جست‌وجوی استاد و پژوهشگر

David L Brownمشاهده پروفایل

استاد بالینی

• Cardiovascular Medicine
• Interventional Cardiology
• Outcomes Research
• +۳ مورد دیگر

David L. Brown, MD is a Clinical Professor of Medicine in the Division of Cardiovascular Medicine at the Keck School of Medicine of USC. A general cardiologist specializing in interventional cardiology, he has extensive experience in critical care cardiology, consultative cardiology, and outpatient cardiology. His career spans over 40 years with over 300 publications, 8,500 citations (h-index 37), and four edited textbooks, including the leading Cardiac Intensive Care . He holds editorial board positions at JAMA Internal Medicine and mentors ~50 trainees annually. Education : Bachelor’s degree from University of Texas MD from Baylor College of Medicine Internal Medicine residency and chief residency at Baylor Cardiology fellowship at UCSF Interventional cardiology fellowship at Cleveland Clinic Research Interests : Outcomes research in cardiovascular disease, particularly addressing knowledge gaps arising from clinical practice. Focus areas include coronary artery disease management, revascularization strategies, and the clinical utility of diagnostic tools like coronary calcium scoring. His work emphasizes evidence-based practices and patient-centered outcomes. Articles Trends : Recent work analyzes long-term outcomes of transcatheter vs. surgical aortic valve replacement, critiques trial design biases in chronic coronary syndrome management, and explores obesity’s impact on coronary physiology. His meta-analyses highlight controversies in revascularization efficacy and surrogate endpoint reliability. Awards : Not explicitly listed, but recognized for textbook contributions and mentorship. Advising/Grants : Mentor to 50+ trainees (medical students, residents, fellows). Active in grant-funded research on cardiovascular outcomes and diagnostic techniques. Labs/Teams : Engaged in collaborative research networks analyzing cardiovascular interventions and outcomes, including contributions to the STICH trial follow-up and meta-analyses in interventional cardiology.

• Computer Science
• Programming Languages
• Software Engineering
• +۳ مورد دیگر

Xinyu Wang is a Research Fellow at the University of Michigan's Department of Physics, affiliated with the School of Literature, Science, and the Arts (LSA). Their primary office is located in the Randall Laboratory, and they are also associated with the Homer A. Neal Lab. Wang's work focuses on advancing program synthesis techniques, web automation systems, and data-driven methodologies to enhance software development and user interaction. Their research addresses challenges in SQL query verification, cloud computing simplification, and integrating human feedback into automated processes. While specific educational background details are not provided in the text, Wang's research demonstrates expertise in computer science, programming languages, and software engineering. Their projects include developing tools like VeriEQL for SQL equivalence verification, Miwa for user-controlled web automation, and SlabCity for query optimization. These efforts highlight a trend toward creating systems that blend formal methods with practical usability. Key Research Themes: Program synthesis, compiler design, database systems, human-computer interaction, neurosymbolic AI, and automated workflows Wang’s contributions include innovations in data structure refinement, cloudless computing architectures, and tensor transformation tools. Their work often emphasizes reliability, user confidence, and scalable solutions. No formal advisees or grants are explicitly listed in the provided texts. However, their involvement in advising resources like 'Advising Career Resources' suggests a role in supporting academic and professional development within the department. Wang collaborates with labs and teams focused on physics and computational sciences, contributing to interdisciplinary projects. Their contact information includes the email wongxy@umich.edu and office phone numbers 734-764-4437 and 734-763-9694.

Arjun Radhakrishnaمشاهده پروفایل

پژوهشگر

• Program Synthesis
• Formal Methods
• Concurrent Programming
• +۲ مورد دیگر

Dr. Arjun Radhakrishna is a Researcher at Microsoft in the PROSE team, specializing in program synthesis and formal methods . His work focuses on developing tools to ensure correctness and optimize soft specifications like performance and energy consumption in concurrent and embedded systems. He previously held post-doctoral positions at the University of Pennsylvania and completed his PhD at IST Austria under Prof. Thomas Henzinger.

Mark Santolucitoمشاهده پروفایل

استادیار

• Program Synthesis
• Computer Music
• DevOps
• +۴ مورد دیگر

Mark Santolucito is an Assistant Professor of Computer Science at Barnard College, Columbia University. He holds a PhD in Computer Science from Yale University, where his research focused on program synthesis and computer music. His current work explores program synthesis techniques to enhance programmer productivity, particularly in lowering barriers to entry for underrepresented groups and optimizing workflows for advanced developers. He leads the Barnard PL (Programming Languages) Labs, which develops tools like TSL (Temporal Stream Logic) for synthesizing reactive systems and analyzing infrastructure-as-code (IaC). His research intersects formal methods with creative applications in music and live coding, emphasizing accessibility and usability. Education: PhD in Computer Science (Yale University), focusing on program synthesis and computer music. Research interests include program synthesis, temporal logic specifications, infrastructure configuration analysis, and music technology. He emphasizes human-centered design in his work, aiming to make programming more accessible through tools like TSL and interactive synthesis environments. Projects include TSL Move Cube, Block-based Editor for Temporal Logic, and Spiral Analysis for medical software migration. Notable contributions include developing TSL synthesis pipelines, optimizing Arduino configurations, and exploring static analysis for cost prediction in cloud deployments. His work bridges theoretical foundations with practical applications in both software engineering and creative computing. Labs/Teams: Leads Barnard PL Labs, collaborating on projects like TSL Synthesis Engine and Static Analysis for IaC. Active in workshops such as SEConfig and FMCAD.

María Celeste Sanches Soaresمشاهده پروفایل

پژوهشگر

• Fashion Design
• Contemporary Creation
• Audiovisual Communication
• +۴ مورد دیگر

María Celeste Sanches Soares is a researcher and academic affiliated with Nebrija University, School of Communication and Arts, where she contributes to the field of Audiovisual Communication and Advertising. She is a member of the ETCC Nebrija Research Group on Transversal Studies in Contemporary Creation, reflecting her engagement in interdisciplinary research in contemporary design and media. Her research focuses on fashion design education and the methodological frameworks guiding form synthesis in design practice. Key interests include the pedagogy of intangible aspects in fashion design, creative processes, and innovative teaching strategies in design education. She earned her PhD from the Universitat Politècnica de València in 2016 with a thesis titled O projeto do intangível na formação de designers de moda: repensando as estratégias metodológicas para a sintaxe da forma na prática projetual , supervised by Dr. Bernabé Hernandis Ortuño and Dr. Sergio Regis Moreira Martins. While no scientific awards or publications are listed in the provided text, her affiliation with a dedicated research group indicates active scholarly involvement. There is no indication of student advisement in the available information. She is associated with research teams exploring transversal approaches in contemporary creation, particularly at the intersection of design, communication, and artistic practice.

• Satisfiability Modulo Theories (SMT)
• Formal Verification
• Automated Reasoning
• +۳ مورد دیگر

Andrew Joseph Reynolds is a Research Scientist at the University of Iowa , actively contributing to the development of the SMT solver cvc5 . He is a core developer in the Computational Logic Center (CLC) and focuses on improving SMT solvers for unbounded strings, regular expressions, proofs, quantified formulas, and synthesis conjectures. Research Interests : Satisfiability Modulo Theories (SMT), Formal Verification, Automated Reasoning, Quantifier Instantiation, String Constraints, Synthesis Algorithms Scientific Contributions include groundbreaking work in distributed SMT solving, proof reconstruction, and nonlinear arithmetic handling. His publications span premier conferences like FMCAD, CAV, IJCAR, and TACAS, with multiple best paper awards and competition wins. Major Competitions won: SMT Comp (multiple years), SyGuS Comp (General track, Conditional Linear Integer Arithmetic), CASC (typed first-order divisions) He serves on program committees for conferences like FroCoS, LPAR, FMCAD, and SMT, and has organized workshops including the SyGuS Comp 2019 and 2018 FMCAD Student Forum . His work is funded by NSF grants and involves collaboration with leading institutions.

Xiaokang Qiuمشاهده پروفایل

دانشیار

• Programming Languages
• Software Engineering
• Program Verification
• +۶ مورد دیگر

Xiaokang Qiu is an Associate Professor at the Elmore Family School of Electrical and Computer Engineering , Purdue University , with a Ph.D. in Computer Science from University of Illinois at Urbana-Champaign (2013). His research focuses on Programming Languages and Software Engineering , particularly theories, algorithms, and tools for program synthesis, verification, and logic-based analysis. Research Interests His work addresses: Formal methods for heap-manipulating programs using separation logic Automated deduction and decision procedures for data structures Syntax-guided synthesis of concurrent and bit-vector programs Integration of machine learning with formal verification Scalable verification of hardware memory consistency Network protocol optimization through program synthesis Recent Publications Recent work includes PLDI 2025 on concurrent string synthesis, POPL 2024 on bit-vector synthesis, and POPL 2023 on comparative network design. His tools like STRAND and VCDryad enable automated verification of complex data-structure manipulations. Grants & Awards Recipient of: NSF SHF Small Award (2024, co-PI, $593K) NSF FMitF Award (2023, PI, $750K) Tenure at Purdue (2023) Professional Service Active in program committees for PLDI , POPL , CAV , and ATVA conferences. Developed tools like DryadSynth (PLDI 2020), ImpSynt (OOPSLA 2017), and JSketch (ESEC/FSE 2015).

Thomas W. Repsمشاهده پروفایل

استاد

• Program Analysis
• Abstract Interpretation
• Model Checking
• +۴ مورد دیگر

Thomas W. Reps is the J. Barkley Rosser Professor & Rajiv and Ritu Batra Chair Emeritus at the University of Wisconsin-Madison , where he has been a faculty member since 1985. He is also President of GrammaTech, Inc., and a co-founder of the company. Education: Ph.D. in Computer Science from Cornell University (1982), winner of the 1983 ACM Doctoral Dissertation Award. Reps’s research spans program analysis , abstract interpretation , model checking , and computer security . His recent work focuses on quantum computing verification , probabilistic program analysis , and symbolic methods for static analysis . His publications (over 225) include foundational contributions to program slicing (1988 paper with Horwitz and Binkley, cited >1,780 times), machine-code analysis (ETAPS Best-Paper Awards in 2004 and 2008), and programming environments (co-author of The Synthesizer Generator ). Key awards include the ACM SIGPLAN Programming Languages Achievement Award (2017) , Guggenheim and Packard Fellowships , and ACM Fellow (2005) . Students: Mentored award-winning graduates like Akash Lal (SIGPLAN Outstanding Dissertation) and Venkatesh Srinivasan (Outstanding Graduate Student Research Award).

Eran Yahavمشاهده پروفایل

دانشیار

• Program Analysis
• Program Synthesis
• Program Verification
• +۴ مورد دیگر

Eran Yahav is an Associate Professor in the Computer Science Department at the Technion - Israel Institute of Technology. He previously served as a research staff member at IBM T.J. Watson Research Center from 2004 to 2010. His academic journey began with a B.Sc. from the Technion in 1996, followed by a Ph.D. from Tel Aviv University in 2005. Yahav's research focuses on program analysis, program synthesis, program verification, and machine learning for programming. His work bridges theoretical foundations with practical applications, particularly in developing techniques that help programmers work more effectively with complex frameworks and APIs. He has pioneered approaches that combine static analysis with machine learning to address challenges in code search, completion, and understanding. His recent work heavily intersects with neural network applications to programming tasks, demonstrating how deep learning can enhance traditional program analysis techniques. His publication record shows a clear evolution from traditional program analysis and verification toward integrating machine learning with programming language processing. The most recent articles reveal a strong focus on neural methods for code understanding, including structural language models, adversarial examples for code models, and neural approaches to binary analysis and program synthesis. This represents a significant shift toward leveraging AI techniques to solve longstanding problems in programming languages and software engineering. Yahav has received numerous accolades including the prestigious Alon Fellowship for Outstanding Young Researchers, the Andre Deloro Career Advancement Chair in Engineering, and an ERC Consolidator Grant. He also earned best paper awards at ISSTA 2006 and 2007. As an advisor, Yahav has mentored numerous Ph.D. and Master's students who have gone on to make significant contributions in academia and industry. His research has been supported by substantial grants, including the ERC Consolidator Grant. He also serves as CTO at Tabnine, demonstrating the practical impact of his research. Yahav leads multiple research projects including PRIME (Programming with Millions of Examples), Fender (Preserving Correctness under Weak Memory Models), Saint (Synthesis using Abstract Interpretation), and several others focused on program analysis, verification, and synthesis. His work often involves building practical tools that translate theoretical advances into usable software engineering solutions.

Stephen Chongمشاهده پروفایل

استاد

• Programming languages
• Information security
• Language-based security
• +۳ مورد دیگر

Stephen Chong is a Gordon McKay Professor of Computer Science in the Harvard John A. Paulson School of Engineering and Applied Sciences, where he serves as Co-Director of Undergraduate Studies for Computer Science. His academic career spans over a decade of teaching and research at Harvard, where he has made significant contributions to programming languages and information security. Chong received his PhD from Cornell University under the guidance of Andrew Myers, and a bachelor's degree from Victoria University of Wellington, New Zealand. Prior to graduate school, he worked as a consultant and contractor in the software industry, bringing practical experience to his academic research. Professor Chong's research focuses on language-based information security, using programming language techniques to provide information security assurance. His work bridges the gap between theoretical foundations and practical applications, developing tools and frameworks that help programmers write trustworthy programs. His research has evolved to address increasingly complex security challenges in modern computing environments, from web applications to cyber-physical systems. His recent publications reveal a strong trend toward integrating advanced programming language techniques with security analysis, particularly through the use of Datalog, SMT solvers, and program synthesis. His work on Formulog has been particularly influential, extending Datalog with mechanisms to construct and reason about SMT formulas for static analysis. His research has expanded to address security challenges in cyber-physical systems, where sensor attacks pose unique threats to safety-critical infrastructure. Chong has received numerous prestigious awards including an NSF CAREER award, an AFOSR Young Investigator award, and a Sloan Research Fellowship. He has also served in leadership roles for major conferences including CSF 2012-2013, PLMW @ PLDI 2021, and as SIGPLAN-M Chair for 2025-2026. As an educator, Chong has mentored numerous students through Harvard's undergraduate research programs and has served as a thesis advisor. His teaching portfolio includes foundational courses like CS51, systems courses like CS61, and advanced topics in programming languages (CS152) and compilers (CS1530). He has been instrumental in shaping Harvard's computer science curriculum, particularly in security and programming languages. Chong leads a research group focused on language-based security, with projects including Formulog (for SMT-based static analysis), PRINCESS (for autonomous adaptation of software), and work on secure shell scripting (Shill). His group collaborates with researchers across Harvard and other institutions to tackle challenging problems at the intersection of programming languages and security.

Nadia Polikarpovaمشاهده پروفایل

دانشیار

• Program Synthesis
• Program Verification
• Type Systems
• +۲ مورد دیگر

Nadia Polikarpova is an Associate Professor in the Computer Science and Engineering Department at the University of California, San Diego. She leads the Programming Systems group and serves as a member of IFIP Working Group 2.8 on Functional Programming since 2022. Her academic journey includes a PhD from ETH Zurich (Switzerland) under Bertrand Meyer's supervision in 2014, followed by postdoctoral work at MIT CSAIL with Armando Solar-Lezama. Her research interests center around program synthesis, program verification, and type systems, with a focus on building practical tools that enhance software security and reliability. Polikarpova's work bridges theoretical foundations with real-world applications, particularly in the emerging area of AI-assisted programming. Her recent publications demonstrate a strong trajectory in program synthesis techniques, with increasing integration of machine learning approaches. The research spans from foundational type-driven synthesis methods to practical applications for validating AI-generated code and synthesizing heap-manipulating programs. Her work frequently appears in top-tier programming languages venues including PLDI, POPL, ICFP, and OOPSLA. 2020 Sloan Fellow 2020 Intel Rising Stars Award 2020 NSF CAREER Award Distinguished paper awards at PLDI'21, ICFP'20, and POPL'19 Best paper award at FM'15 Polikarpova actively mentors PhD students and has advised numerous graduates who now work at Microsoft Research, University of Michigan, and various tech companies. She teaches core programming languages courses including CSE 130 and specialized graduate courses on program synthesis (CSE 291). Her service to the community includes program committee roles for major conferences and co-chairing the Haskell conference in 2022.

Bernd Finkbeinerمشاهده پروفایل

استاد

• Synthesis
• Verification
• Monitoring of Reactive Systems
• +۹ مورد دیگر

Bernd Finkbeiner is a Professor of Computer Science at Saarland University and a faculty member at the CISPA Helmholtz Center for Information Security . He leads the Reactive Systems Group, which merged with CISPA in 2020, focusing on formal methods for ensuring system safety and security. University: Saarland University Research Institution: CISPA Helmholtz Center for Information Security His research spans synthesis, verification, and monitoring of reactive systems , with applications to program repair, static/dynamic analysis, and security guarantees . Recent work includes coinductive proofs for hyperliveness, asynchronous hyperproperty verification, and symbolic execution for bug detection. Key trends in his publications include: Hyperliveness and fairness in reactive systems Symbolic execution for hyperbug identification Integration of synthesis and verification techniques Formal guarantees for cybersecurity and software reliability He contributes to academic communities through committee roles at conferences like POPL, ICFP, SPLASH, and VMCAI.