hypothesis testing under privacy constraints. Rational cryptography, exploring the intersection of cryptography and game theory by modeling adversaries as rational actors. General theoretical computer science, especially secure multi-party computation, zero-knowledge proofs, and oblivious RAM. Scientific Awards & Recognition No specific awards listed in the provided text. Teaching & Mentorship Regularly teaches core undergraduate courses: Introduction to Computing (CSCI 121), Algorithms and Data Structures (MATH/CSCI 382), Computability and Complexity (MATH/CSCI 387), and Cryptography (MATH/CSCI 388). Offers advanced topics courses such as Advanced Algorithms and specialized seminars in theoretical computer science. Has advised over a dozen senior theses at Reed, many co-advised and several resulting in peer-reviewed publications. Actively invites Reed undergraduates to join research projects in privacy and cryptography. Contact & Location Office: Library 313, Reed College, 3203 SE Woodstock Blvd, Portland, OR 97202 Phone: 503-517-5155 Email: agroce@reed.edu

Jan Friedrichمشاهده پروفایل

استادیار

• Accounting
• Sociology of Accounting
• Financial Reporting
• +۳ مورد دیگر

Jan Friedrich is an Assistant Professor in the Financial Reporting & Audit department at ESCP Business School Paris Campus, where his research bridges accounting and sociology to examine standard-setting dynamics and organizational practices in financial reporting. He earned his PhD in accounting from Goethe University Frankfurt, complemented by visiting research positions at Copenhagen Business School, ESSEC Business School, and Sciences Po. His core research spans: Accounting standard-setting processes Financial market regulation Environmental accounting Organizational memory work Sociology of accounting professions Occupational dynamics in regulatory frameworks Analysis of his recent publications reveals growing interdisciplinary engagement with legal theory and sustainability science, particularly in transnational accounting governance and rights-based environmental accounting approaches. He teaches International Financial Reporting (IFRS) across the Master in Management and Big Data and Business Analytics programmes.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Petri Myllymäki is a Director at Helsinki Institute for Information Technology (HIIT) , Computer Science Adjunct Professors , and Finnish Center for Artificial Intelligence (FCAI) within Aalto University's School of Science, Department of Computer Science . His research focuses on Bayesian networks, information discovery, and interactive intent modeling . Active in ACM Transactions on Information Systems and SIGIR Conference publications Recipient of 2016 CPHC/BCS Academy of Computing Distinguished Dissertation runner-up and 2017 Kone Foundation Rajapinta award Collaborated with institutions like Stockholm University and researchers including Giulio Jacucci and Samuel Kaski His 15 most recent publications (2025-2015) span decision-making under conflicting objectives, machine learning applications in social science, Bayesian network structure learning algorithms , and cognitive modeling for exploratory search . Key technical subfields include hashing techniques, two-dimensional representation, computational efficiency, and user experience optimization . Scientific awards : 2016 CPHC/BCS Academy of Computing Distinguished Dissertation runner-up 2017 Kone Foundation Rajapinta award As an information discovery expert , he has contributed to open-access research through Interactive Visualization and Scinet frameworks, impacting Sustainable Development Goals related to digital innovation and knowledge dissemination.

Prashant Pandeyمشاهده پروفایل

استادیار

• Large-Scale Data Systems
• High-Performance Computing
• Computational Biology
• +۳ مورد دیگر

Prashant Pandey is an Assistant Professor at Northeastern University's Khoury College of Computer Sciences, co-directing the Data Lab and affiliated with Berkeley Lab's Performance and Algorithms Research Group. He holds a PhD in Computer Science from Stony Brook University (2018), with prior postdoc research at UC Berkeley, LBL, and Carnegie Mellon University, and a year as a Research Scientist at VMware Research. His research focuses on scalable data systems with theoretical guarantees, spanning high-performance computing, computational biology, stream processing, and storage. Key projects include designing adaptive filters, GPU-accelerated data structures, and graph containers for skewed dynamic data. Recent talks include sessions on hash tables, B-trees, and graph frameworks at conferences in Bangalore, Las Vegas, and Santiago. Teaching includes courses like Advanced Database Systems and Data Structures for Scalable Computing. His work bridges systems and algorithms, emphasizing practical applications in bioinformatics and exascale computing. Awards and grants are not explicitly listed, but his contributions include foundational papers on filters, hash tables, and genomic data indexing. Ongoing efforts involve the Data Lab's exploration of high-performance filters for GPUs and collaborative projects like the BP-tree and Vector Quotient Filters. Students under his supervision focus on database systems, learned indexes, and external-memory joins.

Qin Zhangمشاهده پروفایل

استاد

• Algorithms for Big Data
• Theoretical Foundations of Machine Learning
• Quantum Information and Computing
• +۴ مورد دیگر

Roles and Affiliations: Professor of Computer Science at Indiana University Bloomington, Adjunct Professor in Mathematics. Previously at IBM Almaden Research Center and Aarhus University's Center for Massive Data Algorithmics. PhD from HKUST in Computer Science and Engineering. Education: PhD in Computer Science, HKUST, advised by Mordecai Golin and Ke Yi Research Interests: Focuses on algorithms for big data, including communication-efficient distributed computation, streaming/sketching algorithms, and quantum data management. Explores theoretical foundations of machine learning, particularly distributed learning. Leads projects funded by NSF grants on parallel reinforcement learning, distributed graph algorithms, and noisy data processing. Publications and Awards: Over 100 papers in top venues like FOCS, SIGMOD, and NeurIPS. Won the Best Paper Award at SPAA 2017 for distributed clustering work. Invited to special journal issues for top conferences. Teaching and Grants: Teaches advanced courses on sublinear algorithms and algorithm design. PI on NSF grants totaling over $2M, including collaborative projects on distributed computing and epidemiological modeling. Advises PhD students in areas like quantum algorithms and reinforcement learning. Service: Served on program committees for SIGMOD, NeurIPS, ICML, and PODS. Organizes theory seminars and Midwest Theory Day workshops.