65 citations · 168 across the 18 of their papers we have counts for
24 papers
Draining Fictitious Knots: Restoring Distance-Awareness Guarantees for High-Dimensional Spline Networks
Masoud Ataei, Mohammad Javad Khojasteh, Vikas Dhiman
Kolmogorov-Arnold Networks (KANs) with spline activations have recently shown promise for interpretable function approximation. Distance-Aware Error for Kolmogorov Networks (DAREK)…
How Do Large Language Models Judge Social Attraction? Evidence from Theory-Grounded Persona Ratings Across Multiple LLMs and Humans
Hasan Mahmud, Khawaja Abaid Ullah, Mohammad Javad Khojasteh +2
Large language models (LLMs) are increasingly used to perform subjective evaluations traditionally made by humans, yet their validity as social judges remains unclear. This paper e…
ADS-C: Antidistillation Sampling for Classification
Khawaja Abaid Ullah, Mohammad Javad Khojasteh
Knowledge distillation enables an adversary to replicate a proprietary classifier by querying its prediction interface and training a surrogate on the returned probability vectors.…
Engagement-Aware Agentic Pursuit-Evasion
Ananya Acharya, Trenton Goyette, Masoud Ataei +3
This paper presents a hierarchical multi-agent architecture in which independent large language model (LLM) planners perform strategic role assignment for attacking and defending r…
When Robots Rate Their Own Interactions: Engagement Validity and the Strangeness Failure
Victor Lockwood, Hasan Mahmud, Mohammad Javad Khojasteh +2
Human-robot interaction (HRI) evaluation relies almost exclusively on human-completed questionnaires, leaving the robot's perspective unexamined. We propose an \textit{inverted eva…
VINA: Variational Invertible Neural Architectures
Shubhanshu Shekhar, Mohammad Javad Khojasteh, Ananya Acharya +2
The distinctive architectural features of normalizing flows (NFs), notably bijectivity and tractable Jacobians, make them well-suited for generative modeling. Invertible neural net…
Worst-Case Distance-Aware Error Bounds for Neural Networks
Masoud Ataei, Vikas Dhiman, Mohammad Javad Khojasteh
Safety-critical applications of machine learning require uncertainty estimates that support reliable worst-case analysis. Neural networks (NNs) provide expressive function approxim…
Distance-Aware Error for Spline Networks: A Bottom-Up Approach to Uncertainty
Masoud Ataei, Mohammad Javad Khojasteh, Vikas Dhiman
We develop a new class of distance-aware error bounds that tightly characterize the approximation error of spline neural networks. Our bottom-up approach analyzes the error bound o…
Importance Sampling With Stochastic Particle Flow and Diffusion Optimization
Wenyu Zhang, Mohammad J. Khojasteh, Nikolay A. Atanasov +1
Particle flow (PFL) is an effective method for overcoming particle degeneracy, the main limitation of particle filtering. In PFL, particles are migrated towards regions of high lik…
Particle Flows for Source Localization in 3-D Using TDOA Measurements
Wenyu Zhang, Mohammad Javad Khojasteh, Florian Meyer
Localization using time-difference of arrival (TDOA) has myriad applications, e.g., in passive surveillance systems and marine mammal research. In this paper, we present a Bayesian…
ISR: Invertible Symbolic Regression
Tony Tohme, Mohammad Javad Khojasteh, Mohsen Sadr +2
We introduce an Invertible Symbolic Regression (ISR) method. It is a machine learning technique that generates analytical relationships between inputs and outputs of a given datase…
Uncertainty-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric
Dawei Sun, Mohammad Javad Khojasteh, Shubhanshu Shekhar +1
In this paper, we consider the problem of using a robot to explore an environment with an unknown, state-dependent disturbance function while avoiding some forbidden areas. The goa…
Control Barriers in Bayesian Learning of System Dynamics
Vikas Dhiman, Mohammad Javad Khojasteh, Massimo Franceschetti +1
This paper focuses on learning a model of system dynamics online while satisfying safety constraints. Our objective is to avoid offline system identification or hand-specified mode…
Learning-based attacks in Cyber-Physical Systems: Exploration, Detection, and Control Cost trade-offs
Anshuka Rangi, Mohammad Javad Khojasteh, Massimo Franceschetti
We study the problem of learning-based attacks in linear systems, where the communication channel between the controller and the plant can be hijacked by a malicious attacker. We a…
Safe Multi-Agent Interaction through Robust Control Barrier Functions with Learned Uncertainties
Richard Cheng, Mohammad Javad Khojasteh, Aaron D. Ames +1
Robots operating in real world settings must navigate and maintain safety while interacting with many heterogeneous agents and obstacles. Multi-Agent Control Barrier Functions (CBF…
Probabilistic Safety Constraints for Learned High Relative Degree System Dynamics
Mohammad Javad Khojasteh, Vikas Dhiman, Massimo Franceschetti +1
This paper focuses on learning a model of system dynamics online while satisfying safety constraints.Our motivation is to avoid offline system identification or hand-specified dyna…
Theory and implementation of event-triggered stabilization over digital channels
Mohammad Javad Khojasteh, Mojtaba Hedayatpour, Massimo Franceschetti
In the context of event-triggered control, the timing of the triggering events carries information about the state of the system that can be used for stabilization. At each trigger…
Learning-based attacks in cyber-physical systems
Mohammad Javad Khojasteh, Anatoly Khina, Massimo Franceschetti +1
We introduce the problem of learning-based attacks in a simple abstraction of cyber-physical systems---the case of a discrete-time, linear, time-invariant plant that may be subject…
Exploiting timing information in event-triggered stabilization of linear systems with disturbances
Mohammad Javad Khojasteh, Mojtaba Hedayatpour, Jorge Cortes +1
In the same way that subsequent pauses in spoken language are used to convey information, it is also possible to transmit information in communication networks not only by message…
Stabilizing a linear system using phone calls when time is information
Mohammad Javad Khojasteh, Massimo Franceschetti, Gireeja Ranade
We consider the problem of stabilizing an undisturbed, scalar, linear system over a "timing" channel, namely a channel where information is communicated through the timestamps of t…
Event-triggered stabilization of disturbed linear systems over digital channels
Mohammad Javad Khojasteh, Mojtaba Hedayatpour, Jorge Cortes +1
We present an event-triggered control strategy for stabilizing a scalar, continuous-time, time-invariant, linear system over a digital communication channel having bounded delay, a…
Time-triggering versus event-triggering control over communication channels
Mohammad Javad Khojasteh, Pavankumar Tallapragada, Jorge Cortes +1
Time-triggered and event-triggered control strategies for stabilization of an unstable plant over a rate-limited communication channel subject to unknown, bounded delay are studied…
Circulant Matrix Representation of PN-sequences with Ideal Autocorrelation Property
Mohammad J. Khojasteh, Morteza H. Shoreh, Jawad A. Salehi
In this paper, we investigate PN-sequences with ideal autocorrelation property and the consequences of this property on the number of +1s and -1s and run structure of sequences. We…
The value of timing information in event-triggered control
Mohammad Javad Khojasteh, Pavankumar Tallapragada, Jorge Cortés +1
We study event-triggered control for stabilization of unstable linear plants over rate-limited communication channels subject to unknown, bounded delay. On one hand, the timing of…