جست‌وجوی استاد و پژوهشگر

Fabio Furiniمشاهده پروفایل

دانشیار

• Combinatorial Optimization
• Operations Research
• Integer Linear Programming
• +۳ مورد دیگر

Fabio Furini is an Associate Professor at the Department of Computer Science, Automatics, and Management (DIAG) at Sapienza University of Rome since September 2021. Prior to this position, he served as a CNR researcher at IASI-CNR in Rome (2020-2021), Maître de Conférences at Université Paris-Dauphine, France (2013-2019), postdoctoral researcher at Université Paris-13, France (2012-2013), and research fellow at the University of Bologna (2011-2012). His educational background includes a Ph.D. in Control Engineering and Operations Research from the University of Bologna in 2011. He further obtained the Habilitation à Diriger des Recherches (HDR) in France in 2017 and the National Scientific Qualification for Full Professor in Operations Research in Italy in 2019. Fabio Furini conducts theoretical and methodological research on Combinatorial Optimization and Operations Research. His primary focus is on developing exact algorithms based on decomposition and reformulation techniques for integer linear programming problems. His research spans various applications including network optimization, graph theory, and combinatorial problems such as the maximum clique problem, bin packing problem, and vertex separator problem. His work often bridges theoretical developments with practical applications in transportation, logistics, and network security. His recent publications demonstrate a strong focus on exact algorithms for combinatorial optimization problems, particularly in network interdiction, bin packing with temporal constraints, and graph-based problems. His work consistently combines integer programming techniques with combinatorial search methods to develop novel formulations and efficient solution approaches that advance the state-of-the-art in these domains. Among his notable scientific awards are the Prime d'encadrement doctoral et de recherche (PEDR), which he received annually from 2014 to 2020, recognizing him among the top 15% of researchers in the French university system. He also holds the prestigious Habilitation à Diriger des Recherches from France (2017) and the National Scientific Qualification for Full Professor in Operations Research from Italy (2019). Fabio Furini has been actively involved in supervising PhD students and has served as principal investigator for numerous national and international research projects. His extensive network includes over 60 co-authors across European and American universities. He is also a member of the editorial boards for three prestigious international journals: Omega, Annals of Operations Research, and Discrete Applied Mathematics. His research activities include collaborations with various institutions across Europe and the United States, including Imperial College London and the University of Colorado. These collaborations have resulted in a robust research program focused on advancing the theoretical foundations and practical applications of combinatorial optimization.

• Manufacturing Management
• Production Planning
• Production Control
• +۱۴ مورد دیگر

Maria Leonilde Rocha Varela is an Associate Professor with Habilitation at the School of Engineering, University of Minho, Portugal, where she also serves as a Senior Researcher at the Algoritmi Research Centre. She has been an integrated member of the Algoritmi Research Centre since 2012 and works in the Department of Production and Systems. Dr. Varela earned her degree in Production Engineering from the University of Minho in 1994, completed a Master's in Computer Integrated Production at DPS-UMinho in 1999, and received her Ph.D. in Production and Systems from the University of Minho in 2007. Her primary research focuses on Manufacturing Management, particularly Production Planning, Control and Optimization, and Collaborative Paradigms, Networks and Decision Making Models. She maintains extensive international collaborations with institutions worldwide including the National Institute of Industrial Engineering, VSB-Technick Univerzita Ostrava, University of Belgrade, and others. Her research spans Web Applications and Services for supporting Engineering and Production Management, with increasing emphasis on Artificial Intelligence, Robotic Process Automation, and Industry 4.0/5.0 applications. She has made significant contributions to scheduling algorithms, optimization techniques, and decision support systems for manufacturing environments. Analysis of her recent publications reveals a strong trend toward integrating Artificial Intelligence with traditional manufacturing processes, particularly in Robotic Process Automation applications. Her research increasingly focuses on sustainable manufacturing practices, with numerous publications addressing energy efficiency, environmental sustainability, and resource optimization. There is a clear emphasis on multi-objective optimization approaches to solve complex manufacturing problems, particularly in distributed job shop scheduling. Her work demonstrates an evolution from traditional production planning methods to more advanced AI-driven approaches for Industry 4.0 and 5.0 environments. Dr. Varela has held significant academic leadership roles, currently serving as the director of the master's course in Engineering and Quality Management at DPS-UMinho. She previously coordinated the industrial management and systems subgroup from 2012 to 2021 and was part of the steering committee for the master's course in systems engineering between 2016 and 2019. She has successfully supervised more than 70 MSc projects, with over 15 currently ongoing, focusing on Production and Systems Engineering. Her supervision encompasses collaborative management models, traditional decision approaches, and web-based platforms incorporating AI techniques. She coordinates research projects including 2 concluded Ph.D. projects and 6 ongoing ones. She collaborates as a research member in several R&D projects with national and international industrial enterprises and institutions, and in international Erasmus projects. Dr. Varela is an active participant in the academic community, serving on editorial boards of several international journals and as a member of organizing and scientific committees for numerous international conferences. She is a member of several prestigious research networks including the Euro Working Group of Decision Support Systems (EWG-DSS), Institute of Electrical and Electronics Engineers (IEEE), Industrial Engineering Network, and the Institute of Industrial and Systems Engineers (IISE).

Saleh Javadiمشاهده پروفایل

مدرس ارشد

• Systems engineering
• Signal processing
• Machine learning
• +۱ مورد دیگر

Saleh Javadi is a Senior Lecturer at the Department of Mathematics and Natural Sciences at Blekinge Institute of Technology (BTH) in Karlskrona, Sweden. He is actively engaged in research and teaching within the field of systems engineering. His educational background includes: B.Sc. in Electrical-Control Engineering from Amirkabir University of Technology (2009) M.Sc. in Electrical, Electronic and Systems Engineering from The National University of Malaysia (2013) Ph.D. in Systems Engineering from Blekinge Institute of Technology (BTH) (2021) Saleh Javadi's research focuses on signal processing, machine learning, and computer vision , with applications spanning remote sensing, intelligent transportation systems, and AI-driven industrial optimization. His work bridges theoretical advancements with practical implementations, particularly in SAR imagery analysis, drone-based agricultural monitoring, and traffic surveillance systems. His recent publications demonstrate a strong focus on remote sensing technologies, particularly Synthetic Aperture Radar (SAR) image processing and analysis. There's a clear trend toward applying machine learning techniques to solve complex problems in aerial and satellite imagery, traffic monitoring, and agricultural applications. His research shows interdisciplinary connections between computer vision, signal processing, and practical engineering applications. Saleh Javadi has received significant recognition for his innovative work: Innovator of the Year award (SKAPA – Innovation Prize in Memory of Alfred Nobel) in Blekinge for innovative efforts in optimizing and reducing energy consumption in industries by using artificial intelligence ÅForsk Entrepreneur's prize at the Swedish Innovation Council Day – Swedish Incubators & Science Park's annual conference in May 2019 Dr. Javadi is involved in practical applications of his research through projects such as "Artificiell intelligens AI kan reducera ogräsfrön i utsäde" (ongoing) and "Bekämpa Renkavle med hjälp av drönare och Artificiell Intelligens (AI)" (completed). His work demonstrates a strong commitment to translating academic research into real-world solutions that address industrial and environmental challenges. His research appears to be conducted within a collaborative framework, working with colleagues on drone technology, SAR image analysis, and AI applications across multiple domains including agriculture, maritime monitoring, and transportation systems.

Todd Millsteinمشاهده پروفایل

استاد

• Network Verification
• Programming Languages
• Probabilistic Programming
• +۳ مورد دیگر

Todd Millstein is a Professor in the Computer Science Department at the University of California, Los Angeles (UCLA). He served as the Computer Science Department Chair from 2022-2025 and is also an Amazon Scholar. His research focuses on making software systems more reliable through programming languages techniques, with significant contributions to network verification and probabilistic programming. Millstein received his Ph.D. from the University of Washington Department of Computer Science, where he was a member of the Cecil group led by Craig Chambers. Prior to that, he completed his undergraduate studies at Brown University under the guidance of Paris Kanellakis and Pascal Van Hentenryck. Millstein's research spans several areas of programming languages and systems with a focus on reliability. He has made significant contributions to network verification, developing the Batfish network configuration analyzer which is now managed by Amazon Web Services and forms the basis of Oracle Cloud's Network Path Analyzer. His work has been recognized with the ACM SIGCOMM Networking Systems Award in 2025. He also works on interactive program verification through lemma synthesis and scalable reasoning methods for probabilistic programming languages. His research bridges programming languages theory with practical systems challenges, as highlighted in his SPLASH/OOPSLA 2024 keynote "Everything is a Program (even if it's not)". Millstein's recent publications demonstrate a consistent focus on verification and reliability across multiple domains. His work shows a progression from foundational programming language techniques to practical applications in networking and probabilistic systems. Key themes include data-driven approaches to program analysis, synthesis of verification artifacts, and applying programming languages techniques to non-traditional domains like network configuration. Millstein's scientific achievements have been recognized with numerous prestigious awards including an NSF CAREER Award, an ACM SIGPLAN Most Influential PLDI Paper Award, an ACM SIGCOMM Networking Systems Award, IEEE Micro Top Picks selection, best-paper awards from PLDI, OOPSLA, and SIGCOMM, a Microsoft Research Outstanding Collaborator Award, an Okawa Foundation Research Grant, an IBM Faculty Award, and a Facebook Research Award. He has also received both the Northrop Grumman Excellence in Teaching Award (for junior faculty) and the Eon Instrumentation Inc. Excellence in Teaching Award (for senior faculty) from UCLA Engineering. Millstein advises several Ph.D. students including Ana Brendel, Poorva Garg (co-advised with Guy Van den Broeck), Rajdeep Mondal (co-advised with George Varghese), and Rathin Singha (co-advised with George Varghese). His research has been supported by various grants including an NSF CAREER Award, Okawa Foundation Research Grant, IBM Faculty Award, and Facebook Research Award. He has also been a Co-Founder and Chief Scientist of Intentionet, which was later acquired by Amazon Web Services. Millstein is actively involved in the Batfish project, an open-source network configuration analyzer that has had significant practical impact. Batfish is now managed by AWS, powers Oracle Cloud's Network Path Analyzer, and is used by dozens of companies. His research group continues to work on network reliability, developing techniques for scalable BGP policy verification and behavioral testing of protocol implementations.

Elizabeth Mayer-Davisمشاهده پروفایل

استاد

• Diabetes Epidemiology
• Type 1 Diabetes
• Type 2 Diabetes
• +۶ مورد دیگر

Elizabeth "Beth" Mayer-Davis is the Dean of The Graduate School and the Cary C. Boshamer Distinguished Professor of Nutrition and Medicine at the University of North Carolina at Chapel Hill. She holds joint appointments in the Gillings School of Global Public Health and the School of Medicine, where she previously served as Chair of the Department of Nutrition for eight years. As Dean of The Graduate School, she oversees more than 160 degree-offering programs and over 10,000 graduate students at UNC Chapel Hill. Dr. Mayer-Davis earned her educational credentials from prestigious institutions: Ph.D. in Epidemiology from the University of California, Berkeley (1992) Master of Public Health with honors from the University of Colorado School of Medicine (1986) B.S. in Dietetics from the University of Tennessee (1980) Dr. Mayer-Davis is an internationally recognized expert in diabetes research with a career focused on the epidemiology and natural history of type 1 and type 2 diabetes in children and adults. Her research addresses how nutrition impacts diabetes risk and complications, with particular emphasis on culturally and regionally diverse populations. Her primary current focus is on type 1 diabetes in youth and young adults, examining diabetes self-management and energy balance/weight management for individuals with type 1 diabetes. She employs innovative methodologies including large epidemiological studies, clinical trials, and adaptive intervention designs, often incorporating communication technologies to enhance patient-centered care. Analysis of Dr. Mayer-Davis's recent publications reveals consistent focus on diabetes epidemiology across diverse populations, with particular attention to youth-onset diabetes, health disparities by race and ethnicity, and innovative interventions for diabetes management. Her work frequently addresses the intersection of obesity and diabetes, particularly in type 1 diabetes where this comorbidity has been historically understudied. The research demonstrates methodological sophistication through the use of advanced statistical techniques, continuous glucose monitoring data, and adaptive trial designs to address complex questions in diabetes care. Dr. Mayer-Davis has received numerous professional honors and appointments: Cary C. Boshamer Distinguished Professorship at UNC President for Health Care and Education for the American Diabetes Association (2011) Member of the 2020 Dietary Guidelines Advisory Committee Appointee to President Obama's Advisory Group on Prevention, Health Promotion and Integrative and Public Health Co-director of the Nutrition Obesity Research Center funded by NIH Throughout her career, Dr. Mayer-Davis has been deeply committed to mentoring the next generation of researchers, having supervised dozens of graduate students. She has secured over $45 million in research funding, including as Principal Investigator for the Carolina site of the landmark SEARCH for Diabetes in Youth study and the Nutrition for Precision Health Consortium initiative. Her leadership extends to national scientific committees and professional organizations, where she has shaped diabetes research and care standards. She is particularly dedicated to promoting diversity, equity, and inclusion in graduate education and research. Dr. Mayer-Davis co-directs the UNC Nutrition Obesity Research Center, a NIH-funded center that has received continued support through multiple funding cycles. She also leads the Carolina site of the SEARCH for Diabetes in Youth study, a large multi-center national study that has been tracking diabetes incidence and trends in youth for over two decades. Her research team includes epidemiologists, nutritionists, statisticians, and clinicians working collaboratively to address critical questions in diabetes prevention and management.

Jonathan Ragan-Kelleyمشاهده پروفایل

استادیار

• High-Efficiency Visual Computing
• Compilers
• Computer Architecture
• +۳ مورد دیگر

Jonathan Ragan-Kelley is the Esther and Harold E. Edgerton Assistant Professor of Electrical Engineering & Computer Science at MIT and an Assistant Professor of EECS at UC Berkeley. He leads the Visual Computing group at CSAIL, focusing on high-efficiency visual computing, compilers, and architectures for image processing, machine learning, and 3D rendering. His research bridges systems, compilers, and hardware design, emphasizing scalable solutions for computational challenges. Education: PhD in Computer Science from MIT (2014), postdoc at Stanford University, and visiting researcher at Google. He co-created the Halide language and has developed multiple domain-specific languages (DSLs) and compiler systems. Research interests include compiler optimization, scheduling languages (e.g., Exo), and efficient computing frameworks. He has received awards such as the NSF CAREER Award and ACM SIGGRAPH’s Significant New Researcher Award. Awards: ACM SIGGRAPH Award, NSF CAREER, Intel Outstanding Researcher Award Key Contributions: Halide compiler framework, Exo scheduling language, machine learning acceleration techniques Labs/Teams: Visual Computing at MIT CSAIL

Wout Josephمشاهده پروفایل

استاد

• electromagnetic field exposure assessment
• in-body electromagnetic field modelling
• electromagnetic medical applications
• +۱۲ مورد دیگر

Wout Joseph is a Professor in the domain of Experimental Characterization of wireless communication systems at Ghent University (Belgium), where he has been working since October 2009. He is also an IMEC Principal Investigator since 2017. His research is conducted within the wireless, acoustics, environment & expert systems (WAVES) research unit at the Department of Information Technology (INTEC). Dr. Joseph was born in Ostend, Belgium on October 21, 1977. He received his M.Sc. degree in electrical engineering from Ghent University in July 2000. From September 2000 to March 2005 he was a research assistant at the Department of Information Technology (INTEC), where his scientific work focused on electromagnetic exposure assessment around base stations for mobile communications related to health effects. This work led to his Ph.D. degree in March 2005. Professor Joseph's research expertise spans multiple domains within wireless communications and bioelectromagnetics. His primary research interests include electromagnetic field exposure assessment, in-body electromagnetic field modeling, electromagnetic medical applications, propagation for wireless communication systems, IoT, antennas and calibration. He also specializes in wireless performance analysis, industry 4.0 applications, wireless localization, and Quality of Experience metrics. His work is particularly notable for its focus on dosimetric studies in the radiofrequency range, where his research is ranked first in number of peer-reviewed studies. His research has practical applications in wireless network planning, occupational safety, and public health policy related to electromagnetic fields. His extensive publication record (over 886 publications with an h-index of 45 in ISI Web of Science and 66 in Google Scholar) demonstrates a clear trajectory from fundamental electromagnetic field measurements to applied research in industrial wireless networks and bioelectromagnetic applications. Recent work shows a strong emphasis on 5G exposure assessment across multiple European countries, millimeter-wave channel modeling, and the application of machine learning techniques to exposure assessment and wireless localization. EBEA council board member (2015-2018) EBEA board member at large (2019) Bioelectromagnetics Society board member (2022) Bioelectromagnetics Society board member (2024) 24 research awards Professor Joseph leads significant research efforts in electromagnetic field exposure assessment, with particular emphasis on developing measurement methodologies and computational models for real-world exposure scenarios. His work bridges theoretical electromagnetic modeling with practical applications in wireless communications and bioelectromagnetics. His research group within the WAVES unit is highly active in both theoretical and experimental aspects of wireless communications and bioelectromagnetics, with current projects focusing on 5G exposure assessment across Europe, millimeter-wave channel modeling for data centers and industrial environments, and the development of novel exposure assessment methodologies using advanced signal processing and machine learning techniques.

• Project Management
• Healthcare Decision Making
• Public-Private Partnerships
• +۳ مورد دیگر

Geert Dewulf is a Professor at the University of Twente, specializing in project governance, public-private partnerships (PPPs), and healthcare decision-making. His research focuses on strategic decision support systems, uncertainty management in healthcare organizations, and adaptive governance frameworks. He has contributed to over 215 publications and supervised 21 students. Key areas of expertise include infrastructure development, construction management, and institutional logics in extended enterprises. Research interests span dynamic decision-making models, stakeholder network dynamics, and the integration of real options and scenario planning in strategic management. He has received awards such as the Best Paper at the 14th Engineering Project Organization Conference and recognition for contributions to community-engaged research in construction management. Education: Not explicitly stated in the provided text. Affiliations: Member of the VISICO Center at the University of Twente, engaged in editorial roles for journals like Engineering Project Organization Journal. Labs/Teams: Associated with interdisciplinary teams focused on healthcare infrastructure and PPP governance. His work addresses challenges in healthcare asset management, resilient infrastructure planning, and fostering collaboration in complex projects. Recent contributions include frameworks for adaptive decision support and serious games for reflecting on partnership dynamics in concessions.

• Optimization Algorithms
• Evolutionary Algorithms
• Machine Learning
• +۴ مورد دیگر

Rafał Biedrzycki is an Assistant Professor at The Institute of Computer Science within Warsaw University of Technology's Faculty of Electronics and Information Technology. His research focuses on optimization algorithms, evolutionary computation, and machine learning applications. He holds a PhD in Information Science (2009) and a D.Sc. (2024). Key research interests include evolutionary algorithms (e.g., Differential Evolution, CMA-ES), optimization techniques for real-world problems (e.g., compressor scheduling, optical networks), and algorithm benchmarking. He has contributed to improving constraint-handling methods and hybrid algorithm designs. Received team awards for scientific achievements from Warsaw University of Technology (2019, 2023) and teaching excellence (2021, 2024). Active in interdisciplinary projects, including the DAFNE initiative for data fusion systems (2010-2011). Supervises research in optimization, machine learning, and computational electromagnetics. His work bridges theoretical algorithm development with practical applications in engineering and data analysis. Recent efforts include analysis of CEC competition algorithms and parameter-tuning methodologies.

Aviad Rubinsteinمشاهده پروفایل

استادیار

• Algorithms
• Complexity Theory
• Game Theory
• +۳ مورد دیگر

Aviad Rubinstein is an Assistant Professor of Computer Science at Stanford University, specializing in theoretical computer science with a focus on algorithms, complexity, and game theory. He has taught courses such as Design and Analysis of Algorithms (CS161), Incentives in Computer Science (CS269i), and Topics in Intractability (CS354). His research interests include approximation algorithms, computational complexity, and fair division, with notable work on envy-free cake-cutting and prophet inequalities. He advises several PhD students including Joshua Brakensiek and Ruiquan Gao, and mentors postdocs like Soheil Behnezhad. His undergraduate mentoring includes students from Tsinghua and Berkeley. Rubinstein has received the Kalai Prize from the Game Theory Society and a FOCS Best Paper Award for his work on inapproximability of Nash equilibria. Rubinstein co-authored Algorithms for Toddlers with Mary Wootters, a book simplifying computational concepts for younger audiences. He also organizes workshops on topics like fine-grained complexity and early career mentoring in computer science. Beyond academia, he consults part-time for the blockchain startup Lava. His research frequently bridges theoretical foundations with practical implications, such as developing algorithms with real-world applications in auctions, mechanism design, and optimization under constraints.

Lin Caiمشاهده پروفایل

استاد

• Wireless Communications
• Networking
• Mobile Computing
• +۷ مورد دیگر

Lin Cai is a Professor in the Department of Electrical & Computer Engineering at the University of Victoria, Canada. She holds prestigious fellowships including NSERC Steacie, IEEE, CAE, and Royal Society of Canada. Her research focuses on wireless communications, networking, and mobile computing, with emphasis on protocols for multimedia and IoT systems. She has led projects in vehicular networks, UAV-assisted systems, and federated learning for edge intelligence. Dr. Cai has advised over 20 students, many of whom have received awards and prominent roles in academia and industry. She has authored numerous high-impact papers, secured grants from NSERC, CFI, and industry partners, and serves in leadership roles at IEEE and educational institutions. Notable contributions include work on congestion control, network security, and autonomous systems. Education: BEng (Nanjing U. of Sci. & Tech.), MASc/PhD (University of Waterloo) Affiliations: IEEE Vehicular Technology Society Board of Governors, IEEE ComSoc Distinguished Lecturer Awards: 2020 IEEE N2Women 'Star in Networking', RSC Fellow 2024, Best Paper Awards (ICC 2008, WCNC 2011) Research Labs: Connected Autonomous Vehicles (CAV) Lab, AI-driven Networking Group Her work integrates networking, AI, and control theory to address challenges in 6G, IoT, and smart transportation. She actively promotes diversity through initiatives like the 'Riko-chan' STEM manga series.

• Hyperspectral Imaging
• Computer Vision
• Pattern Recognition
• +۳ مورد دیگر

Jun Zhou is Professor and Deputy Head of School (Research) at Griffith University's School of Information and Communication Technology. His research specializes in hyperspectral imaging, computer vision, and pattern recognition with applications in agriculture, environmental monitoring, and remote sensing. Zhou leads significant projects including the ARC Research Hub for Driving Farming Productivity and Disease Prevention. His work develops innovative computer vision systems for agricultural automation, environmental conservation, and industrial quality control. He has received the ARC Discovery Early Career Researcher Award and secured extensive research funding from ARC, CSIRO, and industry partners. Zhou's publications demonstrate consistent contributions to hyperspectral image analysis, object tracking, and deep learning applications. As Deputy Director of the ARC Industrial Transformation Research Hub, he coordinates multi-institutional research teams developing AI-powered solutions for farming productivity and disease prevention.

Srinivas Narayanaمشاهده پروفایل

استادیار

• Computer Networks
• Formal Verification
• Compilers
• +۴ مورد دیگر

Srinivas Narayana is an Assistant Professor in the Department of Computer Science at Rutgers University, specializing in programmable networking, formal verification, and systems research. He holds a PhD from Princeton University and a B.Tech from IIT Madras, with postdoctoral work at MIT. His research focuses on building safe, high-performance networks through optimizing compilers, verified programming, and distributed system monitoring. He has received NSF grants, the CGO 2022 Distinguished Paper Award, and the 2017 SIGCOMM Best Paper Award. Education: PhD and MA in Computer Science, Princeton University (2016) B.Tech in Computer Science, IIT Madras (2010) Postdoctoral Research, MIT (2018) Research Interests: His work bridges networking and systems with a focus on compilers, formal methods, and programmable hardware. Notable projects include K2 compiler for eBPF, the eBPF verifier soundness work, and congestion control mechanisms like CCP. He explores parallel packet processing, privacy-preserving analytics, and load balancing strategies. Grants & Awards: NSF Awards #2422076, #1910796, #2019302 eBPF Foundation Grant Facebook Networking Research Award Network Programming Initiative (NPI) Funding Lab & Teams: Leads the NetSys group at Rutgers, collaborating with teams on projects like the eBPF verifier, verified packet processing, and network monitoring tools like Marple. His lab emphasizes open-source contributions and industry collaboration.

Sagar Samtaniمشاهده پروفایل

دانشیار

• Artificial Intelligence for Cybersecurity
• Cyber Threat Intelligence
• Deep Learning
• +۵ مورد دیگر

Sagar Samtani is an Associate Professor and Weimer Faculty Fellow at the Kelley School of Business , Indiana University. He serves as Director of the Kelley’s Data Science and Artificial Intelligence Lab (DSAIL) . His research focuses on Artificial Intelligence for Cybersecurity , including cyber threat intelligence, deep learning, and dark web analytics. He holds a PhD from the University of Arizona (2018), and has received prestigious awards such as the Indiana University Outstanding Junior Faculty Award (2023) and IEEE Big Data Security Junior Research Award (2023). Education : PhD in Information Systems, University of Arizona, 2018 MSMIS, University of Arizona, 2014 BSBA, University of Arizona, 2013 Research Interests : Samtani’s work addresses cybersecurity challenges through AI, including proactive threat detection, vulnerability assessment, and healthcare analytics. He emphasizes explainable AI (XAI) for transparency in cybersecurity systems. Grants & Awards : NSF Grant: CyberCorps SFS Program ($2.3M, 2020–2025) NSF Grant: AI4Cyber Research Education ($300K, 2020–2022) Multiple teaching awards, including the Trustees Teaching Award (2023) and recognition as one of Top 50 Undergraduate Professors (2022) Labs & Teams : Leads the DSAIL lab, focusing on AI-driven solutions for business and cybersecurity. Collaborates with NSF-funded initiatives on cyber AI education and threat intelligence.

Amir Giladمشاهده پروفایل

استادیار

• Responsible Data Science
• Causal Inference
• Differential Privacy
• +۵ مورد دیگر

Amir Gilad is a Scharf-Ullman endowed Assistant Professor (Senior Lecturer) at the Hebrew University of Jerusalem’s School of Computer Science and Engineering. His research focuses on responsible data science, including causal inference, differential privacy, fairness in data, and tools for data analysis. He holds a Ph.D. in Computer Science from Tel Aviv University, where he was advised by Prof. Daniel Deutch. Prior to this, he was a postdoctoral researcher at Duke University, mentored by Prof. Sudeepa Roy, Prof. Ashwin Machanavajjhala, and Prof. Jun Yang. Education: Ph.D. in Computer Science, Tel Aviv University (Advisor: Daniel Deutch) MSc in Computer Science, Tel Aviv University BSc in Mathematics and Computer Science, Tel Aviv University His research interests span data quality assessment, private and fair data generation, and causal inference applications . He has received notable awards, including the 2024 Alon Scholarship and the 2019 Google Ph.D. Fellowship. Recent Projects: Developing algorithms for data quality repair and assessing bias in datasets Generating differentially private data that satisfies fairness constraints Applying causal inference to enhance data analysis tools Awards and Honors: 2024 Alon Scholarship for Outstanding Faculty Integration 2019 Google Ph.D. Fellowship in Structured Data 2018 SIGMOD Research Highlight Award 2017 VLDB Best Paper Award Teaching: Courses include “Topics in Responsible Data Science” and “Seminar on Causal Inference in Data Analysis” at Hebrew University, and “Extended Introduction to Computer Science” at Tel Aviv University. He has also led workshops on Google Technologies. Labs & Teams: His work is centered around the School of Computer Science and Engineering’s database group, focusing on foundational and applied aspects of privacy-aware data systems.