Publications

S. Ghiasvand, A. Reisizadeh, M. Alizadeh, R. Pedarsani, “Robust Decentralized Learning with Local Updates and Gradient Tracking”, IEEE Transactions on Networking, 2025.

S. Hutchinson, A. Zibaie, R. Pedarsani, M. Alizadeh, “Optimistic Algorithms for Safe Linear Bandits under General Constraints”, IEEE Open Journal of Control Systems, 2025.

H. Taheri, R. Pedarsani, C. Thrampoulidis, “Asymptotic Behavior of Adversarial Training in Binary Linear Classification”, IEEE Transactions on Neural Networks and Learning Systems, 2025.

M. Beliaev, N. Mehr, R. Pedarsani, “Pricing for Multi-modal Pickup and Delivery Problems with Heterogeneous Users”, Journal of Transportation Research Part C, 2024.

B. Puranik, O. Guldogan, U. Madhow, R. Pedarsani, “Long-Term Fairness in Sequential Multi-Agent Selection with Positive Reinforcement”, IEEE Journal on Selected Areas in Information Theory, 2024.

M. Beliaev, P. Delgosha, H. Hassani, R. Pedarsani, “Efficient and Robust Classification for Sparse Attacks”, IEEE Journal on Selected Areas in Information Theory, 2024.

P. Delgosha, H. Hassani, R. Pedarsani, “Binary Classification Under l0 Attacks for General Noise Distribution”, IEEE Transactions on Information Theory (IT), 2024.

J. Kang, R. Pedarsani, K. Ramchandran, “The Fair Value of Data Under Heterogeneous Privacy Constraints in Federated Learning”, Transactions on Machine Learning Research (TMLR), 2024.

M. Fereydounian, A. Mokhtari, R. Pedarsani, H. Hassani, “Provably Private Distributed Averaging Consensus: An Information-Theoretic Approach”, IEEE Transactions on Information Theory (IT), 2023.

I. Tziotis, Z. Shen, R. Pedarsani, H. Hassani, A. Mokhtari, “Straggler-Resilient Personalized Federated Learning”, Transactions on Machine Learning Research (TMLR), 2023.

M. Beliaev, N. Mehr, R. Pedarsani, “Congestion-aware Bi-modal Delivery Systems Utilizing Drones”, Journal of Future Transportation, 2023.

A. Reisizadeh, I. Tziotis, H. Hassani, A. Mokhtari, R. Pedarsani, “Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity”, IEEE Journal on Selected Areas in Information Theory, 2022.

B. Puranik, U. Madhow, R. Pedarsani, “Generalized Likelihood Ratio Test for Adversarially Robust Hypothesis Testing”, IEEE Transactions on Signal Processing (TSP), 2022.

F. Farnia, A. Reisizadeh, R. Pedarsani, A. Jadbabaie, “An Optimal Transport Approach to Personalized Federated Learning”, IEEE Journal on Selected Areas in Information Theory, 2022.

B. Toghi, R. Valiente, D. Sadigh, R. Pedarsani, Y. Fallah, “Social Coordination and Altruism in Cooperative Autonomous Driving”, IEEE Transactions on Intelligent Transportation Systems (TITS), 2022.

R. Valiente, B. Toghi, R. Pedarsani, Y. Fallah, “Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy Traffic”, IEEE Open Journal of Intelligent Transportation Systems, 2022.

P. Delgosha, H. Hassani, R. Pedarsani, “Robust Classification Under l0 Attack for the Gaussian Mixture Model”, SIAM Journal on Mathematics of Data Science (SIMODS), Vol. 4, No. 1, 2022.

A. Reisizadeh, S. Prakash, R. Pedarsani, S. Avestimehr, “CodedReduce: A Fast and Robust Framework for Gradient Aggregation in Distributed Learning”, IEEE Transactions on Networking, Vol. 30, No. 1, 2022.

D. Lazar, E. Biyik, D. Sadigh, and R. Pedarsani, “Learning How to Dynamically Route Autonomous Vehicles on Shared Roads", Journal of Transportation Research Part C, Vol. 130, 2021.

C. Yang, R. Pedarsani, S. Avestimehr, “Edge Computing in the Dark: Leveraging Contextual-Combinatorial Bandit and Coded Computing”, IEEE/ACM Transactions on Networking (ToN), Vol. 29, No. 3, 2021.

H. Taheri, R. Pedarsani, C. Thrampoulidis, “Sharp Guarantees and Optimal Performance for Inference in Binary and Gaussian-mixture Models”, Entropy: Special Issue on the Role of Signal Processing and Information Theory in Modern Machine Learning, Vol. 23, No. 2, 2021.

E. Biyik, D. Lazar, R. Pedarsani, D. Sadigh “Incentivizing Efficient Equilibria in Traffic Networks with Mixed Autonomy", IEEE Transactions on Control of Network Systems (TCNS), Vol. 8, No. 4, 2021.

D. Lazar and R. Pedarsani, “Optimal Tolling for Multitype Mixed Autonomous Traffic Networks”, IEEE Control Systems Letters, Vol. 5, No. 5, 2021.

D. Lazar, S. Coogan, and R. Pedarsani, “Routing for Traffic Networks with Mixed Autonomy”, IEEE Transactions on Automatic Control (TAC), Vol. 66, No. 6, 2021.

B. Turan, R. Pedarsani, M. Alizadeh, “Dynamic Pricing and Fleet Management for Electric Autonomous Mobility on Demand Systems”, Journal of Transportation Research Part C, Vol. 121, 2020.

S. Prakash, A. Reisizadeh, R. Pedarsani, S. Avestimehr, "Coded Computing for Distributed Graph Analytics”, IEEE Transactions on Information Theory, Vol. 66, No. 10, 2020.

Q. Wei, J. R. Pedarsani, S. Coogan, “Mixed Autonomy in Ride-Sharing Networks”, IEEE Transactions on Control of Network Systems (TCNS), Vol. 7, No. 4, 2020.

A. Reisizadeh, A. Mokhtari, H. Hassani, R. Pedarsani, “An Exact Quantized Decentralized Gradient Descent Algorithm”, IEEE Transactions on Signal Processing (TSP), Vol. 67, No. 19, 2019.

C. Yang, R. Pedarsani, S. Avestimehr, “Communication-Aware Scheduling of Serial Tasks for Dispersed Computing”, IEEE/ACM Transactions on Networking, Vol. 27, No. 4, 2019.

A. Reisizadeh, S. Prakash, R. Pedarsani, S. Avestimehr, “Coded Computation over Heterogeneous Clusters”, IEEE Transactions on Information Theory, Vol. 65, No. 7, 2019.

X. Li, D. Yin, S. Pawar, R. Pedarsani, and K. Ramchandran, “Sub-linear Time Support Recovery for Compressed Sensing Using Sparse-Graph Codes”, IEEE Transactions on Information Theory, Vol. 65, No. 10, 2019.

K. Lee, K. Chandrasekher, R. Pedarsani, and K. Ramchandran, “SAFFRON: A Fast, Efficient, and Robust Framework for Group Testing based on Sparse-Graph Codes”, Vol. 67, No. 17, IEEE Transactions on Signal Processing, 2019.

D. Yin, R. Pedarsani, Y. Chen, and K. Ramchandran, “Learning Mixtures of Sparse Linear Regressions Using Sparse Graph Codes”, IEEE Transactions on Information Theory, Vol. 65, No. 3, 2019.

K. Lee, M. Lam, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran, “Speeding Up Distributed Machine Learning Using Codes”, IEEE Transactions on Information Theory, Vol. 64, No. 3, 2018. (Joint Comm/IT Society Paper Award)

R. Pedarsani, K. Lee, and K. Ramchandran, “PhaseCode: Fast and Efficient Compressive Phase Retrieval based on Sparse-Graph Codes”, IEEE Transactions on Information Theory, Vol. 63, No. 6, 2017.

R. Pedarsani, J. Walrand, and Yuan Zhong, “Robust Scheduling for Flexible Processing Networks”, Advances in Applied Probability, Vol. 49, No. 2, 2017.

J. Lioris, R. Pedarsani, F. Yildiz, and P. Varaiya, “Platoons of Connected Vehicles Can Double Throughput in Urban Roads”, Journal of Transportation Research Part C, vol. 75, pp. 292-305, 2017.

R. Pedarsani and J. Walrand, “Stability of Open Multiclass Queueing Networks under Longest-Queue and Longest-Dominating-Queue Scheduling”, Journal of Applied Probability, Vol. 53, No. 2, 2016.

R. Pedarsani, M. Maddah-Ali, and U. Niesen, “Online Coded Caching”, IEEE/ACM Transactions on Networking, Vol. 24, No. 2, 2016.

A. Muralidharan, R. Pedarsani, and P. Varaiya, “Analysis of Fixed-Time Control”, Journal of Transportation Research Part B, vol. 73, pp. 81–90, 2015.

K. Lee, R. Pedarsani, and K. Ramchandran, “On Scheduling Redundant Requests with Cancellation Overheads”, IEEE/ACM Transactions on Networking, Vol. 25, No. 2, pp. 1279–1290, 2017.

R. Pedarsani, O. Leveque, and S. Yang, “On the DMT Optimality of Time-Varying Distributed Rotation over Slow Fading Relay Channels”, IEEE Transactions on Wireless Communication, vol. 14, pp. 421–434, 2015.

Z. Xue, Z. Qi, G. Liu, B. Chen, R. Pedarsani, “Deactivating Refusal Triggers: Understanding and Mitigating Overrefusal in Safety Alignment”, Proceedings of the 6th Workshop on Trustworthy NLP (TrustNLP), 2026.

P. Madinei, R. Solgi, Z. Wen, J. Skaza, M. Eckstein, R. Pedarsani, “INTERLACE: Interleaved Layer Pruning and Efficient Adaptation in Large Vision-Language Models”, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.

S. Ghiasvand, M. Alizadeh, R. Pedarsani, “pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language Models”, International Conference on Learning Representations (ICLR), 2026.

Z. Xue, R. Abbasi-Asl, R. Pedarsani, “Enhancing the Safety of Medical Vision-Language Models by Synthetic Demonstrations”, The 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2026.

Z. Xue, R. Abbasi-Asl, R. Pedarsani, “Benchmarking and Mitigating the Impact of Noisy User Prompts in Medical VLMs via Cross-Modal Reflection”, The 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL) Industry Track, 2026.

S. Ghiasvand, H. Ehsani Oskouie, M. Alizadeh, R. Pedarsani, “Few-Shot Adversarial Low-Rank Fine-Tuning of Vision-Language Models”, Trustworthy AI Workshop at the International Conference on Learning Representations (ICLR), 2026.

S. Ghiasvand, Y. Yang, Z. Xue, M. Alizadeh, Z. Zhang, R. Pedarsani, “Communication-Efficient and Tensorized Federated Fine-Tuning of Large Language Models”, The 63rd Annual Meeting of the Association for Computational Linguistics (ACL) Findings, 2025.

M. Beliaev, R. Pedarsani, “Inverse Reinforcement Learning by Estimating Expertise of Demonstrators”, Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2025.

Z. Xue, H. Wang, Y. Qin, R. Pedarsani, “Conflict-Aware Adversarial Training”, British Machine Vision Conference (BMVC), 2025.

J. Kang, L. Butler, A. Agarwal, Y. Erginbas, R. Pedarsani, K. Ramchandran, B. Yu, “SPEX: Scaling Feature Interaction Explanations for LLMs”, International Conference on Machine Learning (ICML) 2025.

S. Ghiasvand, M. Alizadeh, R. Pedarsani, “Decentralized Low-Rank Fine-Tuning of Large Language Models”, Workshop for Research on Agent Language Models (REALM), 2025.

J. Kang, Y. Erginbas, L. Butler, R. Pedarsani, K. Ramchandran, “Learning to Understand: Identifying Interactions via the Mobius Transform”, Advances in Neural Information Processing Systems (NeurIPS), 2024.

O. Guldogan, Y. Zeng, J. Sohn, R. Pedarsani, K. Lee, “Equal Improvability: A New Fairness Notion Considering the Long-Term Impact”, International Conference on Learning Representations (ICLR), 2023.

J. Kang, R. Pedarsani, K. Ramchandran, “The Fair Value of Data Under Heterogeneous Privacy Constraints in Federated Learning”, International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS 2023.

M. Beliaev, A. Shih, S. Ermon, D. Sadigh, R. Pedarsani, “Imitation Learning by Estimating Expertise of Demonstrators”, International Conference on Machine Learning (ICML), 2022.

B. Puranik, U. Madhow, R. Pedarsani, “A Dynamic Decision-Making Framework Promoting Long-Term Fairness”, AAAI/ACM Conference on Artificial Intelligent, Ethics, and Society (AIES), 2022.

B. Puranik, U. Madhow, R. Pedarsani, “Dynamic Positive Reinforcement for Long-Term Fairness”, International Conference on Learning Representations (ICLR) 2022 Workshop on Socially Responsible Machine Learning.

W. Wang, M. Beliaev, E. Biyik, D. Lazar, R. Pedarsani, and D. Sadigh, “Emergent Prosociality in Multi-Agent Games Through Gifting”, International Joint Conference on Artificial Intelligence (IJCAI), 2021.

H. Taheri, R. Pedarsani, C. Thrampoulidis, “Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions”, International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.

B. Toghi, R. Valiente, D. Sadigh, R. Pedarsani, Y. Fallah, “Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic”, 2021 ADP3 Workshop at IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

A. Reisizadeh, F. Farnia, R. Pedarsani, A. Jadbabaie, “Robust Federated Learning: The Case of Affine Distribution Shifts”, Advances in Neural Information Processing Systems (NeurIPS), 2020.

H. Taheri, A. Mokhtari, H. Hassani, R. Pedarsani, “Quantized Decentralized Stochastic Learning over Directed Graphs”, International Conference on Machine Learning (ICML), 2020.

A. Reisizadeh, A. Mokhtari, H. Hassani, A. Jadbabaie, R. Pedarsani, “FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization”, International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.

H. Taheri, R. Pedarsani, C. Thrampoulidis, “Sharp Asymptotics and Optimal Performance for Inference in Binary Models”, International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.

M. Beliaev, W. Wang, D. Lazar, E. Biyik, D. Sadigh, and R. Pedarsani, “Emergent Correlated Equilibrium through Synchronized Exploration”, Robotics: Science and Systems (RSS) Workshop on Emergent Behaviors in Human-Robot Systems, 2020.

A. Reisizadeh, H. Taheri, A. Mokhtari, H. Hassani, R. Pedarsani, “Robust and Communication-Efficient Collaborative Learning”, Advances in Neural Information Processing Systems (NeurIPS), 2019.

C. Yang, R. Pedarsani, S. Avestimehr, “Timely-Throughput Optimal Coded Computing over Cloud Networks”, ACM International Symposium on Mobile Ad Hoc Networking and Computing (Mobihoc), 2019. (Best Paper Award Finalist)

E. Biyik, D. Lazar, R. Pedarsani, D. Sadigh , “Altruistic Autonomy: Beating Congestion on Shared Roads”, 13th International Workshop on Algorithmic Foundations of Robotics (WAFR), 2018.

S. Gopalakrishnan, Z. Marzi, U. Madhow, and R. Pedarsani, “Combating Adversarial Attacks Using Sparse Representation”, International Conference on Learning Representations (ICLR) Workshop track, 2018.

J. Chung, K. Lee, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran, “UberShuffle: Communication-efficient Data Shuffling for SGD via Coding Theory”, Neural Information Processing Systems (NeurIPS): Workshop on Machine Learning Systems, 2017.

K. Lee, M. Lam, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran, “Speeding Up Distributed Machine Learning Using Codes”, Neural Information Processing Systems (NeuIPS): Workshop on Machine Learning Systems, 2015.

A. Zibaie, S. Hutchinson, R. Pedarsani, M. Alizadeh, “The Safety-Privacy Tradeoff in Linear Bandits”, IEEE International Symposium on Information Theory (ISIT), 2025.

S. Ghiasvand, A. Reisizadeh, M. Alizadeh, R. Pedarsani, “Communication-efficient and Decentralized Federated Minimax Optimization”, Allerton Conference on Communication, Control, and Computing, 2024.

P. Delgosha, H. Hassani, R. Pedarsani, “Generalization Properties of Adversarial Training for l0-Bounded Adversarial Attacks”, IEEE Information Theory Workshop (ITW), 2023.

P. Delgosha, H. Hassani, R. Pedarsani, “Binary Classification Under l0 Attacks for General Noise Distribution”, IEEE International Symposium on Information Theory (ISIT), 2022.

M. Beliaev, P. Delgosha, H. Hassani, R. Pedarsani, “Efficient and Robust Classification for Sparse Attacks”, IEEE International Symposium on Information Theory (ISIT), 2022.

H. Taheri, R. Pedarsani, C. Thrampoulidis, “Asymptotic Behavior of Adversarial Training in Binary Classification”, IEEE International Symposium on Information Theory (ISIT), 2022.

A. Reisizadeh, I. Tziotis, H. Hassani, A. Mokhtari, R. Pedarsani, “Adaptive Node Participation for Straggler-resilient Federated Learning”, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022.

M. Beliaev, N. Mehr, R. Pedarsani, “Congestion-aware Bi-modal Delivery Systems Utilizing Drones”, European Control Conference (ECC), 2022.

D. Lazar, R. Pedarsani, “Anonymous Tolling for Traffic Networks with Mixed Autonomy”, European Control Conference (ECC), 2022.

M. Beliaev, E. Biyik, D. Lazar, W. Wang, D. Sadigh, and R. Pedarsani, “Incentivizing Routing Choices for Safe and Efficient Transportation in the Face of the COVID-19 Pandemic”, ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), 2021.

B. Toghi, R. Valiente, D. Sadigh, R. Pedarsani, Y. Fallah, “Cooperative Autonomous Vehicles that Sympathize with Human Drivers”, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021.

B. Puranik, U. Madhow, R. Pedarsani, “Adversarially Robust Classification Based on GLRT”, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021.

S. Prakash, A. Reisizadeh, R. Pedarsani, S. Avestimehr, “Hierarchical Coded Gradient Aggregation for Learning at the Edge”, IEEE International Symposium on Information Theory (ISIT), 2020.

H. Taheri, R. Pedarsani, C. Thrampoulidis, “Optimality of Least-squares for Classification in Gaussian-Mixture Models”, IEEE International Symposium on Information Theory (ISIT), 2020.

C. Yang, R. Pedarsani, S. Avestimehr, “Coded Computing in Unknown Environment via Online Learning”, IEEE International Symposium on Information Theory (ISIT), 2020.

C. Bakiskan, S. Gopalakrishnan, M. Cekic, U. Madhow, R. Pedarsani, “Polarizing Front Ends for Robust CNNs”, International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020.

D. Lazar, E. Biyik, D. Sadigh, and R. Pedarsani, “The Green Choice: Learning and Influencing Human Decisions on Shared Roads", IEEE Conference on Decision and Control (CDC), 2019.

D. Lazar, S. Coogan, and R. Pedarsani, “Optimal Tolling for Heterogeneous Traffic Networks with Mixed Autonomy”, IEEE Conference on Decision and Control (CDC), 2019.

H. Taheri, R. Pedarsani, C. Thrampoulidis, “Sharp Guarantees for Solving Random Equations with One-Bit Information”, Allerton Conference on Communication, Control, and Computing, 2019.

A. Reisizadeh, S. Prakash, R. Pedarsani, S. Avestimehr, “Tree Gradient Coding”, IEEE International Symposium on Information Theory (ISIT), 2019.

C. Yang, R. Pedarsani, S. Avestimehr, “Timely Coded Computing”, IEEE International Symposium on Information Theory (ISIT), 2019.

Q. Wei, J. A. Rodriguez, R. Pedarsani, S. Coogan, “Ride-Sharing Networks with Mixed Autonomy”, IEEE American Control Conference (ACC), 2019.

A. Reisizadeh, A. Mokhtari, H. Hassani, R. Pedarsani, “Quantized Decentralized Consensus Optimization”, IEEE Conference on Decision and Control (CDC), 2018.

D. Lazar, K. Chandrasekher, R. Pedarsani, and D. Sadigh, “Maximizing Road Capacity Using Cars that Influence People”, IEEE Conference on Decision and Control (CDC), 2018.

A. Reisizadeh, P. Abdalla, R. Pedarsani, “Sub-linear Time Stochastic Threshold Group Testing via Sparse-Graph Codes”, Information Theory Workshop (ITW), 2018.

N. Mehr, R. Horowtiz, and R. Pedarsani, “Signal Control for Urban Traffic Networks with Unknown System Parameters”, IEEE International Conference on Intelligent Transportation Systems (ITSC), 2018.

Z. Marzi, S. Gopalakrishnan, U. Madhow, R. Pedarsani, “Sparsity-based Defense against Adversarial Attacks on Linear Classifiers”, IEEE International Symposium on Information Theory (ISIT), 2018.

C. Yang, R. Pedarsani, S. Avestimehr, “Communication-Aware Scheduling of Serial Tasks for Dispersed Computing”, IEEE International Symposium on Information Theory (ISIT), 2018.

S. Prakash, A. Reisizadeh, R. Pedarsani, S. Avestimehr, “Coded Computing for Distributed Graph Analytics”, IEEE International Symposium on Information Theory (ISIT), 2018.

D. Lazar, S. Coogan, and R. Pedarsani, “The Price of Anarchy for Transportation Networks with Mixed Autonomy”, IEEE American Control Conference (ACC), 2018.

D. Lazar, S. Coogan, and R. Pedarsani, “Capacity Modeling and Routing for Traffic Networks with Mixed Autonomy”, IEEE Conference on Decision and Control (CDC), 2017.

N. Mehr, R. Horowtiz, and R. Pedarsani, “Low-Complexity Ramp Metering for Freeway Congestion Control via Network Utility Maximization”, IEEE Conference on Decision and Control (CDC), 2017.

P. Abdalla, A. Reisizadeh, R. Pedarsani, “Multilevel Group Testing via Sparse-graph Codes”, Asilomar Conference on Signals, Systems, and Computers, 2017.

A. Reisizadeh, R. Pedarsani, “Latency Analysis of Coded Computation Schemes over Wireless Networks”, Allerton Conference on Communication, Control, and Computing, 2017.

D. Yin, R. Pedarsani, Y. Chen, and K. Ramchandran, “Learning Mixtures of Sparse Linear Regressions Using Sparse Graph Codes”, Allerton Conference on Communication, Control, and Computing, 2017.

N. Mehr, J. Lioris, R. Horowtiz, and R. Pedarsani, “Joint Perimeter and Signal Control of Urban Traffic via Network Utility Maximization”, IEEE International Conference on Intelligent Transportation Systems (ITSC), 2017.

A. Reisizadeh, S. Prakash, R. Pedarsani, S. Avestimehr, “Coded Computation over Heterogeneous Clusters”, IEEE International Symposium on Information Theory (ISIT), 2017.

K. Lee, R. Pedarsani, D. Papailiopoulos, K. Ramchandran, “Coded Computation for Multicore Setups”, IEEE International Symposium on Information Theory (ISIT), 2017.

K. Chandrasekher, K. Lee, P. Kairouz, R. Pedarsani, and K. Ramchandran, “Asynchronous and Noncoherent Neighbor Discovery for the IoT Using Sparse-Graph Codes”, IEEE International Conference on Communications (ICC), 2017.

D. Yin, R. Pedarsani, X. Li, and K. Ramchandran, “Fast and Robust Support Recovery for Compressive Sensing with Continuous Alphabet”, Allerton Conference on Communications, Control and Computing, 2016.

Z. Amini, R. Pedarsani, A. Skabardonis, and P. Varaiya, “Queue-Length Estimation Using Real-Time Traffic Data”, IEEE International Conference on Intelligent Transportation Systems (ITSC), 2016.

K. Lee, M. Lam, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran, “Speeding Up Distributed Machine Learning Using Codes”, IEEE International Symposium on Information Theory (ISIT), 2016.

K. Lee, R. Pedarsani, and K. Ramchandran, “SAFFRON: A Fast, Efficient, and Robust Framework for Group Testing based on Sparse-Graph Codes”, IEEE International Symposium on Information Theory (ISIT), 2016.

J. Lioris, R. Pedarsani, F. Yildiz, and P. Varaiya, “Doubling Throughput in Urban Roads by Platooning”, IFAC Symposium on Control in Transportation Systems, 2015.

R. Pedarsani, K. Lee, and K. Ramchandran, “Sparse Covariance Estimation Based on Sparse-Graph Codes”, Allerton Conference on Communication, Control and Computing, 2015.

K. Lee, R. Pedarsani, and K. Ramchandran, “On Scheduling Redundant Requests with Cancellation Overheads”, Allerton Conference on Communication, Control and Computing, 2015.

R. Pedarsani, K. Lee, and K. Ramchandran, “Capacity-Approaching PhaseCode for Low-Complexity Compressive Phase Retrieval”, IEEE International Symposium on Information Theory (ISIT), 2015. (arxiv version)

D. Yin, K. Lee, R. Pedarsani, and K. Ramchandran, “Fast and Robust Compressive Phase Retrieval with Sparse-Graph Codes”, IEEE International Symposium on Information Theory (ISIT), 2015.

R. Pedarsani, J. Walrand, and Y. Zhong, “Scheduling Tasks with Precedence Constraints on Multiple Servers”, Allerton Conference on Communication, Control, and Computing, 2014.

R. Pedarsani, K. Lee, and K. Ramchandran, “PhaseCode: Fast and Efficient Compressive Phase Retrieval based on Sparse-Graph Codes”, Allerton Conference on Communication, Control, and Computing, 2014.

R. Pedarsani, J. Walrand, and Y. Zhong, “Robust Scheduling in a Flexible Fork-Join Network”, IEEE Conference on Decision and Control (CDC), 2014.

R. Pedarsani, M. Maddah-Ali, and U. Niesen, “Online Coded Caching”, IEEE International Conference on Communications (ICC), 2014. (Best paper award)

R. Pedarsani, J. Walrand, and Y. Zhong, “Robust Scheduling and Congestion Control for Flexible Queueing Networks”, IEEE International Conference on Computing, Networking and Communications (ICNC), 2014.

R. Pedarsani, S. H. Hassani, I. Tal, and E. Telatar, “On the Construction of Polar Codes”, IEEE International Symposium on Information Theory (ISIT), 2011.

R. Pedarsani, O. Leveque, and S. Yang, “On the DMT Optimality of the Rotate-and-Forward Scheme in a Two-Hop MIMO Relay Channel”, Allerton Conference on Communication, Control, and Computing, 2010.

R. Pedarsani, O. Leveque, and S. Yang, “Flip-and-forward Achieves the Optimal Diversity-Multiplexing Tradeoff for the Two-Hop MIMO Relay Channel, with Two Relay Antennas”, Fifth International Conference on Cognitive Radio Oriented Wireless Network and Communications (CROWNCOM), 2010.