جست‌وجوی استاد و پژوهشگر

Heejung Bangمشاهده پروفایل

استاد

• Biostatistics
• Epidemiology
• Health Policy
• +۵ مورد دیگر

Heejung Bang, Ph.D., serves as Professor in the Department of Public Health Sciences at the University of California, Davis School of Medicine. Her academic career spans biostatistics, epidemiology, and health policy with expertise in clinical trial methodology, cost-effectiveness analysis, and predictive modeling for medical decision-making. Dr. Bang's educational foundation includes: B.S. from Ewha Women's University, Seoul, South Korea (1995) M.S. in Statistics from North Carolina State University (1997) Ph.D. in Statistics from North Carolina State University (1999) Postdoctoral Fellowship in Biostatistics & Epidemiology at Harvard School of Public Health (1999-2001) Her research program integrates advanced statistical methods with clinical applications across diverse medical fields. Current work focuses on optimizing screening protocols, evaluating healthcare costs, and developing prediction models for conditions including diabetes, kidney disease, and surgical outcomes. Methodological innovations in blinding assessment and handling censored data represent significant contributions to clinical trial science. Recent publications demonstrate consistent leadership in biostatistical methodology applied to real-world health challenges. Key trends include development of risk prediction tools for dialysis patients, analysis of opioid prescribing patterns, and evaluation of surgical outcomes. Her work bridges statistical theory with clinical practice across reproductive medicine, endocrinology, nephrology, and pain management. Dr. Bang's scholarly recognition includes: Dean’s Team Award for Excellence at UC Davis (2012) Young Investigator Award from the American Statistical Association (2001) Multiple national student awards including ENAR Travel Award and Gertrude M. Cox Academic Achievement Award While specific grant details aren't provided in available sources, her extensive publication record in high-impact medical journals indicates sustained research funding. Dr. Bang actively collaborates with clinical researchers across specialties, evidenced by co-authorship on studies spanning emergency medicine, endocrinology, and surgical disciplines. Her team-based approach was recognized through the Dean's Team Award for Excellence at UC Davis. As a core faculty member in Public Health Sciences, Dr. Bang contributes to the School of Medicine's research infrastructure through methodological consultation and statistical leadership. Her work supports evidence-based decision-making across the UC Davis Health system and national healthcare policy discussions.

Xavier Leroyمشاهده پروفایل

استاد

• Formal verification
• Programming languages
• Functional programming
• +۵ مورد دیگر

Xavier Leroy is a Professor at the Collège de France , holding the Software Science chair. His research focuses on enhancing software reliability, safety, and security through mathematically rigorous approaches like formal semantics, program logic, and deductive systems. He is a key member of the Cambium project-team , a joint venture with Inria, advancing formal verification methods and programming language design. Education: École normale supérieure and Université Paris-Diderot (PhD in 1992), postdoc at Stanford University. Research Themes: Type systems, deductive verification, shared-memory parallelism, weakly consistent memory models, and secure computing on encrypted data (2025 lecture series). Major Contributions: Architect of the OCaml functional programming language and CompCert, a formally verified compiler for mission-critical embedded software. Leroy previously served as Research Director at Inria (2000–present via Cambium) and led the Gallium research team (2006–2019). His work bridges theoretical foundations (e.g., Curry-Howard correspondence) with practical tools for secure software development.

Kay Ashaoluمشاهده پروفایل

مدرس

• Software Engineering Education
• Early-Career Talent Development
• Entrepreneurship
• +۳ مورد دیگر

Kay Ashaolu is a Continuing Lecturer at the UC Berkeley School of Information, where he teaches courses like Front-End Web Architecture and Back-End Web Architecture (2015–2025). Concurrently, he works as an Engineering Manager at Pinterest, with prior roles at the Centers for Medicare & Medicaid Services and Ancestry. Education : B.S.E. in Electrical Engineering (Computer Systems & Software concentration) from Princeton University (2007); M.I.M.S. from UC Berkeley School of Information (2013). Kay’s research focuses on scalable software engineering education frameworks and the impact of AI on early-career engineers . He advocates for team-oriented peer learning and case-study methodologies inspired by MBA models to bridge academic instruction and industry demands. His work emphasizes equipping junior engineers to navigate AI-driven tools and dynamic professional environments.

Jackson Andersonمشاهده پروفایل

استاد پژوهشی

• Ferroelectric Materials
• Piezoelectric Materials
• Semiconductor Engineering
• +۳ مورد دیگر

Jackson Anderson is a Research Professor in the Department of Electrical and Biomedical Engineering at the University of Vermont (UVM), part of the College of Engineering and Mathematical Sciences. He joined UVM in 2023 to contribute to initiatives addressing semiconductor workforce gaps, establishing microelectronics teaching and research laboratories. His research focuses on ferroelectric and piezoelectric materials, their integration into electrical/mechanical devices, and commercial fabrication processes for enhanced circuit efficiency. Anderson holds a PhD (2023) in Electrical and Computer Engineering from Purdue University, an MS (2017) and BS (2015) in Microelectronic Engineering from Rochester Institute of Technology. He interned at GlobalFoundries and IBM Microelectronics, focusing on in-line testing, yield analysis, and data analytics in semiconductor manufacturing. He teaches courses on semiconductor materials/devices (EE 3440/5440, PHYS 3675/5675) and IC fabrication (EE 3420, PHYS 3165). His GitHub repositories (e.g., PyMeasRF ) demonstrate expertise in Python-based RF measurement automation and ferroelectric material data analysis. Recent work includes advancing 2D ferroelectric semiconductors for acoustoelectric circulators and developing ultrathin transistor technologies with GHz performance. Collaborations emphasize bridging materials research with practical semiconductor fabrication challenges.

Vladimir Milovanovićمشاهده پروفایل

دانشیار

• Electrical Engineering
• Computer Science
• Signal Processing
• +۷ مورد دیگر

Dr. Vladimir Milovanović is an Associate Professor at the Faculty of Engineering, University of Kragujevac, Serbia, holding a position as Chair of the Department of Electrical Engineering and Computer Sciences. His academic career is anchored in interdisciplinary research at the intersection of electrical engineering, computer science, and biomedical applications. His research focuses on hardware design, radar sensor systems, biomedical signal processing, and machine learning applications. Notable areas include CMOS circuit design, FPGA-based implementations, and parameterizable hardware generators for signal processing tasks. He also explores medical imaging analysis using deep learning techniques for conditions like disc hernia diagnosis. Recent work emphasizes radar technology (FMCW transceivers, signal processing architectures), embedded systems (FPGA development, IP core utilization), and high-performance streaming data algorithms. His publications span over two decades, demonstrating expertise in analog/digital circuit design, comparative classifier analysis in biomedical contexts, and hardware-software co-design methodologies. Dr. Milovanović collaborates with industry on energy-efficient MIMO arrays and semiconductor gas sensors. His contributions include open-source HDL models for digital signal processors and comparator circuits optimized for low-power and high-speed applications.

Marin Kalužaمشاهده پروفایل

استاد

• Databases
• Software Engineering
• Computer Science
• +۴ مورد دیگر

Marin Kaluža is a Professor of Professional Studies at Veleri University, holding a permanent position. His expertise spans Database Systems, Software Engineering, and Information Technology . He teaches courses in Databases, Distributed Systems, Programming Practices, and Software Engineering Methodologies. His research focuses on database compliance standards, blockchain consensus algorithms, web application frameworks, and cloud migration strategies. He actively publishes in peer-reviewed journals, with notable work on SQL standard adherence, React vs Vue.js framework comparisons, and IoT educational systems. Dr. Kaluža advises students on practical software development projects and maintains an active research agenda in data modeling techniques and cybersecurity for CMS platforms. His contributions include pioneering methodologies for business system complexity estimation and RESTful web service architecture design. He is accessible for student consultations on Mondays and Thursdays, and via mobile during work hours. Teaching Responsibilities: Databases, Software Engineering, Programming Practicum Key Research Themes: Database Standards, Cross-Platform Development, Cloud Migration Notable Projects: Veleri-OI IoT School Meteo System, Knowledge-Based Data Modeling Framework Though no formal awards are listed, his extensive publication record (over 50 articles since 2002) demonstrates sustained academic contribution to IT education and applied research.