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Vipin Kumar Kukkala, Ph.D.
About me
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Posts
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portfolio
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publications
C1. Priority-based Multi-level Monitoring of Signal Integrity in a Distributed Powertrain Control System
Published in IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling, 2015
Recommended citation: V. K. Kukkala, T. Bradley, and S. Pasricha, "Priority-based Multi-level Monitoring of Signal Integrity in a Distributed Powertrain Control System," in Proc. of 4th IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling, July 2015.
P1. Reliability Aware Message Scheduling for FlexRay Automotive Networks
Presented at CSU Ventures Innovation Forum, 2016
PC1. EcoCAR 3 Students Drive Innovation
Published in Colorado State University College Avenue, 2017
PC2. EcoCAR 3 secures top-8 finishes and sportsmanship award at Year Three Competition
Published in Colorado State University Source Magazine, 2017
P2. Uncertainty Analysis and Propagation for an Auxiliary Power Module
Presented at IEEE Transportation Electrification Conference (ITEC), 2017
C2. Uncertainty analysis and propagation for an Auxiliary Power Module
Published in IEEE Transportation Electrification Conference (ITEC), 2017
Recommended citation: V. K. Kukkala, T. Bradley, and S. Pasricha, "Uncertainty Analysis and Propagation for an Auxiliary Power Module," in Proc. of IEEE Transportation Electrification Conference (ITEC), June 2017.
C3. JAMS: Jitter-Aware Message Scheduling for FlexRay Automotive Networks
Published in IEEE/ACM International Symposium on Network-on-Chip (NOCS), 2017
Recommended citation: V. K. Kukkala, S. Pasricha, and T. Bradley, "JAMS: Jitter-Aware Message Scheduling for FlexRay Automotive Networks," in Proc. of IEEE/ACM International Symposium on Network-on-Chip (NOCS), October 2017.
J1. Advanced Driver-Assistance Systems: A path toward autonomous vehicles
Published in IEEE Consumer Electronics Magazine (CEM), 2018
Recommended citation: V. K. Kukkala, J. Tunnell, S. Pasricha and T. Bradley, "Advanced Driver-Assistance Systems: A Path Toward Autonomous Vehicles," in IEEE Consumer Electronics Magazine (CEM), vol. 7, no. 5, pp. 18-25, Sept. 2018.
PC3. And they’re off again: CSU chosen for EcoCAR Mobility Challenge
Published in Colorado State University Source Magazine, 2018
C4. Colorado State University EcoCAR 3 Final Technical Report
Published in SAE World Congress Experience (WCX), 2019
Recommended citation: G. C. DiDomenico, J. Bair, V. K. Kukkala, et al., "Colorado State University EcoCAR 3 Final Technical Report," in SAE World Congress Experience (WCX), April 2019.
J2. JAMS-SG: A Framework for Jitter-Aware Message Scheduling for Time-Triggered Automotive Networks
Published in ACM Transactions on Design Automation of Electronic Systems (TODAES), 2019
Recommended citation: V. K. Kukkala, S. Pasricha, and T. Bradley, "JAMS-SG: A Framework for Jitter-Aware Message Scheduling for Time-Triggered Automotive Networks," in ACM Transactions on Design Automation of Electronic Systems (TODAES), Vol. 24, Iss. 6, September 2019.
PF1. ROSETTA: Robust and Secure Resource Management for Time-Critical Automotive Systems
Presented at IEEE/ACM Design Automation Conference (DAC) Ph.D. Forum, 2020
J3. SEDAN: Security-Aware Design of Time-Critical Automotive Networks
Published in IEEE Transactions on Vehicular Technology (TVT), 2020
Recommended citation: V. Kukkala, S. Pasricha, and T. Bradley, "SEDAN: Security-Aware Design of Time-Critical Automotive Networks," in IEEE Transaction on Vehicular Technology (TVT), Vol. 69, Iss. 8, August 2020.
J4. INDRA: Intrusion Detection using Recurrent Autoencoders in Automotive Embedded Systems
Published in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2020
Recommended citation: V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, "INDRA: Intrusion Detection using Recurrent Autoencoders in Automotive Embedded Systems," in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Vol. 39, Iss. 11, November 2020.
J5. LATTE: LSTM Self-Attention based Anomaly Detection in Embedded Automotive Platforms
Published in ACM Transactions on Embedded Computing Systems, 2021
Recommended citation: V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, "LATTE: LSTM Self-Attention based Anomaly Detection in Embedded Automotive Platforms," in ACM Transactions on Embedded Computing Systems (TECS), Vol. 20, No. 5s, Article 67, August 2021.
C5. Designing Heterogeneous Systems: Large Scale Architectural Exploration Via Simulation
Published in IEEE/ACM Programming Environments for Heterogeneous Computing (PEHC), 2021
Recommended citation: D. Emmot, R. Menhusen, D. Dauwe, V. K. Kukkala, and K. Bresniker, "Designing Heterogeneous Systems: Large Scale Architectural Exploration Via Simulation," in Proc. of IEEE/ACM Programming Environments for Heterogeneous Computing (PEHC), December 2021.
C6. TENET: Temporal CNN with Attention for Anomaly Detection in Automotive Cyber-Physical Systems ( ** Best paper award candidate ** )
Published in IEEE/ACM Asia & South Pacific Design Automation Conference (ASPDAC), 2022
Recommended citation: S. V. Thiruloga, V. K. Kukkala, and S. Pasricha, "TENET: Temporal CNN with Attention for Anomaly Detection in Automotive Cyber-Physical Systems," in Proc. of IEEE/ACM Asia & South Pacific Design Automation Conference (ASPDAC), January 2022.
D1. Robust and Secure Resource Management for Automotive Cyber-Physical Systems
Colorado State University, 2022
Recommended citation: V. K. Kukkala, "Robust and Secure Resource Management for Automotive Cyber-Physical Systems," Colorado State University, 2022.
J6. Roadmap for Cybersecurity in Autonomous Vehicles
Published in IEEE Consumer Electronics Magazine, 2022
Recommended citation: V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, "Roadmap for Cybersecurity in Autonomous Vehicles," in IEEE Consumer Electronics Magazine (CEM), February 2022.
BC1. AI for Cybersecurity in Distributed Automotive IoT Systems
Published in Springer Nature, 2023
Recommended citation: V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, "AI for Cybersecurity in Distributed Automotive IoT Systems," in Frontiers of Quality Electronic Design (QED), Springer Nature, 2023.
PT1. System and method for predicting power usage of network components
Published in U.S. Patent (US11644882B2), 2023
Recommended citation: H. Kuno, A. Davis, T. Wilde, D. W. Dauwe, D. Roweth, R. D. Menhusen, S. Serebryakov, J. L. Byrne, V. K. Kukkala, and S. R. Chalamalasetti, Hewlett Packard Enterprise Development LP, 2023. System and method for predicting power usage of network components. U.S. Patent (US11644882B2)
B1. Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems
Published in Springer Nature, 2023
Recommended citation: V. K. Kukkala and S. Pasricha, "Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems," in Springer Nature, 2023.
BC3. Reliable Real-Time Message Scheduling in Automotive Cyber-Physical Systems
Published in Springer Nature, 2023
Recommended citation: V. K. Kukkala, T. Bradley, and S. Pasricha, "Reliable Real-Time Message Scheduling in Automotive Cyber-Physical Systems," in Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems, Springer Nature, 2023.
BC4. Security-Aware Design of Time-Critical Automotive Cyber-Physical Systems
Published in Springer Nature, 2023
Recommended citation: V. K. Kukkala, T. Bradley, and S. Pasricha, "Security-Aware Design of Time-Critical Automotive Cyber-Physical Systems," in Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems, Springer Nature, 2023.
BC5. Real-Time Intrusion Detection in Automotive Cyber-Physical Systems with Recurrent Autoencoders
Published in Springer Nature, 2023
Recommended citation: V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, "Real-Time Intrusion Detection in Automotive Cyber-Physical Systems with Recurrent Autoencoders," in Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems, Springer Nature, 2023.
BC6. Stacked LSTM Based Anomaly Detection in Time-Critical Automotive Networks
Published in Springer Nature, 2023
Recommended citation: V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, "Stacked LSTM Based Anomaly Detection in Time-Critical Automotive Networks," in Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems, Springer Nature, 2023.
BC7. Deep AI for Anomaly Detection in Automotive Cyber-Physical Systems
Published in Springer Nature, 2023
Recommended citation: S. V. Thiruloga, V. K. Kukkala, and S. Pasricha, "Deep AI for Anomaly Detection in Automotive Cyber-Physical Systems," in Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems, Springer Nature, 2023.
BC2. Machine Learning for Anomaly Detection in Automotive Cyber-Physical Systems
Published in Springer Nature, 2023
Recommended citation: V. K. Kukkala, S. V. Thiruloga, and S. Pasricha, "Machine Learning for Anomaly Detection in Automotive Cyber-Physical Systems," in Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing, Springer Nature, 2023.
research
Advanced Driver Assistance Systems (ADAS) & Connected Automated Vehicles (CAVs)
Research and hands-on experience
Hybrid Electric Vehicles (HEVs)
Research and hands-on experience
Reliability in Automotive Networks
Fault-tolerant network design
Network Modeling, Simulation, and Schedule Synthesis
Cyber-physical systems and large-scale HPC systems
High-Performance Computing (HPC)
Accelerating scientific computing and HPC+AI workloads
Cybersecurity in Autonomous Vehicles
Using deep learning and optimization techniques
talks
DAC PhD Forum, 2020 - Vipin Kumar Kukkala
This is my PhD forum presentation at IEEE/ACM Design Automation Conference (DAC), 2020. In this talk I give a high level overview of my Ph.D. research.
CASES 2020 - INDRA: Intrusion Detection using Recurrent Autoencoders in Automotive Embedded Systems
INDRA (Intrusion Detection using Recurrent Autoencoders in Automotive Embedded Systems) is a novel deep learning based intrusion detection framework that is designed to detect cyber-attacks in vehicles. This work got accepted in CASES conference at Embedded Systems Week 2020 and published in IEEE TCAD journal.
CODES+ISSS 2021 - LATTE (Lightning Talk)
LATTE: LSTM Self-Attention based Anomaly Detection in Embedded Automotive Platforms, is a novel deep learning based anomaly detection framework that is designed to detect cyber-attacks in vehicles. This work got accepted in CODES+ISSS conference at Embedded Systems Week 2021 and published in IEEE TECS journal.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.