Faculty

Institution

Unit

Venue

Vikram Krishnamurthy

Professor

Cornell University

Affiliations

College of Engineering

School of Electrical and Computer Engineering

Vikram Krishnamurthy is currently serving as a College Of Engineering Professor at Cornell University.

Honors

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Experiences

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Education

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Vikram Krishnamurthy

Cornell University

Professor

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computer science applied mathematics signal processing stochastic process data science systems engineering wireless communications mathematical optimization bayesian analysis telecommunication networks stochastic optimization wireless networks reinforcement learning communications systems markov decision process state estimation statistical signal processing computational optimization hidden markov model computational statistics control optimization game theory information fusion sequential decision making digital signal processing cellular networks stochastic dynamics networked system design estimation theory distributed systems filtering technique social simulation computational intelligence sensor optimization radar signal processing tracking systems social networks global networks automatic control cognitive radio hidden markov models statistical methodology dynamic spectrum management moving object tracking markov chain optimal policy multi-sensor management spectrum management adaptive filter channel access method membrane permeation ion channels distributed coordination collaborative sensor network information propagation exploration v exploitation probabilistic graph theory wireless multimedia system markov chain monte carlo social learning nash equilibrium data incest cognitive radio resource management signal detection markov decision processes em algorithm multimedia systems network optimization friendship paradox channel capacity estimation kalman filter maximum likelihood estimation code optimization monotone structure quickest detection multifunction radars stochastic control systems modeling bio-inspired computation evolutionary intelligence biocybernetics

Notable Scholarly Works

Notable Federal Grants

Collaborators

Efficient Neural Sde Training Using Wiener-Space Cubature. arXiv (Cornell University) (2025)

Snow, LukeKrishnamurthy, Vikram

neural networkneural network (machine learning)model optimizationstochastic optimizationpath-wise gradientsneural computationwiener-space cubaturemachine learning researchcomputational intelligenceapplied mathematicsmachine learningstochastic partial differential equationscomputer science

Interacting Large Language Model Agents. Bayesian Social Learning Based Interpretable Models.. IEEE Access (2025)

Adit JainVikram Krishnamurthy

bayesian social learningartificial societycommunicationinterpretable modelscomputational linguisticsartificial intelligencelanguage modelscomputational social sciencenatural language processingbayesian analysisllm-based agentlanguagesocial simulationlinguisticslarge language models

Mle of Banded, Spiked, High-Dimensional Clutter Covariance–a Convex Relaxation Approach. (2025)

Shashwat JainVikram KrishnamurthyMuralidhar RangaswamySandeep GogineniSean M. O'RourkeBosung Kang

physicsstatistical signal processinghigh-dimensional statisticsestimation theorysignal processingcomputational statisticsconvex analysisapplied mathematics

Partially Observed Markov Decision Processes. (2025)

Vikram Krishnamurthy

stochastic dynamicsmachine learning researchadaptive radarsmarkov decision processessequential decision makinghidden markov modelmathematical optimizationmachine learningstochastic partial differential equationsreinforcement learningstochastic processapplied mathematicsmarkov decision processstochastic optimizationapplied probabilityapproximate reasoningbayesian analysiscomputer scienceinverse reinforcement learning

Adaptive Mechanism Design Using Multi-Agent Revealed Preferences. arXiv (Cornell University) (2024)

Luke SnowVikram Krishnamurthy

autonomous agent systemssystems engineeringmechanism designartificial societyagent decision-makingadaptive mechanism designmultiagent systemsmulti-agent mechanism design

Annotation Efficiency: Identifying Hard Samples via Blocked Sparse Linear Bandits. arXiv (Cornell University) (2024)

Jain, AditPal, SoumyabrataChoudhary, SunavNarayanam, RamasuriKrishnamurthy, Vikram

online algorithmssequential decision makingcomputational optimizationlasso estimatormachine learningfixed annotation budgetmathematical optimizationannotation efficiencyartificial intelligenceexploration v exploitationreinforcement learninginferenceknowledge discoverydata sciencemachine learning researchstructured predictionsupervised learningcomputer science

Bimodal Bandits: Max-Mean Regret Minimization. 2014 48th Asilomar Conference on Signals, Systems and Computers (2024)

Adit JainSujay BhattVikram KrishnamurthyAlec Koppel

stochastic optimizationapplied probabilitymathematical optimizationexploration v exploitationreinforcement learningapplied mathematicsbimodal banditscomputer science

Controlling Stochastic Gradient Descent Using Stochastic Approximation for Robust Distributed Optimization. Numerical Algebra Control and Optimization (2024)

Adit JainVikram Krishnamurthy

systems engineeringcomputational optimizationmachine learningstochastic optimizationmathematical optimizationcontrol optimizationstochastic gradient descentstochastic processstochastic approximationapplied mathematicsrobust optimizationcomputer science

Detecting Structural Shifts in Multivariate Hawkes Processes With FréChet Statistic. (2024)

Rui LuoVikram Krishnamurthy

stochastic calculusapplied probabilityhigh-dimensional statisticstime seriesstatisticsstochastic processstatistical methodologyapplied mathematicscomputational statisticsstructural shiftsstochastic phenomena

Distributed Learning in Congested Environments With Partial Information. Automatica (2024)

Amir LeshemVikram KrishnamurthyTomer Boyarski

distributed systemsmachine learningcongested environmentsdistributed learningcomputer science

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Vikram Krishnamurthy

Professor

Cornell University

Affiliations

College of Engineering

School of Electrical and Computer Engineering

Vikram Krishnamurthy is currently serving as a College Of Engineering Professor at Cornell University.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Vikram Krishnamurthy

Cornell University

Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Efficient Neural Sde Training Using Wiener-Space Cubature. arXiv (Cornell University) (2025)

Snow, LukeKrishnamurthy, Vikram

Interacting Large Language Model Agents. Bayesian Social Learning Based Interpretable Models.. IEEE Access (2025)

Adit JainVikram Krishnamurthy

Mle of Banded, Spiked, High-Dimensional Clutter Covariance–a Convex Relaxation Approach. (2025)

Shashwat JainVikram KrishnamurthyMuralidhar RangaswamySandeep GogineniSean M. O'RourkeBosung Kang

physicsstatistical signal processinghigh-dimensional statisticsestimation theorysignal processingcomputational statisticsconvex analysisapplied mathematics

Partially Observed Markov Decision Processes. (2025)

Vikram Krishnamurthy

Adaptive Mechanism Design Using Multi-Agent Revealed Preferences. arXiv (Cornell University) (2024)

Luke SnowVikram Krishnamurthy

autonomous agent systemssystems engineeringmechanism designartificial societyagent decision-makingadaptive mechanism designmultiagent systemsmulti-agent mechanism design

Annotation Efficiency: Identifying Hard Samples via Blocked Sparse Linear Bandits. arXiv (Cornell University) (2024)

Jain, AditPal, SoumyabrataChoudhary, SunavNarayanam, RamasuriKrishnamurthy, Vikram

Bimodal Bandits: Max-Mean Regret Minimization. 2014 48th Asilomar Conference on Signals, Systems and Computers (2024)

Adit JainSujay BhattVikram KrishnamurthyAlec Koppel

stochastic optimizationapplied probabilitymathematical optimizationexploration v exploitationreinforcement learningapplied mathematicsbimodal banditscomputer science

Controlling Stochastic Gradient Descent Using Stochastic Approximation for Robust Distributed Optimization. Numerical Algebra Control and Optimization (2024)

Adit JainVikram Krishnamurthy

Detecting Structural Shifts in Multivariate Hawkes Processes With FréChet Statistic. (2024)

Rui LuoVikram Krishnamurthy

Distributed Learning in Congested Environments With Partial Information. Automatica (2024)

Amir LeshemVikram KrishnamurthyTomer Boyarski

distributed systemsmachine learningcongested environmentsdistributed learningcomputer science

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