Faculty

Institution

Unit

Venue

Sanjay Shakkottai

Professor

University of Texas at Austin

Affiliations

Cockrell School of Engineering

Chandra Family Department of Electrical and Computer Engineering

Sanjay Shakkottai is currently serving as a Chandra Electrical And Computer Engineering Professor at University of Texas At Austin.

Honors

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Experiences

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Education

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Sanjay Shakkottai

University of Texas at Austin

Professor

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computer science machine learning applied mathematics systems engineering electrical engineering communications systems network science wireless communications network analysis telecommunication networks networked system design wireless networks deep learning network optimization stochastic process distributed systems mathematical optimization information theory scheduling (computing) queueing theory automatic control congestion control wireless sensor networks network traffic control scheduling problems information technology network management network routing congestion management network routing algorithm online algorithms congestion control algorithms computational intelligence channel access method high-speed networking scheduling analysis wireless network management discrete algorithms recommender systems machine learning research control optimization dynamic resource allocation supervised learning quality-of-service fluid queue random graphs wireless scheduling congestion controllers cluster computing real-time algorithms wireless routing routing protocols sensor connectivity device-to-device wireless lan medium access control delay-tolerant networking spectrum management radio communication cross-layer optimization exponential rule multihop wireless networks back-pressure routing pathwise optimality access points effective capacity throughput optimality multi-channel wireless networks rate control unknown service rates feedback delay tcp performance stochastic available capacity mathematical programming service management internet economics intelligent network resource allocation smart wireless network

Notable Scholarly Works

Notable Federal Grants

Collaborators

Bandits With Stochastic Experts: Constant Regret, Empirical Experts and Episodes. ACM Transactions on Modeling and Performance Evaluation of Computing Systems (2024)

Nihal SharmaRajat SenSoumya BasuKarthikeyan ShanmugamSanjay Shakkottai

empirical expertsstochastic expertsmodeling and simulationperformance modelingcomputer science

Beyond First-Order Tweedie: Solving Inverse Problems Using Latent Diffusion. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024)

Litu RoutYujia ChenAbhishek KumarConstantine CaramanisSanjay ShakkottaiWen-Sheng Chu

latent diffusioninverse problemsfirst-order tweedieapplied mathematics

CIPAT: Latent-Resilient Toolkit for Performance Impact Prediction Due to Configuration Tuning. Proceedings of the 28th Annual International Conference on Mobile Computing And Networking (2024)

Kartik PatelChanghan GeAjay MahimkarSanjay ShakkottaiYusef Shaqalle

latent-resilient toolkitmobile computingperformance predictionperformance impact predictioncomputer science

In-Context Learning With Transformers: Softmax Attention Adapts to Function Lipschitzness. arXiv (Cornell University) (2024)

Collins, LiamParulekar, AdvaitMokhtari, AryanSanghavi, SujayShakkottai, Sanjay

machine intelligenceadaptive learningattentiondeep learningnatural language processingapplied mathematicscognitive sciencein-context learningmachine learning

Meta-Learning Adaptable Foundation Models. arXiv (Cornell University) (2024)

Block, Jacob L.Srinivasan, SundararajanCollins, LiamMokhtari, AryanShakkottai, Sanjay

meta-learning (computer science)machine learningfoundation modelsdata science

Predicting the Performance of Cellular Networks: A Latent-Resilient Approach. Proceedings of the 28th Annual International Conference on Mobile Computing And Networking (2024)

Kartik PatelChanghan GeAjay MahimkarSanjay ShakkottaiYusef Shaqalle

cellular networkssystems biologymobile computingnetwork performance

Rb-Modulation: Training-Free Personalization of Diffusion Models Using Stochastic Optimal Control. arXiv (Cornell University) (2024)

Rout, LituChen, YujiaRuiz, NatanielKumar, AbhishekCaramanis, ConstantineShakkottai, SanjayChu, Wen-Sheng

diffusion modelsreinforcement learningtraining-free personalizationstochastic optimal controlapplied mathematicsmachine learning

Semantic Image Inversion and Editing Using Rectified Stochastic Differential Equations. arXiv (Cornell University) (2024)

Rout, LituChen, YujiaRuiz, NatanielCaramanis, ConstantineShakkottai, SanjayChu, Wen-Sheng

computational imagingimage restorationfeature extractioncomputer visionsynthetic image generationstochastic processdigital image processingimage analysisapplied mathematicsimage representationstochastic differential equationscomputer scienceimage manipulationdifferential equationssemantic image inversion

$\Mathsf{Hyhoover}$: Verification and Parameter Synthesis in Stochastic Systems With Hybrid State Space Using Optimistic Optimization. IEEE Open Journal of Control Systems (2023)

Negin MusaviDawei SunSayan MitraGeir E. DullerudSanjay Shakkottai

stochastic optimizationmathematical optimizationhierarchical optimistic optimizationcontrol optimizationreinforcement learningexploration v exploitationparameter synthesisstochastic processnew algorithmapplied mathematicscomputer science

Adaptive Kl-Ucb Based Bandit Algorithms for Markovian and I.I.D. Settings. IEEE Transactions on Automatic Control (2023)

Arghyadip RoySanjay ShakkottaiR. Srikant

online algorithmscomputational optimizationmarkov decision processstochastic dynamicsstochastic optimizationapplied probabilitymathematical optimizationexploration v exploitationreinforcement learningregret guaranteesstochastic processmachine learning researchadaptive kl-ucbapplied mathematicsarm rewardcomputer science

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Sanjay Shakkottai

Professor

University of Texas at Austin

Affiliations

Cockrell School of Engineering

Chandra Family Department of Electrical and Computer Engineering

Sanjay Shakkottai is currently serving as a Chandra Electrical And Computer Engineering Professor at University of Texas At Austin.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Sanjay Shakkottai

University of Texas at Austin

Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Bandits With Stochastic Experts: Constant Regret, Empirical Experts and Episodes. ACM Transactions on Modeling and Performance Evaluation of Computing Systems (2024)

Nihal SharmaRajat SenSoumya BasuKarthikeyan ShanmugamSanjay Shakkottai

empirical expertsstochastic expertsmodeling and simulationperformance modelingcomputer science

Beyond First-Order Tweedie: Solving Inverse Problems Using Latent Diffusion. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024)

Litu RoutYujia ChenAbhishek KumarConstantine CaramanisSanjay ShakkottaiWen-Sheng Chu

latent diffusioninverse problemsfirst-order tweedieapplied mathematics

CIPAT: Latent-Resilient Toolkit for Performance Impact Prediction Due to Configuration Tuning. Proceedings of the 28th Annual International Conference on Mobile Computing And Networking (2024)

Kartik PatelChanghan GeAjay MahimkarSanjay ShakkottaiYusef Shaqalle

latent-resilient toolkitmobile computingperformance predictionperformance impact predictioncomputer science

In-Context Learning With Transformers: Softmax Attention Adapts to Function Lipschitzness. arXiv (Cornell University) (2024)

Collins, LiamParulekar, AdvaitMokhtari, AryanSanghavi, SujayShakkottai, Sanjay

machine intelligenceadaptive learningattentiondeep learningnatural language processingapplied mathematicscognitive sciencein-context learningmachine learning

Meta-Learning Adaptable Foundation Models. arXiv (Cornell University) (2024)

Block, Jacob L.Srinivasan, SundararajanCollins, LiamMokhtari, AryanShakkottai, Sanjay

meta-learning (computer science)machine learningfoundation modelsdata science

Predicting the Performance of Cellular Networks: A Latent-Resilient Approach. Proceedings of the 28th Annual International Conference on Mobile Computing And Networking (2024)

Kartik PatelChanghan GeAjay MahimkarSanjay ShakkottaiYusef Shaqalle

cellular networkssystems biologymobile computingnetwork performance

Rb-Modulation: Training-Free Personalization of Diffusion Models Using Stochastic Optimal Control. arXiv (Cornell University) (2024)

Rout, LituChen, YujiaRuiz, NatanielKumar, AbhishekCaramanis, ConstantineShakkottai, SanjayChu, Wen-Sheng

diffusion modelsreinforcement learningtraining-free personalizationstochastic optimal controlapplied mathematicsmachine learning

Semantic Image Inversion and Editing Using Rectified Stochastic Differential Equations. arXiv (Cornell University) (2024)

Rout, LituChen, YujiaRuiz, NatanielCaramanis, ConstantineShakkottai, SanjayChu, Wen-Sheng

$\Mathsf{Hyhoover}$: Verification and Parameter Synthesis in Stochastic Systems With Hybrid State Space Using Optimistic Optimization. IEEE Open Journal of Control Systems (2023)

Negin MusaviDawei SunSayan MitraGeir E. DullerudSanjay Shakkottai

Adaptive Kl-Ucb Based Bandit Algorithms for Markovian and I.I.D. Settings. IEEE Transactions on Automatic Control (2023)

Arghyadip RoySanjay ShakkottaiR. Srikant

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University of California, Berkeley

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University of Illinois Urbana-Champaign

dynamic resource allocation

operations research

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network algorithm

Anthony Ephremides

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mathematical biology

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infrastructure security

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