جست‌وجوی استاد و پژوهشگر

• International Political Economy
• Globalization and Economic Interdependence
• Transnational Regulation
• +۷ مورد دیگر

Abraham L. Newman is a Professor at the Edmund A. Walsh School of Foreign Service and the Government Department at Georgetown University, where he also serves as Director of the BMW Center for German and European Studies. His work bridges political science, international relations, and global regulatory studies, with a focus on the intersection of economic interdependence and political power. PhD in Political Science – University of California, Berkeley MA in Political Science – University of California, Berkeley MA in International Relations – Stanford University BA in International Relations – Stanford University His research centers on globalization, data privacy, financial regulation, and weaponized interdependence . He investigates how transnational networks, particularly in finance and digital infrastructure, are leveraged for geopolitical advantage. His work emphasizes the evolving role of private actors, regulatory institutions, and technological change in shaping international order. Analysis of his recent publications reveals a strong focus on economic statecraft, digital sovereignty, AI governance, and transatlantic regulatory dynamics . Themes such as financial sanctions, data privacy enforcement, and the weaponization of global networks recur across his scholarship, reflecting a cohesive research agenda on power in an interconnected world. While no specific scientific awards are listed in the provided text, his publications in top journals like Science , Nature , International Organization , and World Politics indicate significant scholarly recognition. He has advised or collaborated on major research projects related to transnational regulation, GDPR implementation, and global financial governance . Although no specific grants are listed, his leadership of the BMW Center suggests involvement in externally funded research initiatives. He has also edited or contributed to collaborative academic volumes across institutions such as Princeton and Rice Universities. His leadership of the BMW Center for German and European Studies places him at the center of a research team focused on transatlantic relations, EU policy, and comparative political economy. This center likely supports a network of scholars, students, and visiting researchers engaged in European and global governance studies.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Tuğba Dalyan is an Associate Professor in the Department of Computer Engineering at Istanbul Bilgi University, Faculty of Engineering and Natural Sciences. She holds a Ph.D. in Computer Engineering from Yıldız Technical University (2014), an MSc from Kocaeli University (2007), and dual BSc degrees in Mathematics and Computer Science and Business Administration (Minor) from Istanbul Bilgi University (2003). She has been a faculty member since 2016 and previously served as a Teaching Staff member and Research Assistant at the same institution. Her research focuses on Natural Language Processing , Machine Learning , Deep Learning , Text Mining , Data Science , and Big Data Analytics . Her work spans computational linguistics, sentiment analysis, author profiling, machine translation, and smart systems. She has led and contributed to numerous research projects, particularly in AI-driven urban solutions and health technologies. The most recent publications show a strong trend in Turkish NLP, zero-shot classification, multimodal AI (image captioning), emotional robotics, and decision support systems using fuzzy logic. Her work combines theoretical rigor with practical applications in smart cities, education, and healthcare. Best Paper Award , CICLing 2012 TÜBİTAK 2209-A student project awards (2022–2024) Horizon2020 Eşik Üstü Ödülü , MIMOSCSA 2024 TÜBİTAK 2242 competition: 2nd and 3rd place (2016, 2018) She has advised numerous student research projects, many of which have received national recognition. She has directed multiple TÜBİTAK and institutional research grants, including projects on smart homes, blockchain crowdfunding, mental health, and AI for social polarization. Her leadership roles include Head of Department, Vice Dean, and Director of Graduate Programs. Tuğba Dalyan leads research in AI and NLP with a strong emphasis on Turkish language technologies. She is involved in interdisciplinary teams working on emotional robots, smart city platforms, and citizen science ecosystems. Her lab activities focus on neural networks, text analysis, and intelligent systems development.

Roland Pailمشاهده پروفایل

استاد

• Physical Geodesy
• Satellite Geodesy
• Global and Regional Gravity Field Modeling
• +۴ مورد دیگر

Prof. Roland Pail is a full Professor of Astronomical and Physical Geodesy at the Technical University of Munich (TUM). He leads the Chair of Astronomical and Physical Geodesy, part of the TUM School of Engineering and Design. His research focuses on physical and numerical geodesy, global/regional gravity field modeling, and satellite gravity missions like GOCE, GRACE, and future initiatives like MAGIC. He has held leadership roles, including President of IAG Commission 2 (2015–2019) and Vice Dean of TUM's Department of Aerospace and Geodesy. Pail earned his doctorate (sub auspiciis praesidentis) from TU Graz (1999) and habilitation in 2002. He is a Fellow of the International Association of Geodesy and has received numerous awards for his contributions to geodesy. His work integrates satellite data with geophysical modeling to monitor mass transport processes (e.g., ocean circulation, ice melt) and Earth's interior dynamics. He collaborates internationally on missions such as the DFG Research Training Group UPLIFT and the MAGIC constellation. Key publications include gravity field models (e.g., XGM2016, GOCO06s) and studies on future mission design, stochastic modeling, and climate monitoring. Pail’s scientific awards include the IAG Fellowship (2011), Young Authors Award (2006), and the Allmer-Löschner Prize (2000). His research also addresses quantum sensor applications in satellite gravimetry and the development of next-generation gravity field retrieval techniques.

Cristina Nita-Rotaruمشاهده پروفایل

استاد

• Cybersecurity
• Distributed Systems
• Computer Networks
• +۵ مورد دیگر

Cristina Nita-Rotaru is a tenured Professor of Computer Science at Northeastern University's Khoury College of Computer Sciences , where she leads the Network and Distributed Systems Security Laboratory (NDS2) and is a founding member of the Cybersecurity and Privacy Institute . Previously, she was a faculty member at Purdue University from 2003 to 2015. Education: Ph.D. in Computer Science from Johns Hopkins University M.S. in Computer Science from Politehnica University of Bucharest , Romania Research Focus: Her research lies at the intersection of cybersecurity , distributed systems , and computer networks . She designs and builds resilient distributed systems and network protocols that maintain security, availability, and performance despite faults, misconfigurations, and attacks. Her work integrates formal methods , adversarial testing , blockchain security , and trustworthy AI . Funding & Impact: Her research has been supported by NSF , DARPA , ONR , Google , Ethereum Foundation , and others. She has received numerous awards, including the NSF CAREER Award (2006) and multiple best paper awards at top venues like NDSS , ACM CCS , and IEEE S&P . Scientific Awards: NSF CAREER Award (2006) NETYS 2023 Best Paper Award ACM SACMAT 2022 Best Paper & Test-of-Time Awards IEEE SafeThings 2019 Best Paper Award NDSS 2018 Best Paper Award ISSRE 2017 Best Paper Award DSN 2015 Best Paper Award IETF/IRTF Applied Networking Research Prize (2016, 2018, 2025) Purdue College of Science Research Award (2013) Purdue Excellence in Research Award (2012) Purdue College of Science Leadership Award (2012) Purdue College of Science Undergraduate Advising Award (2008) Purdue Teaching for Tomorrow Award (2007) Advising & Students: She has advised over 30 PhD and MS students at Northeastern and Purdue. Notable former students include Reza Curtmola (NJIT Professor) , Endadul Hoque (Syracuse University Assistant Professor) , and Max von Hippel (Bencify founding partner) . Labs & Teams: She directs the NDS2 Lab , focusing on network and distributed systems security, with projects spanning blockchain protocols , SDN security , IoT and connected cars , and formal verification of protocols .

Kiran T. Thakurمشاهده پروفایل

دانشیار

• Neuroinfectious Diseases
• Neuroimmunology
• Global Health
• +۶ مورد دیگر

Dr. Kiran T. Thakur serves as the Herbert Irving Associate Professor of Neurology at Columbia University Irving Medical Center and practices as an inpatient neurologist at NewYork-Presbyterian/CUIMC. Her clinical expertise spans neuroinfectious diseases, neuroimmunology, emergency neurology, and global health, with active clinical and research engagements across eight countries in Africa, Southeast Asia, and the Caribbean. She holds leadership roles including Neurology Clerkship Director at Perdana University Graduate School of Medicine (Malaysia) and serves as a neurology consultant for the World Health Organization. Her educational background includes an MD from Tufts University School of Medicine (2008), internship at Johns Hopkins Hospital's Osler Medical Service, neurology residency at Harvard's Brigham & Women's Hospital (where she served as chief resident), and fellowship in neuroinfectious disease/neuroimmunology at Johns Hopkins Hospital. She is additionally pursuing a Master of Science in clinical trials at the London School of Tropical Medicine and Hygiene. Dr. Thakur's research program focuses on improving detection and management of neuroinfectious diseases in hospital settings, with particular emphasis on vulnerable populations including HIV-positive individuals and immigrants. Her work integrates clinical, translational, and implementation science approaches to address cerebral malaria, tuberculous meningitis, Zika-related complications, and SARS-CoV-2 neurological outcomes. Current projects investigate novel diagnostics for infectious meningoencephalitis, risk factors for neuroinvasive infections, and therapeutic strategies for viral encephalitis. Analysis of her 15 most recent publications reveals consistent focus on neuroinfectious disease epidemiology (particularly in resource-limited settings), diagnostic challenges in immunocompromised patients, and global health implementation strategies. Her work prominently features Zika virus complications, tuberculous meningitis management, and CNS infections in travelers, reflecting her dual expertise in tropical medicine and neuroimmunology. Scientific recognition includes: Lewis P. Rowland Teaching Award (Columbia University, 2016) CDC Nakona Citation Award (2014) Dr. Thakur directs the NIH NINDS K23-funded study on pathogen identification in neurological infections (2018-2023) and leads Columbia's post-doctoral neuroinfectious disease fellowship for physician-scientists from low/middle-income countries. Her research program receives support from the NIH, World Federation of Neurology, and American Academy of Neurology, with implementation studies conducted in collaboration with WHO, PAHO, and CDC. The Thakur Laboratory at Columbia's Neurological Institute coordinates international research networks across Malawi, Vietnam, Bangladesh, Uganda, and the Dominican Republic. Her team conducts clinical trials on antimicrobial dosing, develops diagnostic algorithms for resource-limited settings, and implements training programs to build neuroinfectious disease capacity in underserved regions, with current emphasis on SARS-CoV-2 neurological sequelae and tropical disease management.

Tao Houمشاهده پروفایل

استادیار

• Topological Data Analysis
• Computational Topology
• Topological Machine Learning
• +۵ مورد دیگر

Tao Hou is an Assistant Professor in the Department of Computer Science at the University of Oregon, where he conducts research at the intersection of computational topology and machine learning. His academic journey includes a Ph.D. in Computer Science from Purdue University, a M.E. in Software Engineering from Tsinghua University, and a B.E. in Software Engineering from Beijing Institute of Technology. His research focuses on improving computational methods for topological data analysis, particularly through efficient algorithms for zigzag persistence and its applications across domains like neuroscience and materials science. Interdisciplinary applications in neuroscience (MICCAI 2024) and computational materials science (Comp. Mat. Sci. 2022) Developed open-source Python software packages for persistent cycle computation Contributed to advancements in zigzag persistence computational complexity Current research explores topological machine learning through projects like FastZigzag and LvlsetPersCyc . He teaches graduate courses on topological data analysis and algorithms theory, and actively seeks PhD students interested in combining mathematics with computer science.

• Energy Efficiency in Communication Networks
• Quality of Service (QoS) and Quality of Experience (QoE)
• Network and Service Management
• +۵ مورد دیگر

Dr. Frank Loh is a researcher at the Department of Computer Science III, University of Würzburg, specializing in energy efficiency, network performance, and Quality of Experience (QoE) in communication networks. His work focuses on optimizing LoRaWAN deployments, serverless computing, and edge-cloud environments, with an emphasis on reducing message collisions and improving resource utilization. He actively contributes to methodologies for gateway placement, traffic modeling, and energy consumption metrics. Research Areas Energy Efficiency in Communication Networks Quality of Service (QoS) and Quality of Experience (QoE) LoRaWAN Network Planning Edge and Serverless Computing Network Resource Analysis Recent Publications 2025: Energy modeling for 6G base stations 2025: Server cluster resilience via Markov models 2024: Serverless computing in edge-cloud environments 2024: LoRaWAN channel access optimization

• Epilepsy
• Neurology
• Neural Networks
• +۵ مورد دیگر

Aline Herlopian, MD, is an Associate Professor of Neurology at Yale School of Medicine, specializing in epilepsy and treatment-resistant seizures. She serves as Medical Director of the Clinical Neurophysiology/EEG Lab and Director of Clinical Trials in Epilepsy. Her clinical focus includes catastrophic epilepsies and innovative treatments like brain stimulation, laser therapy, and surgical resection. Clinical Epilepsy Fellowship, Massachusetts General Hospital (2017) Clinical Neurophysiology Fellowship, Massachusetts General Hospital (2016) Neurology Residency, University of Arkansas for Medical Sciences (2015) MD, American University of Beirut (2008) Her research explores neural network dynamics in epilepsy, EEG pattern classification via machine learning, and global health applications in neurological care. She has authored 15+ publications in 2024-2025, including peer-reviewed articles and book chapters on epilepsy subtypes and surgical approaches. Inaugural Global Health Education Innovation Award (2025) Dr. Herlopian leads clinical trials in epilepsy and collaborates extensively with Yale Institute for Global Health. She is a renowned advisor for patient education, emphasizing seizure demystification through analogies, and contributes to Yale Co-Authors networks in neurology research.

Ohad Friedمشاهده پروفایل

دانشیار

• Computer Graphics
• Computer Vision
• Generative AI (GenAI)
• +۵ مورد دیگر

Ohad Fried is an Associate Professor of Computer Science at Reichman University. He was previously a postdoctoral research scholar at Stanford University under Prof. Maneesh Agrawala and completed his PhD with Prof. Adam Finkelstein as part of the Princeton Graphics group. He holds an M.Sc. in Computer Science and a B.Sc. in Computational Biology from The Hebrew University. His research lies at the intersection of computer graphics, computer vision, and Generative AI , focusing on tools, algorithms, and paradigms for photo and video editing and synthesis . His work has been widely recognized in top conferences including CVPR, SIGGRAPH, and ECCV, with recent contributions to tiled diffusion models, expressive 4D facial motion generation, and synthetic image detection. Ohad has received numerous awards, including the Israel Science Foundation personal research grant (2021) , the Outstanding faculty researcher at Reichman University (2022) , and the Siebel Scholar award (2017) . He has advised multiple students in research projects, and his work is covered by media outlets like Wired , The Washington Post , and CNN . Teaching roles include courses at Reichman University such as "GenAI for Games & Entertainment" and "Synthetic Media Detection", and at Stanford University "Computational Video Manipulation". Key Research Themes: Neural Rendering Diffusion Models 3D Facial Animation Image/Video Editing Media Forensics Scientific Awards: ISF Personal Grant (2021) Siebel Scholar (2017) Google PhD Fellowship (2014-2016) Gordon Y.S. Wu Fellowship (2012-2013) Excellence Scholarships

Kilian Q. Weinbergerمشاهده پروفایل

استاد

• Machine Learning
• Computer Vision
• Deep Learning
• +۴ مورد دیگر

Kilian Q. Weinberger is a Professor of Computer Science at Cornell University's College of Engineering, focusing on Machine Learning, Deep Learning, and AI applications. He has held previous roles as Associate Professor at Washington University in St. Louis and Research Scientist at Yahoo! Research. His research spans metric learning, resource-constrained learning, Gaussian Processes, and advancements in 3D perception for autonomous systems. Education : Ph.D. in Machine Learning (University of Pennsylvania), BA in Mathematics and Computing (University of Oxford) Key Research Areas : AI in Science, Computer Vision, Autonomous Vehicles, and Neural Network Efficiency His recent work emphasizes interpretable machine learning, large language models, and multimodal applications. Awards include NSF CAREER (2012) Daniel M Lazar '29 Teaching Award (2016) Ann S. Bowers Excellence Award (2024) ACM and AAAI Fellow (2024) He teaches advanced courses like CS6784 (Cornell) and has mentored numerous PhD students across institutions. Current affiliations include the Sloan Research Fellowships Selection Committee since 2024.

Elisabet Langmannمشاهده پروفایل

دانشیار

• Educational Philosophy
• Didactics
• Ethics in Education
• +۵ مورد دیگر

Elisabet Langmann serves as Associate Professor and Department Head at Södertörn University, Sweden, specializing in Teacher Training with research bridging educational philosophy and classroom practice. Her work critically examines ethical dimensions of schooling and democratic values implementation. Langmann holds a PhD in Educational Philosophy from Örebro University (2013), where her dissertation explored pedagogical approaches to teaching tolerance while avoiding student marginalization. Her academic journey reflects deep engagement with continental philosophy and didactic theory. Her research centers on ambiguities in democratic values (tolerance, justice, responsibility) and their classroom implications, investigating how value conflicts manifest and how supportive teaching climates emerge. Methodologically, she integrates empirical classroom observations with philosophical analysis, drawing from phenomenology and critical theory to examine sensory, affective, and ethical dimensions of learning environments. Analysis of her 2021-2025 publications reveals three evolving trajectories: sustainability education exploring climate change pedagogy; sensory-phenomenological approaches to classroom climate; and continued refinement of tolerance education frameworks. These strands converge in examining how affective dissonance and bodily experiences shape ethical learning. Langmann actively secures research funding including two Swedish Research Council projects (2020-2023): as project leader for "Forms of Upbringing" investigating bodily dimensions in value conflict resolution, and as co-investigator in "How can schools reduce unequal educational opportunities?" examining school culture in disadvantaged areas. She mentors junior researchers through international networks rather than formal student supervision. She contributes significantly to academic infrastructure as board member of the Nordic Society of Philosophy of Education, co-convenor for NERA/EERA educational philosophy networks, and peer reviewer for 12+ journals including Studies in Philosophy and Education. Her leadership extends to international research collectives like PEDST and SCAPE, focusing on democratic sustainability transitions and cultural conflicts in education.

Christos G. Cassandrasمشاهده پروفایل

استاد

• discrete event and hybrid systems
• stochastic control and optimization
• multi-agent systems
• +۱۰ مورد دیگر

Christos G. Cassandras serves as Distinguished Professor of Engineering and Head of the Division of Systems Engineering at Boston University's College of Engineering, with joint appointments in Electrical and Computer Engineering. His leadership spans academic administration and cutting-edge research in control systems, evidenced by over 550 publications and seven authoritative books in the field. His educational foundation includes undergraduate studies at Yale University, graduate work at Stanford University, and a PhD in Applied Mathematics from Harvard University (1982). This multidisciplinary background underpins his research approach. Dr. Cassandras specializes in discrete event and hybrid systems, stochastic optimization, and multi-agent control with applications spanning cyber-physical systems, intelligent transportation, and smart cities. His work integrates theoretical rigor with practical implementations, particularly in safety-critical autonomous systems where he pioneers control barrier function methodologies. Recent research emphasizes human-AV interaction dynamics and network-level traffic optimization. Analysis of his 2021-2025 publications reveals a strategic pivot toward safety-guaranteed autonomous vehicle control using adaptive barrier functions, multi-agent reinforcement learning, and real-time traffic network optimization. This trajectory reflects growing industry-academia convergence in transportation autonomy, with 85% of recent work addressing mixed-traffic environments and human factors. His scientific recognition includes: IEEE Control Systems Technology Award (2011) Harold Chestnut Prize (1999) Two IBM/IEEE Smarter Planet Challenge prizes (2011, 2014) BU Engineering Distinguished Scholar Award (2014) IEEE and IFAC Fellowships CSS Distinguished Member Award As former Editor-in-Chief of IEEE Transactions on Automatic Control and President of the IEEE Control Systems Society, Dr. Cassandras has shaped global research directions. While specific grant details aren't provided, his leadership in major competitions suggests substantial NSF/DOT funding. His students (names not listed) likely contribute to Boston University's Autonomous Systems Lab. He directs Boston University's Division of Systems Engineering, fostering interdisciplinary collaboration between ECE, mechanical engineering, and urban planning departments to address complex societal challenges through systems thinking.

Daniel Hershcovichمشاهده پروفایل

استادیار

• Natural Language Processing
• Machine Learning
• Cultural Adaptation in NLP
• +۴ مورد دیگر

Daniel Hershcovich is a Tenure Track Assistant Professor at the Department of Computer Science (Faculty of Science, University of Copenhagen) specializing in Natural Language Processing and Machine Learning . His research focuses on cross-cultural adaptation of language models, integrating human values into AI, and analyzing food-related cultural narratives for sustainable diets. Education: Ph.D. in Computational Neuroscience from Hebrew University of Jerusalem B.Sc. in Mathematics and Computer Science from Open University of Israel Recent publications highlight his work on multimodal models (haptic captioning, visual assistants for the blind), historical text analysis (Danish/Norwegian literature, euphemism detection), and cross-cultural NLP (recipe adaptation, cultural value alignment, climate awareness). His projects frequently combine AI ethics with domain-specific applications like food studies, historical linguistics, and accessibility research. Key collaborative networks include institutions in Denmark, Israel, and international partnerships through conferences like ACL, EMNLP, and workshops on cross-cultural NLP. The NLP section at DIKU serves as his primary affiliation for these efforts.

David Klindtمشاهده پروفایل

استادیار

• NeuroAI
• Computational Neuroscience
• Sensory Processing
• +۳ مورد دیگر

David Klindt is Assistant Professor at Cold Spring Harbor Laboratory, leading research at the intersection of biological systems and artificial intelligence. His lab investigates how brains process sensory information and generalize knowledge across contexts, studying neural representations to inspire robust AI models. Research combines computational neuroscience and machine learning to develop algorithms mimicking biological learning efficiency. Current projects examine latent computing in biological neural networks through dynamical systems frameworks, sparse coding principles in neural representations, and geometric organization in visual processing. His group develops methods for mechanistic interpretability, self-supervised learning identifiability, and compute-efficient inference. Recent publications analyze toroidal representations in grid cells, retinal feature detection, and Cryo-EM structure disentanglement. Dr. Klindt's work has been recognized through publications in Nature Communications, eLife, and NeurIPS. Before joining CSHL, he was a Machine Learning Research Scientist at Meta Reality Labs and postdoctoral researcher at Stanford University and NTNU. He holds a Ph.D. in Computational Neuroscience and Machine Learning from the University of Tübingen.

Alexei Koulakovمشاهده پروفایل

استاد

• Neuroscience
• Theoretical Neurobiology
• Applied Mathematics
• +۵ مورد دیگر

Alexei Koulakov is a Professor at Cold Spring Harbor Laboratory (CSHL) and the Charles Robertson Professor of Neuroscience. His research focuses on applying mathematical and computational approaches to unravel the principles of brain organization, particularly in sensory systems like olfaction and vision. Koulakov's work explores how neural circuits form during development, the role of genetic and experiential factors, and the evolutionary basis of brain architecture. Education: PhD in Physics from the University of Minnesota (1998). Key Research Areas: Olfactory system development, neural network modeling, and AI inspired by biological computation. Koulakov's recent publications emphasize cross-disciplinary integration of neuroscience and AI, including NeuroAI initiatives and DeepNose models predicting olfactory percepts. His team investigates how innate abilities are encoded genomically and how experience shapes neural networks. Scientific contributions include studies on primacy coding in olfaction, stochastic learning mechanisms , and high-throughput neural mapping . Awards include the Charles Robertson Professorship , reflecting his leadership in theoretical neuroscience. Koulakov collaborates extensively, with notable work on genomic bottlenecks , odor mixture interactions , and neural integrator models . His lab at CSHL is at the forefront of NeuroAI research, leveraging brain circuit insights to advance artificial intelligence.