Top Conferences (total = 38)
NOTE: Only publications in top-tier conferences with low acceptance rates, are listed here. For a list of all publications, please go here.
| NDSS’25 |
A Method to Facilitate Membership Inference Attacks in Deep Learning Models, Zitao Chen and Karthik Pattabiraman. (Acceptance Rate: TBD) |
| CCS’24 |
AutoPatch: Automated Generation of Hotpatches for Real-Time Embedded Devices, Mohsen Salehi and Karthik Pattabiraman. (Acceptance Rate: 16.7%) |
| CCS’24 |
SpecGuard: Specification Aware Recovery for Robotic Autonomous Vehicles from Physical Attacks, Pritam Dash, Ethan Chan and Karthik Pattabiraman. (Acceptance Rate: 16.7%) |
| IEEE S&P’24 |
POMABuster: Detecting Price Oracle Manipulation Attacks in Decentralized Finance, Rui Xi, Zehua Wang, and Karthik Pattabiraman. (Acceptance rate: 17.8%) |
| NDSS’24 |
Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks by Enforcing Less Confident Prediction, Zitao Chen and Karthik Pattabiraman. (Acceptance Rate: 15%) |
| SC’23 |
Structural Coding: A Low-Cost Scheme to Protect CNNs from Large-Granularity Memory Faults, Ali Asgari, Florian Geissler, Syed Qutub, Michael Paulitsch, Prashant Nair, and Karthik Pattabiraman. (Acceptance Rate: 23.9%). |
| DSN’23 |
SwarmFuzz: Discovering GPS Spoofing Attacks in Drone Swarms, Yiangao (Elaine) Yao, Pritam Dash, and Karthik Pattabiraman (Acceptance Rate: 20%). |
| ICSE’23 |
AChecker, Statically Detecting Smart Contract Access Control Vulnerabilities, Asem Ghaleb, Julia Rubin, and Karthik Pattabiraman (Acceptance Rate: 26%). |
ISSTA’22 |
eTainter: Detecting Gas-Related Vulnerabilities in Smart Contracts, Asem Ghaleb, Julia Rubin, and Karthik Pattabiraman. (Acceptance Rate: 24.5%). |
| DSN’22 |
The Fault in Our Data Stars: Studying Mitigation Techniques against Faulty Training Data in ML Applications, Abraham Chan, Arpan Gujarati, Karthik Pattabiraman, and Sathish Gopalakrishnan. (Acceptance Rate: 18.7%) |
| DSN’21 |
PID-Piper: Recovering Robotic Vehicles from Physical Attacks, Pritam Dash, Guanpeng Li, Zitao Chen, Mehdi Karimibiuki, and Karthik Pattabiraman. (Acceptance Rate: 16.5%). Best paper award. |
| DSN’21 |
A Low Cost Fault Corrector for Deep Neural Networks through Range Restriction, Zitao Chen, Guanpeng Li, and Karthik Pattabiraman. (Acceptance Rate: 16.5%). Best paper award runner up (one of two papers). |
| SC’20 |
GPU-TRIDENT: Efficient Modeling of Error Propagation in GPU Programs, Abdul Rehman Anwer, Guanpeng Li, Karthik Pattabiraman, Michael Sullivan, Timothy Tsai and Siva Hari. (Acceptance Rate: 25.1%) |
| ISSTA’20 |
How Effective are Smart Contract Analysis Tools? Evaluating Smart Contract Static Analysis Tools Using Bug Injection, Asem Ghaleb and Karthik Pattabiraman. (Acceptance Rate: 26%) |
| DSN’20 |
Trace Sanitizer: Eliminating the Effects of Non-Determinism on Error Propagation Analysis, Habib Saissi, Stefan Winter, Oliver Schwan, Karthik Pattabiraman, and Neeraj Suri. (Acceptance Rate: 16.5%) |
| SC’19 |
BinFI: An Efficient Fault Injector for Safety-Critical Machine Learning Systems, Zitao Chen, Guanpeng Li, Karthik Pattabiraman, and Nathan DeBardeleben. (Acceptance Rate: 21%). Finalist for SC reproducibility challenge (1 of 3) |
| DSN’18 |
Modeling Soft-Error Propagation in Programs, Guanpeng Li, Karthik Pattabiraman, Siva Kumar Sastry Hari, Michael Sullivan, and Timothy Tsai. (Acceptance Rate: 25%). Best Paper Award Runner Up – one of two papers. |
| DSN’18 |
Modeling Input-Dependent Error Propagation in Programs, Guanpeng Li, and Karthik Pattabiraman. (Acceptance Rate: 25%) |
| ICSE’18 |
Inferring Hierarchical Motifs from Execution Traces, Saba Alimadadi, Ali Mesbah, and Karthik Pattabiraman. (Acceptance Rate: 21%) |
| ASE’17 |
Detecting Unknown Inconsistencies in Web Applications, Frolin Ocariza, Karthik Pattabiraman, and Ali Mesbah. (Acceptance Rate: 21%) |
| SC’17 |
Understanding Error Propagation in Deep learning Neural Networks (DNN) Accelerators and Applications, Guanpeng Li, Siva Hari, Michael Sullivan, Timothy Tsai, Karthik Pattabiraman, Joel Emer, Stephen Keckler. (Acceptance Rate: 19%). Chosen for IEEE Top Picks in Test and Reliability (TPTR), 2023. |
| FSE’17 |
ARTINALI: Dynamic Invariant Detection for Cyber-Physical System Security, Maryam Raiyat Aliabadi, Amita Kamath, Julien Samson, and Karthik Pattabiraman. (Acceptance Rate: 24%) |
| HPDC’17 |
LetGo: A Lightweight Continuous Framework for HPC Applications Under Failures, Bo Fang, Qiang Guan, Nathan Debardeleben, Karthik Pattabiraman, and Matei Ripeanu. (Acceptance Rate: 19%) |
| DSN’17 | One Bit is (Not) Enough: An Empirical Study of the Impact of Single Bit and Multiple Bit-Flip Errors, Behrooz Sangchoolie, Karthik Pattabiraman and Johan Karlsson. (Acceptance Rate: 23%) | SC’16 |
Understanding Error Propagation in GPGPU Applications, Guanpeng Li, Karthik Pattabiraman, Chen-Yong Cher and Pradip Bose. (Acceptance Rate: 18%) |
| DSN’16 |
ePVF: An Enhanced Program Vulnerability Factor Methodology for Cross-Layer Resilience Analysis, Bo Fang, Qining Lu, Karthik Pattabiraman, Matei Ripeanu and Sudhanva Gurumurthi. (Acceptance Rate: 21%) |
| ICSE’16 |
Understanding Asynchronous Interactions in Full-Stack JavaScript, Saba Alimadadi, Ali Mesbah and Karthik Pattabiraman. (Acceptance Rate: 19%) |
| ASE’15 |
Synthesizing Web Element Locators, Kartik Bajaj, Karthik Pattabiraman and Ali Mesbah. (Acceptance Rate: 20.8%) |
| DSN’15 |
Fine-Grained Characterization of Faults Causing Long Latency Crashes in Programs, Guanpeng Li, Qining Lu and Karthik Pattabiraman. (Acceptance Rate: 22%) |
| ICSE’15 |
Finding Inconsistencies in JavaScript MVC Applications, Frolin Ocariza, Karthik Pattabiraman and Ali Mesbah. (Acceptance Rate: 18.5%) |
| DSN’14 |
Integrated Hardware-Software Diagnosis for Intermittent Hardware Faults, Majid Dadashi, Layali Rashid, Karthik Pattabiraman and Sathish Gopalakrishnan. (Acceptance Rate: 30%). |
| DSN’14 |
Quantifying the Accuracy of High-Level Fault Injection Techniques for Hardware Faults, Jiesheng Wei, Anna Thomas, Guanpeng Li, and Karthik Pattabiraman. (Acceptance Rate: 30%). |
| ICSE’14 |
Vejovis: Suggesting Fixes for JavaScript Faults, Frolin S. Ocariza, Karthik Pattabiraman and Ali Mesbah. (Acceptance Rate: 20%). |
| ICSE’14 |
Understanding JavaScript Event-Based Interactions, Saba Alimadi, Sheldon Sequira, Ali Mesbah and Karthik Pattabiraman (Acceptance Rate: 20%). ACM SIGSOFT Distinguished Paper Award (one of nine papers) |
| ASE’14 |
Dompletion: DOM-Aware Code Completion, Kartik Bajaj, Karthik Pattabiraman and Ali Mesbah. (Acceptance Rate: 20%) |
| DSN’13 |
Error Detector Placement for Soft Computation, |
| DSN’12 |
BLOCKWATCH: Leveraging Similarity in Parallel Programs for Error Detection, Jiesheng Wei and Karthik Pattabiraman. (Acceptance Rate: 17%). |
| ASPLOS’11 |
Flikker: Saving DRAM Refresh-power through Critical Data Partitioning , Song Liu, Karthik Pattabiraman, Thomas Moscibroda and Benjamin Zorn. (Acceptance Rate: 20% ) |
