{"id":2289,"date":"2013-07-04T15:09:59","date_gmt":"2013-07-04T22:09:59","guid":{"rendered":"https:\/\/blogs.ubc.ca\/karthik\/?page_id=2289"},"modified":"2026-03-21T08:01:19","modified_gmt":"2026-03-21T15:01:19","slug":"all-papers","status":"publish","type":"page","link":"https:\/\/blogs.ubc.ca\/karthik\/papers\/all-papers\/","title":{"rendered":"All Papers (after 2010)"},"content":{"rendered":"


\nFor a list of selected papers, go here<\/a>. <\/p>\n

For a list of papers prior to 2010, go here<\/a>.<\/p>\n

<\/p>\n\n\n
Journals<\/a> <\/td>\n Conferences<\/a> <\/td>\n Workshops and Other<\/a> <\/td>\n Patents<\/a> <\/td>\n Talks<\/a> <\/td>\n<\/tr>\n<\/table>\n

<\/a><\/p>\n

\n

Journals (total = 28)<\/A><\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Springer Nature<\/a><\/td>\nSystems-Theoretic and Data-Driven Security Analysis in ML-enabled Medical Devices<\/a>, G. Mitra, M. Hallajiyan, I. Kim, A. P. Dharmalingam, M. Elnawawy, S. Iqbal, K. Pattabiraman, H. Alemzadeh. (Invited)<\/strong> <\/td>\n<\/tr>\n
TDSC<\/a><\/td>\nFeed-Forward Controller-Based Recovery for Robotic Vehicles from Physical Attacks<\/a>, Pritam Dash, Guanpeng Li, Zitao Chen, Mehdi Karimibiuki, Karthik Pattabiraman. In press. <\/td>\n<\/tr>\n
IEEE D&T<\/a><\/td>\nA Low-cost Fault Corrector for Deep Neural Networks through Range Restriction<\/a>, Zitao Chen, Guanpeng Li, Karthik Pattabiraman.<\/td>\n<\/tr>\n
TPDS<\/a><\/td>\nOneOS: Distributed Operating System for the Edge-to-Cloud Continuum<\/a><\/em>, Kumseok Jung, Julien Gascon Samson, Sathish Gopalakrishnan, and Karthik Pattabiraman.<\/td>\n<\/tr>\n
IEEE D&T<\/a><\/td>\n\n

\nUnderstanding Error Propagation in Deep-Learning Neural Networks Accelerators and Applications<\/a>, Guanpeng Li, Siva Kumar Sastry Hari, Michael B. Sullivan, Timothy Tsai, Karthik Pattabiraman, Joel S. Emer. <\/p>\n<\/td>\n<\/tr>\n

TECS<\/a><\/td>\n\n

Co-Approximator: Enabling Performance Prediction in Colocated Applications<\/a>, Mohammad Rafiuzzaman, Sathish Gopalakrishnan and Karthik Pattabiraman. <\/p>\n<\/td>\n<\/tr>\n

TCPS<\/a><\/td>\n\n

Characterizing and Improving Resilience of Accelerators to Memory Errors in Autonomous Robots<\/A>, Deval Shah, Zi Yu Xue, Karthik Pattabiraman and Tor Aamodt. <\/p>\n<\/td>\n<\/tr>\n

JPDC<\/a><\/td>\nMixed Precision Support in HPC Applications: What About Reliability?<\/a>, Alessio Netti, Yang Peng, Patrik Omland, Michael Paulitsch, Jorge Parra, Gustavo Espinosa, Udit Agarwal, Abraham Chan, and Karthik Pattabiraman.<\/td>\n<\/tr>\nSPE<\/a><\/td>\nA Large-scale Empirical Study of Low-level Function Use in
\nEthereum Smart Contracts and Automated Replacement<\/a>, Rui Xi and Karthik Pattabiraman.<\/td>\n<\/tr>\n
TDSC<\/a><\/td>\n\n

Fault Injection for TensorFlow Applications<\/a>, Niranjhana Narayanan, Zitao Chen, Bo Fang, Guanpeng Li, Karthik Pattabiraman, and Nathan DeBardeleben. <\/p>\n<\/td>\n<\/tr>\n

SPE<\/a><\/td>\n\n

ThingsMigrate: Platform Independent Migration of Stateful JavaScript Applications<\/a>, Kumseok Jung, Julien Gascon-Samson, Shivanshu Goyal, Armin Rezalean-Asel, Karthik Pattabiraman.<\/p>\n<\/td>\n<\/tr>\n

TDSC<\/a> <\/td>\n\n

An Empirical Study of the Impact of Single and Multiple Bit-Flip Errors in Programs<\/a>, Behrooz Sangchoolie, Karthik Pattabiraman and Johan Karlsson. <\/p>\n<\/td>\n<\/tr>\n

DTRAP<\/a> <\/td>\n\n

Stealthy Attacks Against Robotic Vehicles Protected by Control-Based Intrusion Detection Techniques<\/A>, Pritam Dash, Mehdi Karimibuiki, and Karthik Pattabiraman. <\/p>\n<\/td>\n<\/tr>\n

TDSC<\/a><\/td>\n\n

Improving the accuracy of IR-level Fault Injection<\/a>, Lucas Palazzi, Guanpeng Li, Bo Fang, and Karthik Pattabiraman, 2020. <\/p>\n<\/td>\n<\/tr>\n

TECS<\/a><\/td>\n\n

Design-level and Code-level Security Analysis of IoT Devices<\/a>, Farid Molazem Tabrizi and Karthik Pattabiraman. 2019. (Best paper award for 2018-2020<\/strong>)\n<\/p>\n<\/td>\n

TECS<\/a><\/td>\n\n

Configurable Detection of SDC-Causing Errors in Programs<\/a>, Qining Lu, Guanpeng Li, Karthik Pattabiraman, Meeta Gupta and Jude Rivers. 2017.\n<\/p>\n<\/td>\n<\/tr>\n

TSE<\/td>\n\n

A Study of Causes and Consequences of Client-Side JavaScript Bugs<\/a>, Frolin Ocariza, Kartik Bajaj, Ali Mesbah and Karthik Pattabiraman. 2017.\n<\/p>\n<\/td>\n<\/tr>\n

TPDS<\/a><\/td>\n\n

A Systematic Methodology for Evaluating the Error Resilience of GPGPU Applications<\/a>, Bo Fang, Karthik Pattabiraman, Matei Ripeanu and Sudhanva Gurumurthi. 2016. <\/p>\n<\/td>\n<\/tr>\n

TOSEM<\/a><\/td>\n\n

Understanding JavaScript Event-based Interactions with Clematis<\/a>, Saba Alimadadi, Ali Mesbah and Karthik Pattabiraman. 2016. <\/p>\n<\/td>\n<\/tr>\n

TECS<\/a><\/td>\nError Detector Placement for Soft Computing Applications<\/a>, Anna Thomas and Karthik Pattabiraman. 2016. <\/td>\n<\/td>\n<\/tr>\n
STVR<\/td>\n\n

Automatic Fault Localization for Client-Side JavaScript<\/a>, Frolin Ocariza, Karthik Pattabiraman and Ali Mesbah. 2016.\n<\/p>\n<\/td>\n<\/tr>\n

TSE<\/td>\n\n

Guided Mutation Testing for JavaScript Web Applications<\/a>, Shabnam Mirshokraie, Ali Mesbah and Karthik Pattabiraman. 2015.\n<\/p>\n<\/td>\n<\/tr>\n

TR<\/td>\n\n

Characterizing the Impact of Intermittent Hardware Faults on Programs<\/a>, Layali Rashid, Karthik Pattabiraman and Sathish Gopalakrishnan. 2015.\n<\/p>\n<\/td>\n<\/tr>\n

JCS<\/a><\/td>\n\n

Modular Protections against Non-control Data Attacks<\/a>, Cole Schlesinger, Karthik Pattabiraman, Nikhil Swamy, David Walker, and Benjamin Zorn, 2014. <\/p>\n<\/td>\n<\/tr>\n

TC<\/a><\/td>\n\n

SymPLFIED: Symbolic Program Level Fault Injection and Error Detection Framework<\/A>, Karthik Pattabiraman, Nithin Nakka, Zbigniew Kalbarczyk and Ravishankar Iyer, 2013. <\/p>\n<\/td>\n<\/tr>\n

TC<\/a><\/td>\n\n

Efficient Runtime Detection and Toleration of Asymmetric Races<\/a>, Paruj Ratanaworabhan, Martin Burtscher, Darko Kirovski, Benjamin Zorn, Rahul Nagpal, Karthik Pattabiraman, 2012 <\/p>\n<\/td>\n<\/tr>\n

TDSC<\/a><\/td>\n\n

Automated Derivation of Application-aware Error Detectors using Dynamic Analysis<\/a>, Karthik Pattabiraman, Giacinto Paulo Saggese, Daniel Chen, Zbigniew Kalbarczyk and Ravishankar Iyer, 2011. <\/p>\n<\/td>\n<\/tr>\n

TDSC<\/a><\/td>\n\n

Automated Derivation of Application-aware Error Detectors using Static Analysis<\/a>, Karthik Pattabiraman, Zbigniew Kalbarczyk and Ravishankar Iyer, 2011. <\/p>\n<\/td>\n<\/tr>\n<\/table>\n

Back to top<\/a><\/p>\n

\n

Refereed Conferences<\/A> (total = 95) <\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
DSN’26<\/a><\/td>\n\n

Thinking Inside the Box: Injecting Realistic Radiation Faults in ML Accelerators<\/em>, Bruno Loureiro Coelho, Seyedmani Sadati, Abraham Chan, Alex Hands, Karthik Pattabiraman, and Paolo Rech. (Acceptance Rate: TBD) <\/p>\n<\/td>\n<\/tr>\n

DSN’26<\/a><\/td>\n\n

ReSect: A Tool for Automated Analysis of Reentrancy Exploit Transactions on Blockchains<\/em>, Yuqi Liu, Rui Xi, and Karthik Pattabiraman. (Acceptance Rate: TBD) <\/p>\n<\/td>\n<\/tr>\n

Middleware’26<\/a><\/td>\n\n

Requalizer: A Co-designed Information Flow Control and Quality of Service Management Framework<\/em>, Kumseok Jung, Sathish Gopalakrishnan, Karthik Pattabiraman. (Acceptance Rate: TBD) <\/p>\n<\/td>\n<\/tr>\n

ICRA’26<\/a><\/td>\n\n

ARMOR: Attack-Resilient Reinforcement Learning Control for UAVs<\/a>, Pritam Dash, Ethan Chan, Nathan P. Lawrence, Karthik Pattabiraman. (Acceptance Rate: 38%) <\/p>\n<\/td>\n<\/tr>\n

Eurosys’26<\/a><\/td>\n\n

Turnstile: Hybrid Information Flow Control Framework for Managing Privacy in Internet-of-Things Applications<\/a>, Kumseok Jung, Mohanna Shahrad, Gargi Mitra, and Karthik Pattabiraman. (Acceptance Rate: 16.9%).<\/p>\n<\/td>\n

ISSRE’25<\/a><\/td>\n\n

DLAFI: Software-Based Fault Injection for Permanent Faults in Deep Learning Accelerators<\/a>, Seyedmani Sadati, Abraham Chan, Udit Kumar Agarwal and Karthik Pattabiraman. (Acceptance Rate: 28%). <\/p>\n<\/td>\n<\/tr>\n

CCS’25<\/a><\/td>\n\n

Anonymity Unveiled: A Practical Framework for Auditing Data Use in Deep Learning Models<\/a>, Zitao Chen and Karthik Pattabiraman. (Acceptance Rate: 14.5%) <\/p>\n<\/td>\n<\/tr>\n

DSN’25<\/a><\/td>\n\n

ReMIX: Resilience for ML Ensembles using XAI at Inference against Faulty Training Dat<\/a>a, Abraham Chan, Arpan Gujarati, Karthik Pattabiraman and Sathish Gopalakrishnan. (Acceptance Rate: 20%)<\/p>\n<\/td>\n<\/tr>\n

DSN’25<\/a><\/td>\n\n

RAVAGE: Robotic Autonomous Vehicles\u2019 Attack Generation Engine<\/a>, Pritam Dash and Karthik Pattabiraman. (Acceptance Rate: 20%)<\/p>\n<\/td>\n<\/tr>\n

DSN’25<\/a><\/td>\n\n

Reentrancy Redux: The Evolution of Real-World Reentrancy Attacks on Blockchains<\/a>, Yuqi Liu, Rui Xi, and Karthik Pattabiraman. (Acceptance Rate: 20%)<\/p>\n<\/td>\n<\/tr>\n

SAC’25<\/a><\/td>\n\n

D-semble: Efficient Diversity-Guided Search for Resilient ML Ensembles<\/a>, Abraham Chan, Arpan Gujarati, Karthik Pattabiraman and Sathish Gopalakrishnan. (Acceptance Rate: 23%)<\/p>\n<\/td>\n<\/tr>\n

NDSS’25<\/a><\/td>\n\n

A Method to Facilitate Membership Inference Attacks in Deep Learning Models<\/a>, Zitao Chen and Karthik Pattabiraman. (Acceptance Rate: 16.1%)<\/p<\/td>\n<\/tr>\n

CCS’24<\/a><\/td>\n\n

AutoPatch: Automated Generation of Hotpatches for Real-Time Embedded Devices<\/a>, Mohsen Salehi and Karthik Pattabiraman. (Acceptance Rate: 16.7%) <\/p>\n<\/td>\n<\/tr>\n

CCS’24<\/a><\/td>\n\n

SpecGuard: Specification Aware Recovery for Robotic Autonomous Vehicles from Physical Attacks<\/a>, Pritam Dash, Ethan Chan and Karthik Pattabiraman. (Acceptance Rate: 16.7%) <\/p>\n<\/td>\n<\/tr>\n

IEEE S&P’24<\/a><\/td>\n\n

POMABuster: Detecting Price Oracle Manipulation Attacks in Decentralized Finance<\/a>, Rui Xi, Zehua Wang, and Karthik Pattabiraman. (Acceptance rate: 17.8%)<\/p>\n<\/td>\n<\/tr>\n

CHASE’24<\/a><\/td>\n\n

Systematically Assessing the Security Risks of AI\/ML-enabled Connected Healthcare Systems<\/a>, Mohammad ElNawawy, Mohammadreza Hallajiyan, Gargi Mitra, Shahrear Iqbal, and Karthik Pattabiraman. (Acceptance Rate: 28.4%)\n<\/p>\n<\/td>\n<\/tr>\n

IoTDI’24<\/a><\/td>\n\n

ImmunoPlane: Middleware for Providing Adaptivity to Distributed Internet-of-Things Applications<\/a>, Kumseok Jung, Gargi Mitra, Sathish Gopalakrishnan and Karthik Pattabiraman. (Acceptance Rate: 36.7%)<\/p>\n<\/td>\n

AsiaCCS’24<\/a><\/td>\n\n

Diagnosis-guided Attack Recovery for Securing Robotic Vehicles from Sensor Deception Attacks<\/a>, Pritam Dash, Guanpeng Li, Mehdi Karimibiuki, and Karthik Pattabiraman. (Acceptance Rate: 21.9%) <\/p>\n<\/td>\n<\/tr>\n

NDSS’24<\/a><\/td>\n\n

Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks by Enforcing Less Confident Prediction<\/a>, Zitao Chen and Karthik Pattabiraman. (Acceptance Rate: 15%)<\/p>\n<\/td>\n<\/tr>\n

SEC’23<\/a><\/td>\n\n

EdgeEngine: A Thermal-Aware Optimization Framework for Edge Inference<\/a>, Amirhossein Ahmadi, Hazem Abdelhafez, Karthik Pattabiraman and Matei Ripeanu. (Acceptance Rate: 25%) <\/p>\n<\/td>\n<\/tr>\n

ISSRE’23<\/a><\/td>\n\n

Resilience Assessment of Large Language Models under Transient Hardware Faults<\/a>, Udit Agarwal, Abraham Chan, and Karthik Pattabiraman. (Acceptance Rate: 29.5%)<\/p>\n<\/td>\n<\/tr>\n

ISSRE’23<\/a><\/td>\n\n

Evaluating the Effect of Common Annotation Faults on Object Detection Techniques<\/a>, Abraham Chan, Arpan Gujarati, Karthik Pattabiraman and Sathish Gopalakrishnan. (Acceptance Rate: 29.5%) <\/p>\n<\/td>\n<\/tr>\n

SC’23<\/a><\/td>\n\n

Structural Coding: A Low-Cost Scheme to Protect CNNs from Large-Granularity Memory Faults<\/a>, Ali Asgari, Florian Geissler, Syed Qutub, Michael Paulitsch, Prashant Nair, and Karthik Pattabiraman. (Acceptance Rate: 23.9%).<\/p>\n<\/td>\n<\/tr>\n

SafeComp’23<\/a><\/td>\nA Low-cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural Networks<\/a>, Florian Geissler, Syed Qutub, Michael Paulitsch and Karthik Pattabiraman. (Acceptance Rate: 20%)<\/td>\n<\/tr>\n
DSN’23<\/a><\/td>\n\n

SwarmFuzz: Discovering GPS Spoofing Attacks in Drone Swarms<\/a>, Yiangao (Elaine) Yao, Pritam Dash, and Karthik Pattabiraman (Acceptance Rate: 20%). <\/p>\n<\/td>\n<\/tr>\n

ICSE’23<\/a><\/td>\n\n

AChecker: Statically Detecting Smart Contract Access Control Vulnerabilities<\/a>, Asem Ghaleb, Julia Rubin, and Karthik Pattabiraman (Acceptance Rate: 26%). <\/p>\n<\/td>\n<\/tr>\n

AsiaCCS’23<\/a><\/td>\n\n

Jujutsu: A Two-stage Defense against Adversarial Patch Attacks on Deep Neural Networks<\/a>, Zitao Chen, Pritam Dash, and Karthik Pattabiraman. (Acceptance Rate: 17%)<\/p>\n<\/td>\n<\/tr>\n

SEC’22<\/a><\/td>\n\n

Characterizing Variability in Heterogeneous Edge Systems: A Methodology & Case Study<\/a>, Hazem A. Abdelhafez, Hassan Halawa, Amr Almoallim, Amirhossein Ahmadi, Karthik Pattabiraman, and Matei Ripeanu. (Acceptance Rate: 27%) <\/p>\n<\/td>\n<\/tr>\n

ISSRE’22<\/a><\/td>\nLLTFI: Framework Agnostic Fault Injection for Machine Learning Applications (Tools and Artifact Track)<\/a>, Udit Agarwal, Abraham Chan, and Karthik Pattabiraman (Acceptance Rate: 29%).<\/td>\n<\/tr>\n
ISSTA’22<\/a><\/td>\n\n

eTainter: Detecting Gas-Related Vulnerabilities in Smart Contracts<\/a>, Asem Ghaleb, Julia Rubin, and Karthik Pattabiraman. (Acceptance Rate: 24.5%). <\/p>\n<\/td>\n<\/tr>\n

DSN’22<\/a><\/td>\n\n

The Fault in Our Data Stars: Studying Mitigation Techniques against Faulty Training Data in ML Applications<\/a>, Abraham Chan, Arpan Gujarati, Karthik Pattabiraman, and Sathish Gopalakrishnan. (Acceptance Rate: 18.7%)<\/p>\n<\/td>\n<\/tr>\n

IoTDI’22<\/a><\/td>\n\n

\u03c0-Configurator: Enabling Efficient Configuration of Pipelined Applications on the Edge<\/a>, Mohammad Rafiuzzaman, Sathish Gopalakrishnan and Karthik Pattabiraman. (Acceptance Rate: 33%)<\/p>\n<\/td>\n<\/tr>\n

SANER’22<\/a><\/td>\n\n

When They Go Low: Automated Replacement of Low-level Functions in Ethereum Smart Contracts<\/a>, Rui Xi and Karthik Pattabiraman. (Acceptance Rate: 36%)<\/p>\n<\/td>\n<\/tr>\n

QRS’21<\/a><\/td>\n\n

Understanding the Resilience of Neural Network Ensembles against Faulty Training Data<\/a>, Abraham Chan, Niranjhana Narayananan, Arpan Gujarati, Karthik Pattabiraman, and Sathish Gopalakrishnan. (Acceptance Rate: 25.1%). Best Paper Award (1 of 3)<\/strong><\/p>\n<\/td>\n<\/tr>\n

SEC’21<\/a><\/td>\n\n

OneOS: Middleware for Running Edge Computing Applications as Distributed POSIX Pipelines<\/a>, Kumseok Jung, Julien Gascon-Samson, and Karthik Pattabiraman. (Acceptance Rate: 27%). Best Demo Award.<\/strong> <\/p>\n<\/td>\n<\/tr>\n

SEC’21<\/a><\/td>\n\n

MIRAGE: Machine Learning-based Modeling of Identical Replicas of the Jetson AGX Embedded Platform<\/a>, Hazem A. Abdelhafez, Hassan Halawa, Mohamed Ahmed, Karthik Pattabiraman, and Matei Ripeanu. (Acceptance Rate: 27%).<\/p>\n<\/td>\n<\/tr>\n

PRDC’21<\/a><\/td>\n\n

Are you for Real? Authentication in Dynamic IoT Systems<\/a>, Mehdi Karimibiuki, Karthik Pattabiraman, and Andre Ivanov. (Acceptance Rate: 43%).<\/p>\n<\/td>\n<\/tr>\n

DSN’21<\/a><\/td>\n\n

PID-Piper: Recovering Robotic Vehicles from Physical Attacks<\/a>, Pritam Dash, Guanpeng Li, Zitao Chen, Mehdi Karimibiuki, and Karthik Pattabiraman. (Acceptance Rate: 16.5%). Best paper award <\/strong>.\n<\/p>\n<\/td>\n<\/tr>\n

DSN’21<\/a><\/td>\n\n

A Low Cost Fault Corrector for Deep Neural Networks through Range Restriction<\/a>, Zitao Chen, Guanpeng Li, and Karthik Pattabiraman. (Acceptance Rate: 16.5%). Best paper award runner up (1 of 2), IEEE Top Pick in Test and Reliability (TPTR)<\/a>, 2024<\/strong>.\n<\/p>\n<\/td>\n<\/tr>\n

ISSRE’20<\/a><\/td>\n\n

TensorFI: A Flexible Fault Injection Framework for TensorFlow Applications<\/a><\/em>, Zitao Chen, Niranjhana Narayanan, Bo Fang, Guanpeng Li, Karthik Pattabiraman, and Nathan DeBardeleben. (Acceptance Rate: 26%)<\/p>\n<\/td>\n<\/tr>\n

ISSRE’20<\/a><\/td>\n\n

How Far Have We Come in Detecting Anomalies in Distributed Systems? An Empirical Study with a Statement-level Fault Injection Method<\/a>, Yong Yang, Yifan Wu, Karthik Pattabiraman, Long Wang, and Ying Li. (Acceptance Rate: 26%)<\/p>\n<\/td>\n<\/tr>\n

SC’20<\/a><\/td>\n\n

GPU-TRIDENT: Efficient Modeling of Error Propagation in GPU Programs<\/a>, Abdul Rehman Anwer, Guanpeng Li, Karthik Pattabiraman, Michael Sullivan, Timothy Tsai and Siva Hari. (Acceptance Rate: 25.1%) <\/p>\n<\/td>\n<\/tr>\n

ISSTA’20<\/a> <\/td>\n\n

How Effective are Smart Contract Analysis Tools? Evaluating Smart Contract Static Analysis Tools Using Bug Injection<\/a>, Asem Ghaleb and Karthik Pattabiraman. (Acceptance Rate: 26%)<\/p>\n<\/td>\n<\/tr>\n

 DSN’20<\/a> <\/td>\n\n

Trace Sanitizer: Eliminating the Effects of Non-Determinism on Error Propagation Analysis<\/a>, Habib Saissi, Stefan Winter, Oliver Schwan, Karthik Pattabiraman, and Neeraj Suri. (Acceptance Rate: 16.5%)<\/p>\n<\/td>\n<\/tr>\n

ACSAC’19<\/a><\/td>\n\n

Out of Control: Stealthy Attacks on Robotic Vehicles Protected by Control-Based Techniques<\/a>, Pritam Dash, Mehdi Karimibuiki, and Karthik Pattabiraman. (Acceptance Rate: 23%)<\/p>\n<\/td>\n<\/tr>\n

ISSRE’19<\/a><\/td>\n\n

A Tale of Two Injectors: End-to-End Comparison of IR-level and Assembly-level Fault Injection<\/a>, Lucas Palazzi, Guanpeng Li, Bo Fang, and Karthik Pattabiraman. (Acceptance Rate: 31.5%). <\/p>\n<\/td>\n<\/tr>\n

SC’19<\/a><\/td>\n\n

BinFI: An Efficient Fault Injector for Safety-Critical Machine Learning Systems<\/a>, Zitao Chen, Guanpeng Li, Karthik Pattabiraman, and Nathan DeBardeleben. (Acceptance Rate: 21%). Reproducibility Initiative Finalist (1 of 3)<\/strong> <\/p>\n<\/td>\n<\/tr>\n

ICS’19<\/a><\/td>\n\n

BonVoision: Leveraging Spatial Data Smoothness for Recovery from Memory Soft Errors<\/a>, Bo Fang, Karthik Pattabiraman, Matei Ripeanu and Sriram Krishnamoorthy (Acceptance Rate: 23.2%)<\/p>\n<\/td>\n<\/tr>\n

SAC’19<\/a><\/td>\n\n

Failure Prediction in the Internet of Things due to Memory Exhaustion<\/a>, Mohammad Rafiuzzaman, Julien Gascon-Samson, Karthik Pattabiraman, and Sathish Gopalakrishnan. (Acceptance Rate: 27.5%)<\/p>\n<\/td>\n<\/tr>\n

PRDC’18<\/a><\/td>\nDynPolAC: Dynamic Policy-based Access Control for IoT Systems<\/a>, Mehdi Karimibuiki, Ekta Aggarwal, Karthik Pattabiraman and Andre Ivanov. (Acceptance Rate: 45%)<\/p>\n<\/td>\n<\/tr>\n
ECOOP’18<\/a><\/td>\n\n

ThingsMigrate: Platform-Independent Migration of Stateful JavaScript IoT Applications<\/a>, Julien Gascon-Samson, Kumseok Jung, Shivanshu Goyal, Armin Rezalean-Asel, and Karthik Pattabiraman. (Acceptance Rate: 39%) <\/p>\n<\/td>\n<\/tr>\n

DSN’18<\/a><\/td>\n\n

Modeling Soft-Error Propagation in Programs<\/a>, Guanpeng Li, Karthik Pattabiraman, Siva Kumar Sastry Hari, Michael Sullivan, and Timothy Tsai. (Acceptance Rate: 25%) Best paper Award Runner Up (one of three papers nominated for the award) <\/strong><\/p>\n<\/td>\n<\/tr>\n

DSN’18<\/a><\/td>\n\n

Modeling Input-Dependent Error Propagation in Programs<\/a>, Guanpeng Li, and Karthik Pattabiraman. (Acceptance Rate: 25%)<\/p>\n<\/td>\n<\/tr>\n

ICSE’18<\/a><\/td>\n\n

Inferring Hierarchical Motifs from Execution Traces<\/a>, Saba Alimadadi, Ali Mesbah, and Karthik Pattabiraman. (Acceptance Rate: 21%)<\/p>\n<\/td>\n<\/tr>\n

ASE’17<\/a><\/td>\n\n

Detecting Unknown Inconsistencies in Web Applications<\/a>, Frolin Ocariza, Karthik Pattabiraman, and Ali Mesbah. (Acceptance Rate: 21%)<\/p>\n<\/td>\n<\/tr>\n

SC’17<\/a><\/a><\/td>\n\n

Understanding Error Propagation in Deep learning Neural Networks (DNN) Accelerators and Applications,<\/a> 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. <\/A><\/strong><\/p>\n<\/td>\n<\/tr>\n

FSE’17<\/a><\/td>\n\n

ARTINALI: Dynamic Invariant Detection for Cyber-Physical System Security<\/a>, Maryam Raiyat Aliabadi, Amita Kamath, Julien Samson, and Karthik Pattabiraman. (Acceptance Rate: 24%)<\/p>\n<\/td>\n<\/tr>\n

HPDC’17<\/a><\/td>\n\n

LetGo: A Lightweight Continuous Framework for HPC Applications Under Failures<\/a>, Bo Fang, Qiang Guan, Nathan Debardeleben, Karthik Pattabiraman, and Matei Ripeanu. (Acceptance Rate: 19%)<\/p>\n<\/td>\n<\/tr>\n

DSN’17<\/a><\/td>\n\n

One Bit is (Not) Enough: An Empirical Study of the Impact of Single Bit and Multiple Bit-Flip Errors<\/a>, Behrooz Sangchoolie, Karthik Pattabiraman and Johan Karlsson. (Acceptance Rate: 23%)<\/p>\n<\/td>\n<\/tr>\n

ICST’17<\/a><\/td>\n\n

IPA: Error Propagation Analysis of Multi-threaded Programs Using Likely Invariants<\/a>, Abraham Chan, Stefan Winter, Habib Saissi, Karthik Pattabiraman and Neeraj Suri. (Acceptance Rate: 27%)<\/p>\n<\/td>\n<\/tr>\n

ACSAC’16<\/a><\/td>\n\n

Formal Security Analysis of Smart Embedded Systems<\/a>, Farid Molazem Tabrizi and Karthik Pattabiraman. (Acceptance Rate: 23%).<\/p>\n<\/td>\n<\/tr>\n

SC’16<\/a><\/td>\n\n

Understanding Error Propagation in GPGPU Applications<\/a>, Guanpeng Li, Karthik Pattabiraman, Chen-Yong Cher and Pradip Bose. (Acceptance Rate: 18%)<\/p>\n<\/td>\n<\/tr>\n

EDCC’16<\/a><\/td>\n\n

Finding Resilience-Friendly Compiler Optimizations Using Meta-Heuristic Search Techniques<\/a>, Nithya Narayanamurthy, Karthik Pattabiraman, and Matei Ripeanu. (Acceptance Rate: 41%) (Best Paper Award – one of three<\/strong>) <\/td>\n<\/p>\n<\/tr>\n

SafeComp’16<\/a><\/td>\n\n

FIDL: Fault Injection Description Language for Compiler-Based SFI Tools<\/a>, Maryam Raiyat Ailabadi and Karthik Pattabiraman. (Acceptance Rate: 34%) <\/p>\n<\/td>\n<\/tr>\n

DSN’16<\/a><\/td>\n\n

ePVF: An Enhanced Program Vulnerability Factor Methodology for Cross-Layer Resilience Analysis<\/a>, Bo Fang, Qining Lu, Karthik Pattabiraman, Matei Ripeanu and Sudhanva Gurumurthi. (Acceptance Rate: 21%)<\/p>\n<\/tr>\n

ICST’16<\/a><\/td>\n\n

Inferring Unit Oracles from GUI Test Cases<\/a>, Shabnam Mirshokraie, Ali Mesbah and Karthik Pattabiraman. (Acceptance Rate: 27%)<\/p>\n<\/tr>\n

ICSE’16<\/a><\/td>\n\n

Understanding Asynchronous Interactions in Full-Stack JavaScript<\/a>, Saba Alimadadi, Ali Mesbah and Karthik Pattabiraman. (Acceptance Rate: 19%)<\/p>\n<\/td>\n<\/tr>\n

ISSRE’15<\/a><\/td>\n\n

Experience Report: An Application-specific Checkpointing Technique for Minimizing Checkpoint Corruption<\/a>, Guanpeng Li, Karthik Pattabiraman, Chen-Yong Cher and Pradip Bose. (Acceptance Rate: 32%)<\/p>\n<\/td>\n<\/tr>\n

ASE’15<\/a><\/td>\n\n

Synthesizing Web Element Locators<\/a>, Kartik Bajaj, Karthik Pattabiraman and Ali Mesbah. (Acceptance Rate: 20.8%)<\/p>\n<\/td>\n<\/tr>\n

EDCC’15<\/a><\/td>\n\n

Flexible Intrusion Detection Systems for Memory-Constrained Embedded Systems<\/a>, Farid Molazem Tabrizi and Karthik Pattabiraman. (Acceptance Rate: 45%). Best Paper Award – one of three<\/strong>. <\/p>\n<\/td>\n<\/tr>\n

ECOOP’15<\/a><\/td>\n\n

Hybrid DOM-sensitive Change Impact Analysis for JavaScript<\/a>, Saba Alimadadi, Ali Mesbah and Karthik Pattabiraman. (Acceptance Rate: 22.8%)<\/p>\n<\/td>\n<\/tr>\n

DSN’15<\/a><\/td>\n\n

Fine-Grained Characterization of Faults Causing Long Latency Crashes in Programs<\/a>, Guanpeng Li, Qining Lu and Karthik Pattabiraman. (Acceptance Rate: 22%)<\/p>\n<\/td>\n<\/tr>\n

ICSE’15<\/a><\/td>\n\n

Finding Inconsistencies in JavaScript MVC Applications<\/a>, Frolin Ocariza, Karthik Pattabiraman and Ali Mesbah. (Acceptance Rate: 18.5%)<\/p>\n<\/td>\n<\/tr>\n

ICST’15<\/a><\/td>\n\n

JSEFT: Automated JavaScript Unit Test Generation<\/a>, Shabnam Mirshokraie, Ali Mesbah and Karthik Pattabiraman. (Acceptance Rate: 25%)<\/p>\n<\/td>\n<\/tr>\n

ISSRE’14<\/a><\/td>\n\n

Failure Analysis of Jobs in Compute Clouds: A Google Cluster Case Study<\/a>, Xin Chen, Charng-da Lu and Karthik Pattabiraman. (Acceptance Rate: 25%). Chosen as “Highlights of ISSRE” in 2019 – one of 26 papers out of more than 1000.<\/strong><\/p>\n<\/td>\n<\/tr>\n

CASES’14<\/a><\/td>\n\n

SDCTune: A Model for Predicting the SDC-Proneness of an Application for Configurable Protection<\/a>, Qining Lu, Karthik Pattabiraman, Meeta Gupta and Jude Rivers. (Acceptance Rate: 30%).<\/p>\n<\/td>\n<\/tr>\n

DSN’14<\/a><\/td>\n\n

\nIntegrated Hardware-Software Diagnosis for Intermittent Hardware Faults<\/a>, Majid Dadashi, Layali Rashid, Karthik Pattabiraman and Sathish Gopalakrishnan. (Acceptance Rate: 30%).\n<\/p>\n<\/td>\n<\/tr>\n

DSN’14<\/a><\/td>\n\n

Quantifying the Accuracy of High-Level Fault Injection Techniques for Hardware Faults<\/a>, Jiesheng Wei, Anna Thomas, Guanpeng Li, and Karthik Pattabiraman. (Acceptance Rate: 30%).<\/p>\n<\/td>\n<\/tr>\n

ICSE’14<\/a><\/td>\n\n

Vejovis: Suggesting Fixes for JavaScript Faults<\/a>, Frolin S. Ocariza, Karthik Pattabiraman and Ali Mesbah. (Acceptance Rate: 20%). <\/p>\n<\/td>\n<\/tr>\n

ICSE’14<\/a><\/td>\n\n

Understanding JavaScript Event-Based Interactions<\/a>, Saba Alimadi, Sheldon Sequira, Ali Mesbah and Karthik Pattabiraman (Acceptance Rate: 20%). ACM SIGSOFT Distinguished Paper Award (one of nine papers)<\/p>\n<\/td>\n<\/tr>\n

ASE’14<\/a><\/td>\n\n

Dompletion: DOM-Aware Code Completion<\/a>, Kartik Bajaj, Karthik Pattabiraman and Ali Mesbah. (Acceptance Rate: 20%)<\/p>\n<\/td>\n<\/tr>\n

MSR’14<\/a><\/td>\n\n

Mining Questions Asked by Web Developers<\/a>, Kartik Bajaj, Karthik Pattabiraman and Ali Mesbah. (Acceptance rate: 34%) <\/p>\n<\/td>\n<\/tr>\n

DATE’14<\/a><\/td>\n\n

GPGPUs: How to combine high performance with high reliability<\/a>, L. Bautista Gomez, F. Cappello, L. Carro, N. DeBardeleben, Bo Fang, S. Gurumurthi, Karthik Pattabiraman, P. Rech, M. Sonza Reorda, Embedded Tutorial. <\/p>\n<\/td>\n<\/tr>\n

ISPASS’14 <\/a><\/td>\n\n

GPU-Qin: A Methodology for Evaluating the Error Resilience of GPGPU Applications<\/a>, Bo Fang, Karthik Pattabiraman, Matei Ripeanu and Sudhanva Gurumurthi. (Acceptance rate: 30%) <\/p>\n<\/td>\n<\/tr>\n

HASE’14<\/a><\/td>\n\n

A Model-based Intrusion Detection System for Smart Meters<\/a>, Farid M. Tabrizi and Karthik Pattabiraman. (Acceptance rate: 30%)<\/p>\n<\/td>\n<\/tr>\n

ASE’13<\/a><\/td>\n\n

PYTHIA: Generating Test Cases with Oracles for JavaScript Applications<\/a>, Shabnam Mirshokraie, Ali Mesbah and Karthik Pattabiraman. New Ideas Track (Acceptance rate: 23%)<\/p>\n<\/td>\n<\/tr>\n

ESEM’13<\/a><\/td>\n\n

An Empirical Study of Client-Side JavaScript Bugs<\/a>,
\nFrolin Ocariza, Kartik Bajaj, Karthik Pattabiraman, and Ali Mesbah. (Acceptance rate: 28%) <\/p>\n<\/td>\n<\/tr>\n

DSN’13<\/a><\/td>\n\n

Error Detector Placement for Soft Computation<\/a>,
\nAnna Thomas and Karthik Pattabiraman. (Acceptance rate: 20%)<\/p>\n<\/td>\n<\/tr>\n

ICST’13<\/a><\/td>\n\n

Efficient JavaScript Mutation Testing<\/a>,
\nShabnam Mirshokraie, Ali Mesbah and Karthik Pattabiraman. Best Paper Award Runner Up<\/B> (Acceptance Rate: 25%).<\/p>\n<\/td>\n<\/tr>\n

QEST’12<\/a><\/td>\n\n

Intermittent Errors Recovery: Modeling and Evaluation, <\/a> Layali Rashid, Karthik Pattabiraman and Sathish Gopalakrishnan. (Acceptance Rate: Unknown).<\/p>\n<\/td>\n<\/tr>\n

DSN’12<\/a><\/td>\n\n

BLOCKWATCH: Leveraging Similarity in Parallel Programs for Error Detection<\/a>, Jiesheng Wei and Karthik Pattabiraman. (Acceptance Rate: 17%). <\/p>\n<\/td>\n<\/tr>\n

ICST’12<\/a><\/td>\n\n

AutoFlox: An Automatic Fault Localizer For JavaScript<\/a>, Frolin Ocariza Jr., Karthik Pattabiraman and Ali Mesbah. Best Paper Award Nominee <\/B>. (Acceptance rate: 27 %). <\/p>\n<\/td>\n<\/tr>\n

ISSRE’11<\/a><\/td>\n\n

JavaScript Errors in the Wild: An Empirical Study<\/a>, Frolin Ocariza Jr., Karthik Pattabiraman and Ben Zorn. (Acceptance Rate: 25 %). <\/a> <\/p>\n<\/td>\n<\/tr>\n

CSF’11<\/a><\/td>\n\n

Yarra: An Extension to C for Data Integrity and Partial Safety<\/a>, Cole Schlesinger, Karthik Pattabiraman, Nikhil Swamy, David Walker and Ben Zorn.(Acceptance Rate: 26 %). Forwarded to Journal of Computer Security as one of the best papers at the conference <\/B><\/p>\n<\/td>\n<\/tr>\n

ASPLOS’11<\/a><\/td>\n\n

Flikker: Saving DRAM Refresh-power through Critical Data Partitioning <\/a>, Song Liu, Karthik Pattabiraman, Thomas Moscibroda and Benjamin Zorn. (Acceptance Rate: 20% ). Won the Jean Claude Laprie Award<\/a> in Dependable Computing in 2025.<\/strong> <\/p>\n<\/td>\n<\/tr>\n

PRDC’10<\/a><\/td>\n\n

Modeling the Propagation of Intermittent Hardware Faults in Programs<\/a>, Layali Rashid, Karthik Pattabiraman and Sathish Gopalakrishnan. (Acceptance Rate: 42 %) <\/p>\n<\/td>\n<\/tr>\n

ISSRE’10<\/a><\/td>\n\n

DoDOM: Leveraging DOM Invariants for Web 2.0 Application Robustness Testing<\/a>, Karthik Pattabiraman and Benjamin Zorn. (Acceptance Rate: 31 %)<\/p>\n<\/td>\n<\/tr>\n<\/table>\n

Back to top<\/a><\/p>\n

\n

Selected Workshops and Other<\/A><\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
DSN’25 Industry Track<\/a><\/td>\nLarge-Scale AI Infra Reliability: Challenges, Strategies, and Llama 3 Training Experience<\/a>, Xun Jiao, Abhinav Pandey, Karthik Pattabiraman, and Fred Lin. <\/td>\n<\/tr>\n
DSML’25<\/a><\/td>\nLearning from the Good Ones: Risk Profiling-Based Defenses Against Evasion Attacks on DNNs<\/a>
\nMohammed Elnawawy, Gargi Mitra, Shahrear Iqbal, Karthik Pattabiraman. (Extended abstract) <\/td>\n<\/tr>\n
FITML’24<\/a><\/td>\nHierarchical Unlearning Framework for Multi-Class Classification<\/a>, Abraham Chan, Arpan Gujarati, Karthik Pattabiraman and Sathish Gopalakrishnan. <\/td>\n<\/tr>\n
RICCS’24<\/a><\/td>\nTargeting the Blind Spot: Evaluating Modern ICS Security Against A Novel Denial of Service (DoS) Attack<\/a>, Gargi Mitra, Pritam Dash, Yingao (Elaine) Yao, Aastha Mehta, Karthik Pattabiraman. <\/td>\n<\/tr>\n
HealthSec’24<\/a><\/td>\nSAM: Foreseeing Inference-Time False Data Injection Attacks on ML-enabled Medical Devices<\/a>, Mohammadreza Hallajiyan, Athish Pranav Dharmalingam, Gargi Mitra, Homa Alemzadeh, Shahrear Iqbal and Karthik Pattabiraman. <\/a>\n<\/td>\n<\/tr>\n
AISafety’24<\/a><\/td>\nGlobal Clipper: Enhancing Safety and Reliability of Transformer-based Object Detection Models<\/a>, Qutub Syed, Michael Paulitsch, Karthik Pattabiraman, Korbinian Hagn1, Fabian Oboril, Cornelius Buerkle, Kay-Ulrich Scholl, Gereon Hinz and Alois Knoll. (Acceptance Rate: TBD)<\/td>\n<\/tr>\n
DSN’24-Disrupt<\/a><\/td>\nHarnessing Explainability to Improve ML Ensemble Resilience<\/a>, Abraham Chan, Arpan Gujarati, Karthik Pattabiraman and Sathish Gopalakrishnan. (Acceptance Rate: 45%)<\/td>\n<\/tr>\n
EdgeSys’23<\/a><\/td>\nHot Under the Hood: An Analysis of Ambient Temperature Impact on Heterogeneous Edge Platforms<\/a>, Amirhossein Ahmadi, Hazem AbdelHafez, Shaswat Jaiswal, Karthik Pattabiraman, and Matei Ripeanu. (Acceptance Rate: 42%). Best Paper Award<\/strong><\/td>\n<\/tr>\n
SELSE’23<\/a><\/td>\nTowards Reliability Assessment of Systolic Arrays against Stuck-at Faults<\/a>, Udit Agarwal, Abraham Chan, Ali Asgari and Karthik Pattabiraman, Chosen as \u201cBest of SELSE\u201923\u201d and invited to present at DSN\u201923 – one of three papers.<\/strong><\/td>\n<\/tr>\n
DSML’22<\/a><\/td>\nTowards Building Resilient Ensembles against Training Data Faults<\/em>, Abraham Chan, Arpan Gujarati, Karthik Pattabiraman, and Sathish Gopalakrishnan. <\/td>\n
WoSoCER’21<\/a><\/td>\n\n

(WiP) Low Level Tensor Fault Injector (LLTFI)<\/a>, Abraham Chan, Udit Agarwal, and Karthik Pattabiraman. <\/p>\n<\/td>\n<\/tr>\n

AI Safety’21<\/a><\/td>\n\n

Towards a safety case for hardware-fault tolerance in convolutional neural networks using activation range supervision<\/a>, Florian Geissler, Syed Qutub, Sayanta Roychowdhury, Ali Asgari, Yang Peng, Akash Dhamasia, Ralf Graefe, Karthik Pattabiraman and Michael Paulitsch, Best Paper Award Nominee (1 of 4)<\/strong><\/p>\n<\/td>\n<\/tr>\n

EdgeSys’21<\/a><\/td>\n\n

Snowflakes at the Edge — A Study of Variability among NVIDIA Jetson AGX Xavier Boards<\/a>, Hazem A. Abdelhafez, Hassan Halawa, Karthik Pattabiraman, Matei Ripeanu<\/p>\n<\/td>\n<\/tr>\n

DeepTest’21<\/a><\/td>\n\n

TF-DM: Tool for Studying ML Model Resilience to Data Faults<\/a>, Niranhana Narayanan and Karthik Pattabiraman<\/p>\n<\/td>\n<\/tr>\n

WoSoCER’20<\/a><\/td>\n\n

New Wine in an Old Bottle: N-Version Programming for Machine Learning Components<\/a>, Arpan Gujarati, Sathish Gopalakrishnan, and Karthik Pattabiraman<\/p>\n<\/td>\n<\/tr>\n

Springer book Chapter<\/a><\/td>\nApplication-Aware Reliability and Security: The Trusted Illiac Experience<\/em>, Karthik Pattabiraman, 2020. <\/td>\n<\/tr>\n
HotEdge’19<\/a><\/td>\n\n

OneOS: IoT Platform based on POSIX and Actors<\/a>, Kumseok Jung, Julien Gascon-Samson, and Karthik Pattabiraman<\/p>\n<\/td>\n<\/tr>\n

SELSE’19<\/a><\/td>\n\n

Towards analytically evaluating the error resilience of GPU Programs<\/em>, Abdul Rehman Anwer, Guanpeng Li, Karthik Pattabiraman, Siva Kumar Sastry Hari, Michael Sullivan and Timothy Tsai\n<\/p>\n<\/td>\n<\/tr>\n

CPS-SPC 2018<\/a><\/td>\n\n

CORGIDS: A Correlation-based Generic Intrusion Detection System<\/a>, Ekta Aggarwal, Mehdi Karimibuiki, Karthik Pattabiraman and Andre Ivanov<\/p>\n<\/td>\n<\/tr>\n

WoSoCER 2018<\/a><\/td>\n\n

TensorFI: A Configurable Fault Injector for TensorFlow Applications<\/a>, Guanpeng Li, Karthik Pattabiraman, and Nathan DeBardeleben<\/p>\n<\/td>\n<\/tr>\n

M4IoT 2017<\/a><\/td>\n\n

ThingsJS: Towards a Flexible and Self-Adaptable Middleware for Dynamic and Heterogeneous IoT Environments<\/a>, Julien Gascon-Samson, Mohammad Rafiuzzaman, and Karthik Pattabiraman<\/p>\n<\/td>\n

RSDA’2016<\/a><\/td>\n\n

SDC is in the eye of the beholder: A survey and preliminary study<\/a>, Bo Fang, Panruo Wu, Qiang Guan, Nathan Debardeleben, Laura Monroe, Sean Blanchard, Zhizong Chen, Karthik Pattabiraman, and Matei Ripeanu <\/p>\n<\/td>\n<\/tr>\n

Middleware’15-Student forum<\/a><\/td>\n\n

Intrusion Detection for Embedded Systems<\/a>, Farid Molazem and Karthik Pattabiraman<\/p>\n<\/td>\n<\/tr>\n

\n

ISSRE’15-Industry Track<\/a><\/td>\n

FIDL: A Fault Injection Description Language for Compiler-based Tools, Maryam Raiyat Aliabadi, Karthik Pattabiraman, Nematollah Bidokhti<\/p>\n<\/td>\n<\/tr>\n
\n

ASE’15-Tools Track<\/a><\/td>\n

LED: Tool for Synthesizing Web Element Locators<\/a>, Kartik Bajaj, Karthik Pattabiraman and Ali Mesbah<\/p>\n<\/td>\n<\/tr>\n
\n

ISSRE’14-Industry Track<\/a><\/td>\n

Soft-LLFI: A Comprehensive Framework for Software Fault Injection<\/a>, Maryam Raiyat Aliabadi, Karthik Pattabiraman, Nematollah Bidokhti<\/p>\n<\/td>\n<\/tr>\n
QRS’15<\/a><\/td>\n\n

LLFI: An Intermediate Code-Level Fault Injection Tool for Hardware Faults<\/a> <\/p>\n

Qining Lu, Mostafa Farahani, Jiesheng Wei, Anna Thomas and Karthik Pattabiraman.<\/p>\n<\/td>\n<\/tr>\n

RSDA’14<\/a><\/td>\n\n

Failure Prediction of Jobs in Compute Clouds: A Google Cluster Case Study<\/a>, Xin Chen, Charng-da Lu and Karthik Pattabiraman. <\/p>\n<\/td>\n<\/tr>\n

FTXS’14<\/a><\/td>\n\n

Evaluating the Error Resilience of Parallel Programs<\/a>, Bo Fang, Karthik Pattabiraman, Matei Ripeanu and Sudhanva Gurumurthi. <\/p>\n<\/td>\n<\/tr>\n

AER’13<\/a><\/td>\n\n

Effect of Compiler Optimizations on the Error Resilience of Soft Computing Applications<\/a>, Anna Thomas, Jacques Clapach and Karthik Pattabiraman.<\/p>\n<\/td>\n<\/tr>\n

RSDA’13<\/a><\/td>\n\n

Predicting Job Completion Times Using System Logs in Supercomputing Clusters<\/a>, Xin Chen, Charng-da Lu and Karthik Pattabiraman. <\/p>\n<\/td>\n<\/tr>\n

SELSE’13<\/a><\/td>\n\n

LLFI: An Intermediate Code Level Fault Injector for Soft Computing Applications<\/a>, Anna Thomas and Karthik Pattabiraman. <\/p>\n<\/td>\n<\/tr>\n

SELSE’13<\/a><\/td>\n\n

SCRIBE: A Hardware Infrastructure Enabling Fine-Grained Software Layer Diagnosis<\/a>, Majid Dadashi, Layali Rashid and Karthik Pattabiraman.<\/p>\n<\/td>\n<\/tr>\n

WRA’12<\/td>\n\n

Towards Building Error Resilient GPGPU Applications<\/a>, Bo Fang, Jiesheng Wei, Karthik Pattabiraman and Matei Ripeanu.<\/p>\n<\/td>\n<\/tr>\n

WRAITS’12<\/a><\/td>\n\n

A Model for Security Analysis of Smart Meters<\/a>, Farid M. Tabrizi and Karthik Pattabiraman.<\/p>\n<\/td>\n<\/tr>\n

SELSE’12 <\/a><\/td>\n\n

DIEBA: Diagnosing Intermittent Errors by Backtracing Application Failures<\/a>, Layali Rashid, Karthik Pattabiraman and Sathish Gopalakrishnan<\/p>\n<\/td>\n<\/tr>\n

SELSE’12 <\/a><\/td>\n\n

BlockWatch: Leveraging Similarity in Parallel Programs for Error Detection<\/a>, Jiesheng Wei and Karthik Pattabiraman.<\/p>\n<\/td>\n<\/tr>\n

WDSN’11<\/a><\/td>\n\n

Comparing the Effects of Transient and Intermittent Faults on Programs<\/a>, Jiesheng Wei, Layali Rashid, Sathish Gopalakrishnan and Karthik Pattabiraman.<\/p>\n<\/td>\n<\/tr>\n

WDSN’10<\/a><\/td>\n\n

Towards Understanding the Effects of Intermittent Hardware Faults on Programs<\/a>, Layali Rashid, Karthik Pattabiraman and Sathish Gopalakrishnan. <\/p>\n<\/td>\n<\/tr>\n

SELSE’10<\/a><\/td>\n\n

Formal Diagnosis of Hardware Transient Errors in Programs <\/a>, Layali Rashid, Karthik Pattabiraman, and Sathish Gopalakrishnan, Workshop on Silicon Errors in Logic, System Effects (SELSE)<\/a>, 2010, Palo Alto, CA. <\/p>\n<\/td>\n<\/tr>\n<\/table>\n

Back to top<\/a><\/p>\n

\n

Patents<\/a><\/strong><\/p>\n\n\n\n
\n

Providing Hardware Resources having Different Reliabilities for Use by an Application, with Benjamin Zorn, Thomas Moscibroda and Song Liu, Sep 2011, USA (patent number 20110231601A1). <\/p>\n<\/td>\n<\/tr>\n

\n

Leveraging On-Chip Variability, B Zorn, D Kirovski, R Bittner, K Pattabiraman, Dec 2011 (Patent# 20110314210).<\/p>\n<\/td>\n<\/tr>\n<\/table>\n

Back to top<\/a><\/p>\n

\n
\n

Talks<\/a><\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Building Reliable ML Systems from Unreliable Components<\/a>, Intelligent Visual Computing and Consumer Device Summit, Simon Fraser University (SFU), November 2025.<\/p>\n<\/td>\n<\/tr>\n

\n

Building Error-Resilient and Attack-Resilient Machine Learning Systems<\/a>, Foundations of AI Seminar Series, Georgia Tech. November 2025.<\/p>\n<\/td>\n<\/tr>\n

\n

Jean Claude Laprie Award Presentation at DSN’25<\/a><\/p>\n<\/td>\n<\/tr>\n

\n

Machine Learning Reliabiility and Security: Old Wine in a New Bottle or Not?,<\/a> Keynote talk at the Dependable and Secure Machine Learning Workshop (DSML),<\/a> co-held with the IEEE Dependable and Secure networks (DSN) conference, 2025.<\/p>\n<\/td>\n<\/tr>\n

\n

Error-Resilient Machine Learning for HPC: Challenges and Opportunities <\/a>, Featured talk at FTXS’24 Workshop<\/a>, co-held with SC 2024. <\/p>\n<\/td>\n<\/tr>\n

\n

In Autonomy We Trust: Building Autonomous Systems for a Safer Future<\/a>, SUTD\/SMU\/ADSC\/IITM\/IBM Talk, 2024.<\/p>\n<\/td>\n<\/tr>\n

\n

Security Challenges and Opportunities in Decentralized Finance (DeFi)<\/a>, Nanyang Techological University (NTU) Blockchain Symposium, 2024<\/a>. <\/p>\n<\/td>\n<\/tr>\n

\n

Secure and Resilient Cyber-Physical Systems for Critical Infrastructure<\/a>, BDRC Cybersecurity Conference<\/a>, Laval Univ, 2024.<\/p>\n<\/td>\n<\/tr>\n

\n

Building Error-resilient and attack-resilient ML-Enabled CPS<\/a>, IFIP WG 10.4 Workshop on ML-Enabled CPS, 2024. <\/p>\n<\/td>\n<\/tr>\n

\n

Fault Injection is Dead. Long Live Fault Injection!<\/a>, Keynote talk at VERDI’23<\/a> Workshop.<\/p>\n<\/td>\n<\/tr>\n

\n

Building Error Resilient Machine Learning Systems from Unreliable Components<\/a>, Univ of Lisboa and Univ of Coimbra, June 2023. <\/p>\n<\/td>\n<\/tr>\n

\n

From Padawan to Jedi Knight: The nine trials of a PhD student<\/a>, ISSRE 2022 Doctoral Symposium<\/a> Keynote, October 2022. <\/p>\n<\/td>\n<\/tr>\n

\n

In Autonomy We Trust: Building Trustworthy Autonomous Systems for a Safer Future<\/a>, Lakehead University Computer Science Department Seminar, October 2022. <\/p>\n<\/td>\n<\/tr>\n

\n

The Barbarians are at the Gate: Security Vulnerabilities of the IoT and their Implications<\/a>, Chartered Engineers Pacific, Invited Talk, March 2022. <\/p>\n<\/td>\n<\/tr>\n

\n

Failure Data EveryWhere, but not a Failure in Sight! The joys and frustrations of analyzing open data sources<\/a>, Keynote talk at the RSDA 2021<\/a> workshop. <\/p>\n<\/td>\n<\/tr>\n

\n

Detection is Not Enough: Low-Cost Error and Attack Recovery in Autonomous Systems<\/a>, Invited guest lecture at the University of Illinois (UIUC), 2021.<\/p>\n<\/td>\n<\/tr>\n

\n

Looking to the Past to Predict the Future<\/a> (An invited talk at the 25th anniversary celebration of my undergraduate alma mater – SVCE IT department), 2021.<\/p>\n<\/td>\n<\/tr>\n

\n

Good Enough Dependability – A Unified Paradigm for Dependable Systems Design (“Rising Star in Dependability Award” at DSN 2020)<\/a> (Video<\/a>) <\/p>\n<\/td>\n<\/tr>\n

\n

Modeling Hardware Error Propagation in Programs for Low-Cost Dependability<\/a><\/p>\n<\/td>\n<\/tr>\n

\n

Building Reliable Software for the Web, IoT and Beyond …<\/a><\/p>\n<\/td>\n<\/tr>\n

\n

Resilience and Security in Cyber-Physical Systems: Self-Driving Cars and Smart Devices<\/a> (Video<\/a>) <\/p>\n<\/td>\n<\/tr>\n

\n

Tolerating Hardware Faults in Commodity Software: Problems, Solutions and a Roadmap<\/a><\/p>\n<\/td>\n<\/tr>\n

\n

Security and Reliability of the Internet of Things: A Smart Meter Case Study<\/a><\/p>\n<\/td>\n<\/tr>\n

\n

How I learned to Stop Worrying and Love the DOM<\/a><\/p>\n<\/td>\n<\/tr>\n

\n

Does Error Resilience Matter in the age of Approximate Computing?<\/a><\/p>\n<\/td>\n<\/tr>\n

\n

Approximate Computing and Error Resilient Systems: Conjoined Twins Separated at Birth?<\/a><\/p>\n<\/td>\n<\/tr>\n

\n

Tolerating Silent Data Corruption (SDC) causing Hardware Faults Through Software Techniques<\/a> <\/p>\n<\/td>\n<\/tr>\n

\n

Model-Based Intrusion Detection System (IDS) for Smart Meters<\/a><\/p>\n<\/td>\n<\/tr>\n

\n

Why do Web Applications Fail and What Can We do About it<\/a> <\/p>\n<\/td>\n<\/tr>\n

\n

Good Enough Systems: Tolerating (most) hardware Errors using Software<\/a><\/p>\n<\/td>\n<\/tr>\n

\n

Towards Improving the Reliability of JavaScript-Based Web Applications<\/a><\/p>\n<\/td>\n<\/tr>\n

\n

Good Enough Computer Systems: Reliability on the Cheap<\/a><\/p>\n<\/td>\n<\/tr>\n<\/table>\n

Back to top<\/a><\/p>\n

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