Martin Vechev
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Computer Science
Martin Vechev's Degrees
- PhD Computer Science Stanford University
- Masters Computer Science Stanford University
- Bachelors Computer Science Stanford University
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Why Is Martin Vechev Influential?
(Suggest an Edit or Addition)According to Wikipedia, Martin Vechev is a professor at the Department of Computer Science at ETH Zurich working in the fields of programming languages, machine learning, and security. He leads the Secure, Reliable, and Intelligent Systems Lab , part of the Department of Computer Science. He is known for his pioneering works in machine learning for code , where he introduced statistical programming engines trained on large codebases, reliable and trustworthy artificial intelligence, where he introduced abstract interpretation methods for reasoning about deep neural networks to enable the verification of large machine learning models, and quantum programming, introducing the first high-level programming language and system Silq.
Martin Vechev's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation (2018) (666)
- Securify: Practical Security Analysis of Smart Contracts (2018) (553)
- Code completion with statistical language models (2014) (516)
- An abstract domain for certifying neural networks (2019) (439)
- Differentiable Abstract Interpretation for Provably Robust Neural Networks (2018) (434)
- Predicting Program Properties from "Big Code" (2015) (363)
- Fast and Effective Robustness Certification (2018) (351)
- PHOG: Probabilistic Model for Code (2016) (173)
- Probabilistic model for code with decision trees (2016) (171)
- VerX: Safety Verification of Smart Contracts (2020) (142)
- Abstraction-guided synthesis of synchronization (2010) (136)
- Learning programs from noisy data (2016) (130)
- Laws of order: expensive synchronization in concurrent algorithms cannot be eliminated (2011) (128)
- Automatic inference of memory fences (2010) (126)
- PSI: Exact Symbolic Inference for Probabilistic Programs (2016) (126)
- Idempotent work stealing (2009) (125)
- Adversarial Training and Provable Defenses: Bridging the Gap (2020) (125)
- Boosting Robustness Certification of Neural Networks (2018) (123)
- Chameleon: adaptive selection of collections (2009) (119)
- Beyond the Single Neuron Convex Barrier for Neural Network Certification (2019) (119)
- Effective race detection for event-driven programs (2013) (115)
- Learning to Fuzz from Symbolic Execution with Application to Smart Contracts (2019) (111)
- Scalable and precise dynamic datarace detection for structured parallelism (2012) (109)
- Race detection for web applications (2012) (108)
- Statistical Deobfuscation of Android Applications (2016) (107)
- Deriving linearizable fine-grained concurrent objects (2008) (106)
- Phrase-Based Statistical Translation of Programming Languages (2014) (98)
- DL2: Training and Querying Neural Networks with Logic (2019) (94)
- Certifying Geometric Robustness of Neural Networks (2019) (93)
- QVM: An Efficient Runtime for Detecting Defects in Deployed Systems (2011) (93)
- Practical concurrent binary search trees via logical ordering (2014) (91)
- Scalable race detection for Android applications (2015) (88)
- Experience with Model Checking Linearizability (2009) (87)
- Efficient data race detection for async-finish parallelism (2010) (86)
- Fast polyhedra abstract domain (2017) (83)
- Testing atomicity of composed concurrent operations (2011) (79)
- Dynamic synthesis for relaxed memory models (2012) (78)
- Silq: a high-level quantum language with safe uncomputation and intuitive semantics (2020) (77)
- Partial-coherence abstractions for relaxed memory models (2011) (74)
- Verifying linearizability with hindsight (2010) (72)
- Debin: Predicting Debug Information in Stripped Binaries (2018) (69)
- NetComplete: Practical Network-Wide Configuration Synthesis with Autocompletion (2018) (64)
- Commutativity race detection (2014) (61)
- Network-Wide Configuration Synthesis (2016) (57)
- Learning Certified Individually Fair Representations (2020) (53)
- zkay: Specifying and Enforcing Data Privacy in Smart Contracts (2019) (52)
- Learning to Solve SMT Formulas (2018) (50)
- NetHide: Secure and Practical Network Topology Obfuscation (2018) (47)
- Serializability for eventual consistency: criterion, analysis, and applications (2017) (47)
- Stateless model checking of event-driven applications (2015) (47)
- Inferring Synchronization under Limited Observability (2009) (45)
- Predicate Abstraction for Relaxed Memory Models (2013) (44)
- Adversarial Robustness for Code (2020) (43)
- QVM: an efficient runtime for detecting defects in deployed systems (2008) (43)
- Effective abstractions for verification under relaxed memory models (2015) (42)
- DP-Finder: Finding Differential Privacy Violations by Sampling and Optimization (2018) (42)
- SDNRacer: concurrency analysis for software-defined networks (2016) (41)
- Refactoring with synthesis (2013) (40)
- Certified Defense to Image Transformations via Randomized Smoothing (2020) (39)
- Correctness-preserving derivation of concurrent garbage collection algorithms (2006) (39)
- Learning a Static Analyzer from Data (2016) (39)
- TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer (2021) (38)
- Making numerical program analysis fast (2015) (38)
- Inferring crypto API rules from code changes (2018) (38)
- Automatic Verification of Determinism for Structured Parallel Programs (2010) (34)
- Config2Spec: Mining Network Specifications from Network Configurations (2020) (31)
- Scaling Polyhedral Neural Network Verification on GPUs (2020) (31)
- Learning Commutativity Specifications (2015) (30)
- SDNRacer: detecting concurrency violations in software-defined networks (2015) (29)
- Static serializability analysis for causal consistency (2018) (29)
- A practical construction for decomposing numerical abstract domains (2017) (28)
- CGCExplorer: a semi-automated search procedure for provably correct concurrent collectors (2007) (28)
- Fast Numerical Program Analysis with Reinforcement Learning (2018) (27)
- Probabilistic Verification of Network Configurations (2020) (26)
- A Provable Defense for Deep Residual Networks (2019) (24)
- Online Robustness Training for Deep Reinforcement Learning (2019) (23)
- Scalable taint specification inference with big code (2019) (22)
- Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound (2022) (21)
- Bayonet: probabilistic inference for networks (2018) (21)
- λPSI: exact inference for higher-order probabilistic programs (2020) (20)
- Programming with "Big Code": Lessons, Techniques and Applications (2015) (20)
- Synthesis of Memory Fences via Refinement Propagation (2014) (20)
- Scalable Certified Segmentation via Randomized Smoothing (2021) (19)
- PODS: Policy Optimization via Differentiable Simulation (2021) (19)
- Synthesis of Probabilistic Privacy Enforcement (2017) (19)
- PRIMA: Precise and General Neural Network Certification via Multi-Neuron Convex Relaxations (2021) (18)
- Efficient Certification of Spatial Robustness (2020) (18)
- Race Detection in Two Dimensions (2015) (18)
- Fine-Grained Semantics for Probabilistic Programs (2018) (18)
- PHALANX: parallel checking of expressive heap assertions (2010) (18)
- Universal Approximation with Certified Networks (2019) (18)
- Neural Network Robustness Verification on GPUs (2020) (17)
- Automatic Synthesis of Deterministic Concurrency (2013) (17)
- Net2Text: Query-Guided Summarization of Network Forwarding Behaviors (2018) (17)
- Verifying atomicity via data independence (2014) (16)
- High-level real-time programming in Java (2005) (16)
- Write barrier elision for concurrent garbage collectors (2004) (16)
- Asynchronous assertions (2011) (16)
- Boosting Randomized Smoothing with Variance Reduced Classifiers (2021) (16)
- Robust relational layout synthesis from examples for Android (2018) (15)
- AStarix: Fast and Optimal Sequence-to-Graph Alignment (2020) (15)
- Scalable Polyhedral Verification of Recurrent Neural Networks (2020) (15)
- Incremental inference for probabilistic programs (2018) (15)
- Robustness Certification for Point Cloud Models (2021) (14)
- Unsupervised learning of API aliasing specifications (2019) (14)
- DP-Sniper: Black-Box Discovery of Differential Privacy Violations using Classifiers (2021) (14)
- Fair Normalizing Flows (2021) (13)
- Learning fast and precise numerical analysis (2020) (13)
- Adversarial Attacks on Probabilistic Autoregressive Forecasting Models (2020) (12)
- Precise Multi-Neuron Abstractions for Neural Network Certification (2021) (12)
- Bayesian Framework for Gradient Leakage (2021) (12)
- Program Synthesis for Character Level Language Modeling (2016) (11)
- Certified Defenses: Why Tighter Relaxations May Hurt Training? (2021) (11)
- Unqomp: synthesizing uncomputation in Quantum circuits (2021) (11)
- Fast and precise certification of transformers (2021) (11)
- Sprint: speculative prefetching of remote data (2011) (11)
- Robustness certification with generative models (2020) (11)
- An Interactive System for Data Structure Development (2015) (11)
- Automated Discovery of Adaptive Attacks on Adversarial Defenses (2021) (11)
- Syncopation: generational real-time garbage collection in the metronome (2005) (11)
- ZeeStar: Private Smart Contracts by Homomorphic Encryption and Zero-knowledge Proofs (2022) (10)
- Fast and optimal sequence-to-graph alignment guided by seeds (2021) (10)
- Derivation and Evaluation of Concurrent Collectors (2005) (10)
- Certify or Predict: Boosting Certified Robustness with Compositional Architectures (2021) (9)
- Latent Space Smoothing for Individually Fair Representations (2021) (9)
- LAMP: Extracting Text from Gradients with Language Model Priors (2022) (8)
- Guiding Program Synthesis by Learning to Generate Examples (2020) (8)
- Distilled Agent DQN for Provable Adversarial Robustness (2018) (8)
- Fast and Effective Robustness Certification for Recurrent Neural Networks (2020) (7)
- Prompting Is Programming: A Query Language For Large Language Models (2022) (7)
- On Distribution Shift in Learning-based Bug Detectors (2022) (7)
- Learning Disjunctions of Predicates (2017) (7)
- Predicting program properties from 'big code' (2019) (7)
- Modeling and analysis of remote memory access programming (2016) (5)
- BigBug: Practical Concurrency Analysis for SDN (2017) (5)
- Learning to Explore Paths for Symbolic Execution (2021) (5)
- Metha: Network Verifiers Need To Be Correct Too! (2021) (5)
- The Fundamental Limits of Interval Arithmetic for Neural Networks (2021) (5)
- zkay v0.2: Practical Data Privacy for Smart Contracts (2020) (5)
- Certification of Semantic Perturbations via Randomized Smoothing (2020) (5)
- Certified Training: Small Boxes are All You Need (2022) (4)
- Shared Certificates for Neural Network Verification (2021) (4)
- Data Leakage in Federated Averaging (2022) (4)
- Learning to find naming issues with big code and small supervision (2021) (4)
- Robust and Accurate - Compositional Architectures for Randomized Smoothing (2022) (3)
- Statistical Verification of General Perturbations by Gaussian Smoothing (2019) (3)
- Practical concurrent traversals in search trees (2018) (3)
- Finding Fix Locations for CFL-Reachability Analyses via Minimum Cuts (2017) (3)
- Race Detection in Two Dimensions (2018) (3)
- Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation (2017) (2)
- Effective Certification of Monotone Deep Equilibrium Models (2021) (2)
- Controlling Large Language Models to Generate Secure and Vulnerable Code (2023) (2)
- FASE: functionality-aware security enforcement (2016) (2)
- Static Serializability Analysis for Causal Consistency (extended version) (2018) (1)
- Class Unloading with a Concurrent Garbage Collector in an Embedded Java VM (2003) (1)
- zkay (2019) (1)
- Learning to Configure Computer Networks with Neural Algorithmic Reasoning (2022) (1)
- Effective Serializability for Eventual Consistency (2016) (1)
- Learning to Infer User Interface Attributes from Images (2019) (1)
- Private and Reliable Neural Network Inference (2022) (1)
- Programming with "Big Code" (Dagstuhl Seminar 15472) (2015) (1)
- Human-Guided Fair Classification for Natural Language Processing (2022) (0)
- Training Neural Machines with Partial Traces (2018) (0)
- Upregulation of HLA I on tumor skin T lymphocytes as a tumor immune escape mechanism in CTCL (2019) (0)
- FARE: Provably Fair Representation Learning (2022) (0)
- Artifact for PLDI'21 paper #156 "Fast and Precise Certification of Transformers" (2021) (0)
- Optimal Learning of Specifications from Examples (2016) (0)
- On the Paradox of Certified Training (2021) (0)
- Session details: Synthesis (2013) (0)
- Reqomp: Space-constrained Uncomputation for Quantum Circuits (2022) (0)
- Computer-Assisted Construction of Efficient Concurrent Algorithms (2008) (0)
- Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation (2023) (0)
- Session details: Instrumentation & evaluation (2010) (0)
- : Android Deobfuscation via “ Big Code ” (2016) (0)
- Verifying Optimistic Algorithms Should be Easy ( Position Paper ) (2009) (0)
- Zapper: Smart Contracts with Data and Identity Privacy (2022) (0)
- Efficient Certified Training and Robustness Verification of Neural ODEs (2023) (0)
- Replication Package for Robustness Certification with Generative Models (2021) (0)
- C OMPLETE V ERIFICATION VIA M ULTI -N EURON R ELAXATION G UIDED B RANCH - AND -B OUND (2022) (0)
- Computer-aided construction of concurrent systems (2010) (0)
- lpsi-artifact (2020) (0)
- Data Leakage in Tabular Federated Learning (2022) (0)
- Robust Relational Layouts Synthesis from Examples for Android (2018) (0)
- Generating Intuitive Fairness Specifications for Natural Language Processing (2022) (0)
- Supplementary Material: Adversarial Robustness for Code (2020) (0)
- Efficient data race detection for async-finish parallelism (2012) (0)
- Reproduction Package for Article: Learning Fast and Precise Numerical Analysis (2020) (0)
- HLA I shield tumor skin T lymphocytes from NK-cell-mediated elimination (2018) (0)
- Abstract Interpretation of Fixpoint Iterators with Applications to Neural Networks (2021) (0)
- IBM Research Report Inferring Synchronization under Limited Observability (2008) (0)
- Certifying Neural Network Audio Classifiers (2019) (0)
- Zapper (2022) (0)
- Efficient Robustness Verification of Neural Ordinary Differential Equations (2022) (0)
- silq-artifact (2020) (0)
- R OBUST AND A CCURATE – C OMPOSITIONAL A RCHITECTURES FOR R ANDOMIZED S MOOTHING (2022) (0)
- Fast and Precise Transformer Certification (0)
- 1032 HLA I shield tumor skin T lymphocytes from NK-cell-mediated elimination (2018) (0)
- Scalable Inference of Symbolic Adversarial Examples (2020) (0)
- Artifact for the PLDI'18 paper "Bayonet: Probabilistic Inference for Networks" (2018) (0)
- F AIR N ORMALIZING F LOWS (2022) (0)
- Verification of Generative-Model-Based Visual Transformations (2019) (0)
- ERAN User Manual (2020) (0)
- Replication Package for the article (2018) (0)
- Proceedings of the 2012 international symposium on Memory Management (2012) (0)
- Towards Auditable AI Systems Current status and future directions based on the workshop “ Auditing AI-Systems : From Basics to Applications (2021) (0)
- Technical Perspective: Beautiful Symbolic Abstractions for Safe and Secure Machine Learning (2023) (0)
- L EARNING TO I NFER U SER I NTERFACE A TTRIBUTES FROM I MAGES (2021) (0)
- L ATENT S PACE S MOOTHING FOR I NDIVIDUALLY F AIR R EPRESENTATIONS (2022) (0)
- Provably Robust Adversarial Examples (2020) (0)
- Training Neural Machines with Trace-Based Supervision (2018) (0)
- Session details: Synthesis (2013) (0)
- Automatic Verification of RMA Programs via Abstraction Extrapolation (2018) (0)
- Abstraction-guided synthesis of synchronization (2012) (0)
- Supplementary Material-Adversarial Attacks on Probabilistic Autoregressive Forecasting Models (2020) (0)
- (De-)Randomized Smoothing for Decision Stump Ensembles (2022) (0)
- VARIANCE REDUCED CLASSIFIERS (2022) (0)
- C4 Tool Source Code (2018) (0)
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