Publications

Online Learning for Multi-Layer Hierarchical Inference under Partial and Policy-Dependent Feedback

CoreQ: Learning-Free Mismatch Correction and Successive Rounding for Quantization

Foundation-Preserving Adaptation via Generalized Rayleigh-Quotient Optimization

Long-Lived AI Agents Age Too: They Quietly Decay After Deployment

Class-Incremental Learning with Zero-Shot Unlearning via Activation Disentanglement

When Is Rank-1 Steering Cheap? Geometry, Granularity, and Budgeted Search

Diffusion-Based Channel Inpainting for Robust SRS-Based CSI Acquisition

FedProTIP: Task-Agnostic Federated Continual Learning via Replay-Free Gradient Projection

FedRot-LoRA: Mitigating Rotational Misalignment in Federated LoRA

Training-Free Layout-to-Image Generation with Marginal Attention Constraints

PRISM-AMC: Replay-Free Continual Learning for Automatic Modulation Classification

Adaptive Evolutionary Clustering for Federated Learning under Nonstationary Client Distributions

Optimal Resource Allocation for ML Model Training and Deployment under Concept Drift

Joint Model Onloading and Offloading for Hierarchical Multi-Task Inference

Quantized Gradient Projection for Memory-Efficient Continual Learning

Transformers as Implicit State Estimators: In-Context Learning in Dynamical Systems

Managing task offloading in viewport prediction via reinforcement learning

Federated self-supervised learning for automatic modulation classification in heterogeneous settings

Super capacity SRS design for 5G and beyond using channel in-painting

NextVir: Enabling classification of tumor-causing viruses with genomic foundation models

XVir: A transformer-based architecture for identifying viral reads from cancer samples

Accelerated distributed stochastic non-convex optimization over time-varying directed networks

Viewport prediction via adaptive edge offloading

Federated Learning at Scale: Addressing Client Intermittency and Resource Constraints

XVir: A transformer-based architecture for identifying viral reads from cancer samples

Accelerated distributed stochastic non-convex optimization over time-varying directed networks

Heterogeneity-guided client sampling: Towards fast and efficient non-IID federated learning

Recovering labels from local updates in federated learning

Mixed-precision quantization for federated learning on resource-constrained heterogeneous devices

Optimization of offloading policies for accuracy-delay tradeoffs in hierarchical inference

Fed-QSSL: A framework for personalized federated learning under bitwidth and data heterogeneity

Reducing communication in federated learning via efficient client sampling

Federated learning in non-IID settings aided by differentially private synthetic data

The best of both worlds: Accurate global and personalized models through federated learning with data-free hyper-knowledge distillation

XHap: Haplotype assembly using long-distance read correlations learned by transformers

Automotive RADAR sub-sampling via object detection networks: Leveraging prior signal information

Graph-based reconstruction and analysis of disease transmission networks using viral genomic data

Federated learning under intermittent client availability and time-varying communication constraints

Graph-based reconstruction and analysis of disease transmission networks using viral genomic data

RF-based Network Inference: Learning from Channel Usage and Activity Dynamics Data

End-to-end system for object detection from sub-sampled radar data

Deep learning for assembly of haplotypes and viral quasispecies from short and long sequencing reads

Federated dynamic sparse training: Computing less, communicating less, yet learning better

On the benefits of multiple gossip steps in communication-constrained decentralized federated learning

Federated recommendations using differentially private prototypes

On the benefits of progressively increasing sampling sizes in stochastic greedy weak submodular maximization

Towards accelerated greedy sampling and reconstruction of bandlimited graph signals

Real-Time Radio Technology and Modulation Classification via an LSTM Auto-Encoder

Communication-efficient variance-reduced decentralized stochastic optimization over time-varying directed graphs

RF-based network inference: Theoretical foundations

No-regret learning with high-probability in adversarial Markov decision processes

Optimizing resource constrained distributed collaborative sensing

Decentralized optimization on time-varying directed graphs under communication constraints

On the performance-complexity tradeoff in stochastic greedy weak submodular optimization

Real-time radio modulation classification with an LSTM auto-encoder

Online learning with implicit exploration in episodic Markov decision processes

Opportunistic federated learning: An exploration of egocentric collaboration for pervasive computing applications

Evolutionary clustering via message passing

Randomized greedy sensor selection: Leveraging weak submodularity

Greedy sensor selection: Leveraging submodularity

A convolutional auto-encoder for haplotype assembly and viral quasispecies reconstruction

Identifying low-dimensional structures in Markov Chains: A nonnegative matrix factorization approach

A study of the learnability of relational properties

A graph auto-encoder for haplotype assembly and viral quasispecies reconstruction

ComHapDet: A spatial community detection algorithm for haplotype assembly

Reconstructing intra-tumor heterogeneity via convex optimization and branch-and-bound search

Weighted subset selection for fast SVM training

On submodularity of quadratic observation selection in constrained networked sensing systems

Online topology inference from streaming stationary graph signals

Online selective training for faster neural network learning

Submodular observation selection and information gathering for quadratic models

Deep learning propagation models over irregular terrain

Evolutionary subspace clustering: Discovering structure in self-expressive time-series data

A MAP framework for support recovery of sparse signals using orthogonal least squares

Matrix completion and performance guarantees for single individual haplotyping

Binary matrix completion with performance guarantees for single individual haplotyping

Near-optimal distributed estimation for a network of sensing units operating under communication constraints

A novel scheme for support identification and iterative sampling of bandlimited graph signals

A randomized greedy algorithm for near-optimal sensor scheduling in large-scale sensor networks

Sampling and reconstruction of graph signal via weak submodularity and semidefinite relaxation

Evolutionary self-expressive models for subspace clustering

Accelerated orthogonal least-squares for large-scale sparse reconstruction

Viral quasispecies reconstruction via tensor factorization with successive removal

Multiplexed identification, quantification and genotyping of infectious agents using a semiconductor biochip

Cyclic block coordinate minimization algorithms for DOA estimation in co-prime arrays

Sparse tensor decomposition for haplotype assembly of diploids and polyploids

aBayesQR: A Bayesian method for reconstruction of viral populations characterized by low diversity

Viral quasispecies reconstruction via tensor factorization

Sparse tensor decomposition for haplotype assembly of diploids and polyploids

aBayesQR: A Bayesian method for reconstruction of viral populations characterized by low diversity

Data subset selection for efficient SVM training

Sampling-based binary-level cross-platform performance estimation

Recovery of sparse signals via Branch-and-Bound least-squares

Evolutionary affinity propagation

QSdpR: Viral quasispecies reconstruction via correlation clustering

Information-theoretic analysis of haplotype assembly

Optimal haplotype assembly via a branch-and-bound algorithm

Sparse linear regression via generalized orthogonal least-squares

Nonnegative gridless compressive sensing for co-prime arrays

Beam tracking for mobile millimeter wave communication systems

Structurally-constrained gradient descent for matrix factorization in haplotype assembly problems

End-to-end optimization of high-throughput DNA sequencing

Structured low-rank matrix factorization for haplotype assembly

Decoding genetic variations: Communications-inspired haplotype assembly

Non-uniformity correction of IR images using natural scene statistics

Distributed self localization of sensors with poisson deployment using extended Kalman filter

Designing optimal mortality risk prediction scores that preserve clinical knowledge

Joint haplotype assembly and genotype calling via sequential Monte Carlo algorithm

Semi-supervised affinity propagation with soft instance-level constraints

SDhaP: Haplotype assembly for diploids and polyploids via semi-definite programming

Optimal haplotype assembly with statistical pruning

Single individual haplotyping with low rank semidefinite programming

Haplotype assembly: An information-theoretic view

Iterative learning of single individual haplotypes from high-throughput DNA sequencing data

Iterative learning for reference-guided DNA sequence assembly from short reads: Algorithms and limits of performance

Sparsity-aware sphere decoding: Algorithms and complexity analysis

Deterministic sequential Monte Carlo for haplotype inference

A message passing algorithm for haplotype assembly

Message passing algorithm for inferring consensus sequence from next-generation sequencing data

Exploiting time series properties for mortality prediction in pediatric brain injury

Expected complexity of sphere decoding for sparse integer least-square problems

Bayesian active learning for drug combinations

Base calling for high-throughput short-read sequencing: Dynamic programming solutions

Message-passing algorithms for coordinated spectrum sensing in cognitive radio networks

A message passing algorithm for reference-guided sequence assembly from high-throughput sequencing data

An imputation-enhanced algorithm for ICU mortality prediction

Base calling error rates in next-generation DNA sequencing

Adaptive experimental design for drug combinations

Distributed algorithms for spectrum access in cognitive radio relay networks

Joint parameter estimation and base-calling for pyrosequencing systems

Greedy sensor selection under channel uncertainty

ParticleCall: A particle filter for base calling in next-generation sequencing systems

OnlineCall: Fast online parameter estimation and base calling for Illumina’s next-generation sequencing

Estimating parameters of sampled diffusion processes in affinity biosensors

Graphical models and inference on graphs in genomics: Challenges of high-throughput data analysis

A sequential Monte Carlo base-calling method for next-generation DNA sequencing

An MCMC Algorithm for base calling in sequencing-by-synthesis

A message-passing algorithm for spectrum access in cognitive radio relay networks

Base-calling for Illumina’s next-generation DNA sequencing systems via Viterbi algorithm

A dual Kalman filter for parameter-state estimation in real-time DNA microarrays

Message-passing for base-calling in sequencing-by-synthesis systems

Distributed routing in networks using affinity propagation

Sequential Monte Carlo method for parameter estimation in diffusion models of affinity-based biosensors

Estimating time-varying sparse signals under communication constraints

Inference of gene-regulatory networks using message-passing algorithms

Model-based sequential base calling for Illumina sequencing

On parameter estimation for diffusion processes in real-time biosensors

Optimal estimation in DNA Microarrays via global optimization

Maximum likelihood DNA sequence detection via sphere decoding

Inferring parameters of gene regulatory networks via particle filtering

Further results on message-passing algorithms for motif finding

Rao-Blackwellized unscented Kalman filter for nonlinear systems with bandwidth constrains

Compressed sensing for bandwidth constrained systems

An MCMC algorithm for target estimation in real-time DNA microarrays

Inferring parameters of gene regulatory networks via particle filtering

Limits of performance of quantitative polymerase chain reaction systems

Limits of performance of real-time DNA microarrays

An MCMC algorithm for parameter estimation in stochastically modeled real-time biosensor arrays

Message-passing for motif finding

Stochastic modeling of reaction kinetics in biosensors using the Fokker-Planck equation

A particle filtering algorithm for parameter estimation in real-time biosensor arrays

Target estimation in real-time polymerase chain reaction using sequential Monte Carlo

Performance of sphere decoding of block codes

Real-time DNA microarray analysis

On scaling laws of biosensors: A stochastic approach

On the performance of sphere decoding of block codes

Estimation in real-time affinity-based biosensors

Sparse measurements, compressed sampling, and DNA microarrays

On estimation in real-time microarrays

Modeling and estimation for real-time microarrays

Recovering sparse signals using sparse measurement matrices in compressed DNA microarrays

Speeding up the sphere decoder with H-infinity and SDP inspired lower bounds

Signal processing aspects of real-time DNA microarrays

Signal processing for real-time DNA microarrays

On recovery of sparse signals in compressed DNA microarrays

Modeling the kinetics of hybridization in microarrays

PEP analysis of SDP-based non-coherent signal detection

ML estimation of DNA initial copy number in polymerase chain reaction processes

PEP analysis of the SDP based joint channel estimation and signal detection

On noise processes and limits of performance in biosensors

On limits of performance of DNA microarrays

On joint maximum-likelihood estimation of PCR efficiency and initial amount of target

Further results on speeding up the sphere decoder

Asymptotic analysis of the Gaussian broadcast channel with perturbation preprocessing

On joint detection and decoding of linear block codes on Gaussian vector channels

Rate maximization in multi-antenna broadcast channels with linear preprocessing

Efficient joint maximum-likelihood channel estimation and signal detection

Sphere-constrained ML detection for frequency-selective channels

A statistical model for microarrays, optimal estimation algorithms, and limits of performance

Rate maximization in multi-antenna broadcast channels with linear preprocessing

Sphere-constrained ML detection for frequency-selective channels

Bounds on the performance of sphere decoding of linear block codes

An efficient H-infinity estimation approach to speed up the sphere decoder

An H-infinity based lower bound to speed up sphere decoder

Optimal estimation of gene expression levels in microarrays

A probabilistic model for inherent noise and systematic errors of microarrays

A branch and bound approach to speed up the sphere decoder

On sphere-decoding algorithm II. Generalizations, second-order statistics, and applications to communications

On sphere-decoding algorithm I. Expected complexity

On robust signal reconstruction in noisy filter banks

Statistical approach to ML decoding of linear block codes on symmetric channels

Nucleic acid detection using bioluminescence regenerative cycle and statistical signal processing

Iterative decoding for MIMO channels via modified sphere decoding

On the capacity of frequency-selective channels in training-based transmission schemes

Sphere-constrained ML detection for channels with memory

On joint ML detection and decoding

Joint ML channel estimation and signal detection for SIMO channels

Low-complexity iterative detection and decoding of multi-antenna systems employing channel and space-time codes

On the expected complexity of sphere decoding for frequency-selective channels

Modified Fincke-Pohst algorithm for low-complexity iterative decoding over multiple antenna channels

Towards closing the capacity gap on multiple antenna channels

On the expected complexity of integer least-squares problems

Maximum-likelihood sequence detection of multiple antenna systems over dispersive channels via sphere decoding

Low-complexity iterative decoding over multiple antenna channels via a modified sphere decoder

On the expected complexity of sphere decoding

Optimal training for frequency-selective fading channels

On robust multiuser detection

CDMA multiuser detection based on state-space estimation techniques

Exponential-quadratic optimal signal reconstruction in noisy filter banks

Energy efficient design of portable wireless systems

Mixed H2/H-infinity optimal signal reconstruction in noisy filter banks

On H-infinity optimal signal reconstruction in noisy filter banks

Distributed detection in dependent nonGaussian noise

Distributed detection of known signals in Gaussian mixture noise which is dependent from sensor to sensor

Design and parameter adaptation of a fuzzy servo controller

Diffusion-Based Channel Inpainting for Robust SRS-Based CSI Acquisition

FedProTIP: Task-Agnostic Federated Continual Learning via Replay-Free Gradient Projection

Transformers as Implicit State Estimators: In-Context Learning in Dynamical Systems

Managing task offloading in viewport prediction via reinforcement learning

NextVir: Enabling classification of tumor-causing viruses with genomic foundation models

XVir: A transformer-based architecture for identifying viral reads from cancer samples

Accelerated distributed stochastic non-convex optimization over time-varying directed networks

Viewport prediction via adaptive edge offloading

Federated Learning at Scale: Addressing Client Intermittency and Resource Constraints

Reducing communication in federated learning via efficient client sampling

XHap: Haplotype assembly using long-distance read correlations learned by transformers

Automotive RADAR sub-sampling via object detection networks: Leveraging prior signal information

Graph-based reconstruction and analysis of disease transmission networks using viral genomic data

Federated learning under intermittent client availability and time-varying communication constraints

Communication-efficient variance-reduced decentralized stochastic optimization over time-varying directed graphs

On the benefits of multiple gossip steps in communication-constrained decentralized federated learning

Federated recommendations using differentially private prototypes

On the benefits of progressively increasing sampling sizes in stochastic greedy weak submodular maximization

Towards accelerated greedy sampling and reconstruction of bandlimited graph signals

Real-Time Radio Technology and Modulation Classification via an LSTM Auto-Encoder

Evolutionary clustering via message passing

Randomized greedy sensor selection: Leveraging weak submodularity

ComHapDet: A spatial community detection algorithm for haplotype assembly

Matrix completion and performance guarantees for single individual haplotyping

Evolutionary self-expressive models for subspace clustering

Accelerated orthogonal least-squares for large-scale sparse reconstruction

Viral quasispecies reconstruction via tensor factorization with successive removal

Multiplexed identification, quantification and genotyping of infectious agents using a semiconductor biochip

Cyclic block coordinate minimization algorithms for DOA estimation in co-prime arrays

Sparse tensor decomposition for haplotype assembly of diploids and polyploids

aBayesQR: A Bayesian method for reconstruction of viral populations characterized by low diversity

QSdpR: Viral quasispecies reconstruction via correlation clustering

Information-theoretic analysis of haplotype assembly

Optimal haplotype assembly via a branch-and-bound algorithm

End-to-end optimization of high-throughput DNA sequencing

Structured low-rank matrix factorization for haplotype assembly

Decoding genetic variations: Communications-inspired haplotype assembly

Designing optimal mortality risk prediction scores that preserve clinical knowledge

Joint haplotype assembly and genotype calling via sequential Monte Carlo algorithm

Semi-supervised affinity propagation with soft instance-level constraints

SDhaP: Haplotype assembly for diploids and polyploids via semi-definite programming

Iterative learning for reference-guided DNA sequence assembly from short reads: Algorithms and limits of performance

Sparsity-aware sphere decoding: Algorithms and complexity analysis

Bayesian active learning for drug combinations

Base calling for high-throughput short-read sequencing: Dynamic programming solutions

Message-passing algorithms for coordinated spectrum sensing in cognitive radio networks

Distributed algorithms for spectrum access in cognitive radio relay networks

Joint parameter estimation and base-calling for pyrosequencing systems

Greedy sensor selection under channel uncertainty

ParticleCall: A particle filter for base calling in next-generation sequencing systems

OnlineCall: Fast online parameter estimation and base calling for Illumina’s next-generation sequencing

Estimating parameters of sampled diffusion processes in affinity biosensors

Graphical models and inference on graphs in genomics: Challenges of high-throughput data analysis

Estimating time-varying sparse signals under communication constraints

An MCMC algorithm for target estimation in real-time DNA microarrays

Inferring parameters of gene regulatory networks via particle filtering

Limits of performance of quantitative polymerase chain reaction systems

Performance of sphere decoding of block codes

Real-time DNA microarray analysis

On scaling laws of biosensors: A stochastic approach

Modeling and estimation for real-time microarrays

Recovering sparse signals using sparse measurement matrices in compressed DNA microarrays

Speeding up the sphere decoder with H-infinity and SDP inspired lower bounds

On noise processes and limits of performance in biosensors

On joint detection and decoding of linear block codes on Gaussian vector channels

Rate maximization in multi-antenna broadcast channels with linear preprocessing

Efficient joint maximum-likelihood channel estimation and signal detection

Sphere-constrained ML detection for frequency-selective channels

A statistical model for microarrays, optimal estimation algorithms, and limits of performance

On sphere-decoding algorithm II. Generalizations, second-order statistics, and applications to communications

On sphere-decoding algorithm I. Expected complexity

On robust signal reconstruction in noisy filter banks

Iterative decoding for MIMO channels via modified sphere decoding

On the capacity of frequency-selective channels in training-based transmission schemes

Maximum-likelihood sequence detection of multiple antenna systems over dispersive channels via sphere decoding

Online Learning for Multi-Layer Hierarchical Inference under Partial and Policy-Dependent Feedback

CoreQ: Learning-Free Mismatch Correction and Successive Rounding for Quantization

Foundation-Preserving Adaptation via Generalized Rayleigh-Quotient Optimization

Long-Lived AI Agents Age Too: They Quietly Decay After Deployment

Class-Incremental Learning with Zero-Shot Unlearning via Activation Disentanglement

When Is Rank-1 Steering Cheap? Geometry, Granularity, and Budgeted Search

FedRot-LoRA: Mitigating Rotational Misalignment in Federated LoRA

Training-Free Layout-to-Image Generation with Marginal Attention Constraints

PRISM-AMC: Replay-Free Continual Learning for Automatic Modulation Classification

Adaptive Evolutionary Clustering for Federated Learning under Nonstationary Client Distributions

Optimal Resource Allocation for ML Model Training and Deployment under Concept Drift

Joint Model Onloading and Offloading for Hierarchical Multi-Task Inference

Quantized Gradient Projection for Memory-Efficient Continual Learning

Federated self-supervised learning for automatic modulation classification in heterogeneous settings

Super capacity SRS design for 5G and beyond using channel in-painting

Heterogeneity-guided client sampling: Towards fast and efficient non-IID federated learning

Recovering labels from local updates in federated learning

Mixed-precision quantization for federated learning on resource-constrained heterogeneous devices

Optimization of offloading policies for accuracy-delay tradeoffs in hierarchical inference

Fed-QSSL: A framework for personalized federated learning under bitwidth and data heterogeneity

XVir: A transformer-based architecture for identifying viral reads from cancer samples

Federated learning in non-IID settings aided by differentially private synthetic data

The best of both worlds: Accurate global and personalized models through federated learning with data-free hyper-knowledge distillation

Accelerated distributed stochastic non-convex optimization over time-varying directed networks

RF-based Network Inference: Learning from Channel Usage and Activity Dynamics Data

End-to-end system for object detection from sub-sampled radar data

Deep learning for assembly of haplotypes and viral quasispecies from short and long sequencing reads

Graph-based reconstruction and analysis of disease transmission networks using viral genomic data

Federated dynamic sparse training: Computing less, communicating less, yet learning better

RF-based network inference: Theoretical foundations

No-regret learning with high-probability in adversarial Markov decision processes

Optimizing resource constrained distributed collaborative sensing

Decentralized optimization on time-varying directed graphs under communication constraints

On the performance-complexity tradeoff in stochastic greedy weak submodular optimization

Real-time radio modulation classification with an LSTM auto-encoder

Online learning with implicit exploration in episodic Markov decision processes

Opportunistic federated learning: An exploration of egocentric collaboration for pervasive computing applications

A convolutional auto-encoder for haplotype assembly and viral quasispecies reconstruction

Identifying low-dimensional structures in Markov Chains: A nonnegative matrix factorization approach

A study of the learnability of relational properties

A graph auto-encoder for haplotype assembly and viral quasispecies reconstruction

Reconstructing intra-tumor heterogeneity via convex optimization and branch-and-bound search

Weighted subset selection for fast SVM training

On submodularity of quadratic observation selection in constrained networked sensing systems

Online topology inference from streaming stationary graph signals

Online selective training for faster neural network learning

Submodular observation selection and information gathering for quadratic models

Deep learning propagation models over irregular terrain

Evolutionary subspace clustering: Discovering structure in self-expressive time-series data

A MAP framework for support recovery of sparse signals using orthogonal least squares

Near-optimal distributed estimation for a network of sensing units operating under communication constraints

A novel scheme for support identification and iterative sampling of bandlimited graph signals

A randomized greedy algorithm for near-optimal sensor scheduling in large-scale sensor networks

Sampling and reconstruction of graph signal via weak submodularity and semidefinite relaxation

Viral quasispecies reconstruction via tensor factorization

Data subset selection for efficient SVM training

Sparse tensor decomposition for haplotype assembly of diploids and polyploids

aBayesQR: A Bayesian method for reconstruction of viral populations characterized by low diversity

Sampling-based binary-level cross-platform performance estimation

Recovery of sparse signals via Branch-and-Bound least-squares

Evolutionary affinity propagation

Binary matrix completion with performance guarantees for single individual haplotyping

Sparse linear regression via generalized orthogonal least-squares

Nonnegative gridless compressive sensing for co-prime arrays

Beam tracking for mobile millimeter wave communication systems

Structurally-constrained gradient descent for matrix factorization in haplotype assembly problems

Non-uniformity correction of IR images using natural scene statistics

Distributed self localization of sensors with poisson deployment using extended Kalman filter

Optimal haplotype assembly with statistical pruning

Single individual haplotyping with low rank semidefinite programming

Haplotype assembly: An information-theoretic view

Iterative learning of single individual haplotypes from high-throughput DNA sequencing data

Deterministic sequential Monte Carlo for haplotype inference

A message passing algorithm for haplotype assembly

Message passing algorithm for inferring consensus sequence from next-generation sequencing data

Exploiting time series properties for mortality prediction in pediatric brain injury

Expected complexity of sphere decoding for sparse integer least-square problems

A message passing algorithm for reference-guided sequence assembly from high-throughput sequencing data

An imputation-enhanced algorithm for ICU mortality prediction

Base calling error rates in next-generation DNA sequencing

Adaptive experimental design for drug combinations

A sequential Monte Carlo base-calling method for next-generation DNA sequencing

An MCMC Algorithm for base calling in sequencing-by-synthesis

A message-passing algorithm for spectrum access in cognitive radio relay networks

Base-calling for Illumina’s next-generation DNA sequencing systems via Viterbi algorithm

A dual Kalman filter for parameter-state estimation in real-time DNA microarrays

Message-passing for base-calling in sequencing-by-synthesis systems

Distributed routing in networks using affinity propagation

Sequential Monte Carlo method for parameter estimation in diffusion models of affinity-based biosensors

Greedy sensor selection: Leveraging submodularity

Inference of gene-regulatory networks using message-passing algorithms

Model-based sequential base calling for Illumina sequencing

On parameter estimation for diffusion processes in real-time biosensors

Optimal estimation in DNA Microarrays via global optimization

Maximum likelihood DNA sequence detection via sphere decoding

Inferring parameters of gene regulatory networks via particle filtering

Further results on message-passing algorithms for motif finding

Rao-Blackwellized unscented Kalman filter for nonlinear systems with bandwidth constrains

Compressed sensing for bandwidth constrained systems

Limits of performance of real-time DNA microarrays

An MCMC algorithm for parameter estimation in stochastically modeled real-time biosensor arrays

Message-passing for motif finding

Stochastic modeling of reaction kinetics in biosensors using the Fokker-Planck equation

A particle filtering algorithm for parameter estimation in real-time biosensor arrays

Target estimation in real-time polymerase chain reaction using sequential Monte Carlo

Estimation in real-time affinity-based biosensors

Sparse measurements, compressed sampling, and DNA microarrays

On estimation in real-time microarrays

Signal processing aspects of real-time DNA microarrays

Signal processing for real-time DNA microarrays

On recovery of sparse signals in compressed DNA microarrays

Modeling the kinetics of hybridization in microarrays

PEP analysis of SDP-based non-coherent signal detection

ML estimation of DNA initial copy number in polymerase chain reaction processes

PEP analysis of the SDP based joint channel estimation and signal detection

On the performance of sphere decoding of block codes

On limits of performance of DNA microarrays

On joint maximum-likelihood estimation of PCR efficiency and initial amount of target

Further results on speeding up the sphere decoder

Asymptotic analysis of the Gaussian broadcast channel with perturbation preprocessing

Bounds on the performance of sphere decoding of linear block codes

An efficient H-infinity estimation approach to speed up the sphere decoder

An H-infinity based lower bound to speed up sphere decoder

Optimal estimation of gene expression levels in microarrays

A probabilistic model for inherent noise and systematic errors of microarrays

A branch and bound approach to speed up the sphere decoder

Rate maximization in multi-antenna broadcast channels with linear preprocessing

Statistical approach to ML decoding of linear block codes on symmetric channels

Nucleic acid detection using bioluminescence regenerative cycle and statistical signal processing

Sphere-constrained ML detection for channels with memory

On joint ML detection and decoding

Sphere-constrained ML detection for frequency-selective channels

Joint ML channel estimation and signal detection for SIMO channels

Low-complexity iterative detection and decoding of multi-antenna systems employing channel and space-time codes

Modified Fincke-Pohst algorithm for low-complexity iterative decoding over multiple antenna channels

Towards closing the capacity gap on multiple antenna channels

On the expected complexity of integer least-squares problems

On the expected complexity of sphere decoding for frequency-selective channels

Low-complexity iterative decoding over multiple antenna channels via a modified sphere decoder

On the expected complexity of sphere decoding

Optimal training for frequency-selective fading channels

On robust multiuser detection

CDMA multiuser detection based on state-space estimation techniques

Exponential-quadratic optimal signal reconstruction in noisy filter banks

Energy efficient design of portable wireless systems

Mixed H2/H-infinity optimal signal reconstruction in noisy filter banks

On H-infinity optimal signal reconstruction in noisy filter banks

Distributed detection in dependent nonGaussian noise

Distributed detection of known signals in Gaussian mixture noise which is dependent from sensor to sensor

Design and parameter adaptation of a fuzzy servo controller