## About

169

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Introduction

Additional affiliations

January 2009 - present

June 2005 - December 2008

August 1999 - March 2005

## Publications

Publications (169)

Most existing Time series classification (TSC) models lack interpretability and are difficult to inspect. Interpretable machine learning models can aid in discovering patterns in data as well as give easy-to-understand insights to domain specialists. In this study, we present Neuro-Symbolic Time Series Classification (NSTSC), a neuro-symbolic model...

In this work, we develop a novel neuro-symbolic model for automated seizure detection using multi-views of data representation. Firstly, the spectral and line length features are extracted using a multi-view feature extraction technique. Next, a signal temporal logic neural network (STONE) that combines the benefits of neural networks and temporal...

Circadian rhythm is an important biological process for humans as it modulates a wide range of physiological processes, including body temperature, sleep-wake cycle, and cognitive performance. As the most powerful external stimulus of circadian rhythm, light has been studied as a zeitgeber to regulate the circadian phase and sleep. This paper addre...

Spatial variance reduction of microbot systems through ensemble control, i.e., using a global control input, is a challenging task. In this paper, we propose to use a sequence of primary motion maneuvers called motion primitives to perform spatial variance reduction. We extract these primitives from the principal directions of the optimal control t...

Extracting spatial-temporal knowledge from data is useful in many applications. It is important that the obtained knowledge is human-interpretable and amenable to formal analysis. In this paper, we propose a method that trains neural networks to learn spatial-temporal properties in the form of weighted graph-based signal temporal logic (w-GSTL) for...

Extracting spatial-temporal knowledge from data is useful in many applications. It is important that the obtained knowledge is human-interpretable and amenable to formal analysis. In this paper, we propose a method that trains neural networks to learn spatial-temporal properties in the form of weighted graph-based signal temporal logic (wGSTL) form...

In this paper, we study the problem of decentralized motion planning of robot swarms under high-level temporal logic specifications with a top-down approach. We use Swarm Signal Temporal Logic (SwarmSTL) to express swarm-level specifications. By encoding SwarmSTL formulas as mixed binary-integer constraints on the swarm features, the motion plannin...

The circadian rhythm, called Process C, regulates a wide range of biological processes in humans including sleep, metabolism, body temperature, and hormone secretion. Light is the dominant synchronizer of the circadian rhythm—it has been used to regulate the circadian phase to cope with jet-lag, shift work, and sleep disorder. The homeostatic oscil...

In this paper, we propose a neuro-symbolic framework called weighted Signal Temporal Logic Neural Network (wSTL-NN) that combines the characteristics of neural networks and temporal logics. Weighted Signal Temporal Logic (wSTL) formulas are recursively composed of subformulas that are combined using logical and temporal operators. The quantitative...

Sleep schedule and circadian phase irregularity are associated with some health problems and diseases, e.g., narcolepsy, circadian disorder, and concussion. Actigraphy has been widely used in the study of sleep and circadian rhythms. This paper presents a method for estimating the sleep/wake state based on the minute-by-minute actigraphy data measu...

We report herein the application of an adaptive notch filter (ANF) algorithm to minute-by-minute actigraphy data to estimate the continuous circadian phase of eight healthy adults. As the adaptation rates and damping factor of the ANF algorithm have large impacts on the ANF states and circadian phase estimation results, we propose a method for opti...

In this paper, we develop a distributed monitoring framework for robot swarms so that the agents can monitor whether the executions of robot swarms satisfy Swarm Signal Temporal Logic (SwarmSTL) formulas. We define generalized moments (GMs) to represent swarm features. A dynamic generalized moments consensus algorithm (GMCA) with Kalman filter (KF)...

In this paper, we present a mechanism for building hybrid system observers to differentiate between specific positions of the hybrid system. The mechanism is designed through inferring metric temporal logic (MTL) formulae from simulated trajectories from the hybrid system. We first approximate the system behavior by simulating finitely many traject...

This work studies the user equilibrium (UE) state and the system optimal (SO) state in vehicular communication networks that support both V2V and V2I communication. Each user in this network is assumed to make route choice that optimizes a utility function that involves the traditional travel cost and the data communication utility. The overall soc...

The circadian rhythm functions as a master clock that regulates many physiological processes in humans including sleep, metabolism, hormone secretion, and neurobehavioral processes. Disruption of the circadian rhythm is known to have negative impacts on health. Light is the strongest circadian stimulus that can be used to regulate the circadian pha...

In this paper, we present a controller synthesis approach for wind turbine generators (WTG) and energy storage systems with metric temporal logic (MTL) specifications, with provable probabilistic guarantees in the stochastic environment of wind power generation. The MTL specifications are requirements for the grid frequency deviations, WTG rotor sp...

We seek a methodological approach to assess circadian processes in subjects who have recently experienced traumatic brain injury, using regularly gathered intracranial temperature data. The health effects of circadian regulation are profound, yet assessments of circadian processes are often infeasible in the neurotrauma intensive care unit (ICU). W...

In this letter, we propose methods to perform swarm behavior analysis with a novel swarm signal temporal logic (SwarmSTL). We define generalized moments to describe swarm features and propose a logical proposition to represent an event, where the Boolean value of the logical proposition at a certain time is known
a priori
. We develop methods for...

In complex cyber-physical system operations, fault detection needs to be performed using limited state information for practicality and privacy concerns. While a well-designed observation can distinguish a faulty behavior from the normal behavior, it can also represent the action of hiding some of the state information or discrete mode switchings....

Inferring spatial-temporal properties from data is important for many complex systems, such as additive manufacturing systems, swarm robotic systems and biological networks. Such systems can often be modeled as a labeled graph where labels on the nodes and edges represent relevant measurements such as temperatures and distances. We introduce graph...

Circadian rhythm is usually represented by the 24-hour biological cycles which are mainly driven by the daily light-dark cycle on earth. Light stimulus is widely used as the control input of the circadian system entrainment. In this paper, we study the light-based minimum-time circadian entrainment problem of mammals, Neurospora, and Drosophila bas...

Control of conventional transportation networks aims at bringing the state of the network (e.g., the traffic flows in the network) to the
system optimal
(SO) state. This optimum is characterized by the minimality of the social cost function, i.e., the total cost of travel (e.g., travel time) of all drivers. On the other hand, drivers are assumed...

This paper investigates the problem of inferring knowledge from data so that the inferred knowledge is interpretable and informative to humans who have prior knowledge. Given a dataset as a collection of system trajectories, we infer parametric linear temporal logic (pLTL) formulas that are informative and satisfied by the trajectories in the datas...

In this paper, we present a method to learn (infer) and refine a set of advices from the trajectories generated in the successful and failed attempts in a task or game, in the form of advisory signal temporal logic (STL) formulas. Each advice consists of an advisory motion STL formula that characterizes the spatial-temporal pattern of the motion as...

Actigraphy has been widely used for the analysis of circadian rhythm. Current practice applies regression analysis to data from multiple days to estimate the circadian phase. This paper presents a filtering method for online processing of biometric data to estimate the circadian phase. We apply the proposed method on actigraphy data of fruit flies...

For practical applications that involve microrobots there are several control related challenges. These challenges are often alleviated by constructing ideal environments, which are devoid of potential disturbances that can affect performance. However, in less idealistic working spaces where obstacles exist, microrobotic navigation algorithms must...

Tetrahymena pyriformis is a single cell eukaryote that can be modified to respond to magnetic fields, a response called magnetotaxis. Naturally, this microorganism cannot respond to magnetic fields, but after modification using iron oxide nanoparticles, cells are magnetized and exhibit constant magnetic dipole strength. In experiments, a rotating f...

We present an energy storage controller synthesis method for power systems with respect to metric temporal logic (MTL) specifications. The power systems with both constant impedance loads and constant power loads are modeled as a set of differential–algebraic equations. After a fault is cleared, with uncertainties in the fault clearing time, the ge...

Control of conventional transportation networks aims at bringing the state of the network to the system optimal (SO) state. This optimum is characterized by the minimality of the social cost function, i.e., the total cost of travel of all drivers. On the other hand, drivers are assumed to be rational and selfish, and make their travel decisions to...

The aim is to synthesize control inputs for robotic manipulator arms that ensure a desired task specification is executed while optimizing a desired performance objective. We use Metric Temporal Logic (MTL) to express the task specifications defined in terms of manipulating objects and implemented a hierarchical method combining Mixed Integer- Line...

Manipulation of cellular motility using a target signal can facilitate the development of biosensors or microbe-powered biorobots. Here, we engineered signal-dependent motility in Escherichia coli via the transcriptional control of a key motility gene. Without manipulating chemotaxis, signal-dependent switching of motility, either on or off, led to...

A formal safety controller synthesis method for power grid frequency regulation using energy storage systems is proposed. After a fault, with uncertainties in the fault clearing time, the generator machine angles and rotor speed deviations will enter a set of post-fault states that can be over-approximated using reachability analysis. We use the ro...

We present a formal robust testing method for power system cascading failure mitigations. The approach is model-based, using simulated trajectories of the system and proving that uncertainties, e.g., in the initial states or disturbances, do not perturb the trajectories beyond a robust neighborhood around them. We model power systems as hybrid syst...

We propose a method for discriminating among competing models for biological systems. Our approach is based on learning temporal logic formulas from data obtained by simulating the models. We apply this method to find dynamic features of epidermal growth factor (EGF) - induced extracellular regulated kinase (ERK) activation that are strictly unique...

The traditional method of circadian rhythm estimation is based on a double actogram that provides phase estimation on a daily basis, but not continuously and also fails to effectively filter noise. Our goal is to develop a circadian rhythm estimator that accurately and continuously estimates circadian phase while filtering noise. The estimator is a...

In this paper, we define a novel census signal temporal logic (CensusSTL) that focuses on the number of agents in different subsets of a group that complete a certain task specified by the STL. CensusSTL consists of an “inner logic” STL formula and an “outer logic” STL formula. We present a new inference algorithm to infer CensusSTL formulas from t...

Accurate estimation of circadian phase is critical to the assessment and treatment of circadian disruption. Direct measurements of circadian rhythm markers such as dim light melatonin onset and core body temperature are inconvenient and acquired at best at low rate. On the other hand, measurements of other circadian rhythm modulated signals such as...

Light is a strong synchronizer for circadian rhythm — the 24-h biological oscillation in plants, insects, and mammals. This paper considers the circadian entrainment problem for a popular circadian oscillation model (the Kronauer model) by using light intensity as the control input. This problem is commonly encountered by shift workers and internat...

The fundamental idea of this work is to synthesize reactive controllers such that closed-loop execution trajectories of the system satisfy desired specifications that ensure correct system behaviors, while optimizing a desired performance criteria. In our approach, the correctness of a system's behavior can be defined according to the system's rela...

First order phase reduced model is a good approximation of the dynamics of forced nonlinear oscillators near its limit cycle. The phase evolution is determined by the unforced frequency, the forcing term, and the phase response curve (PRC). Such models arise in biological oscillations such as in circadian rhythm, neural signaling, heart beat, etc....

Temporal logics are widely used to express (desired) system properties in controller synthesis and verification. In linear temporal logics, the semantics of the formulae are defined on the execution trajectories of the system. Recently, there have been a lot of interest in using dense-time linear temporal logic, such as Signal Temporal Logic (STL)...

In this study, a data-driven computational procedure was utilized in order to identify candidate transcription factors involved in the gene regulation network associated with mitogenactivated protein kinase (MAPK) signal transduction. Because the network reconstruction algorithm used for this study is relatively new, one purpose of the study was to...

The model-based fault diagnosability analysis is concerned with the timely detection and isolation of faults by using the system model and observations of the system output. In this paper, we propose the (δd, δm, α)-diagnosability notion for hybrid systems with probabilistic reset, where the faults are diagnosed by observing the timed event sequenc...

Tetrahymena pyriformis is a single cell eukaryote that can be modified to respond to magnetic fields, a response called magnetotaxis. Naturally, this microorganism cannot respond to magnetic fields, but after modification using iron oxide nanoparticles, cells are magnetized and exhibit a constant magnetic dipole strength. In experiments, a rotating...

For the design and implementation of engineering systems, performing
model-based analysis can disclose potential safety issues at an early stage.
The analysis of hybrid system models is in general difficult due to the
intrinsic complexity of hybrid dynamics. In this paper, a simulation-based
approach to formal verification of hybrid systems is pres...

This chapter presents a trajectory-based perspective in solving safety/ reachability analysis and synthesis problems and fault diagnosability analysis in hybrid systems. The main tool used in obtaining the results presented in this chapter is the concept of trajectory robustness, which is derived from the theory of approximate bisimulation. Traject...

This treatment of modern topics related to mathematical systems theory forms the proceedings of a workshop, Mathematical Systems Theory: From Behaviors to Nonlinear Control, held at the University of Groningen in July 2015. The workshop celebrated the work of Professors Arjan van der Schaft and Harry Trentelman, honouring their 60th Birthdays.
The...

Multi-link robots with elastic joints are receiving a lot of interest because neglecting joint flexibility introduced in industrial robots due to presence of transmission elements results in poor control performances. Robots with elastic joints also play a pivotal role in making human-robot interaction more safe. In this paper, we discuss the probl...

Untethered robotic microswimmers are very promising to significantly improve various types of minimally invasive surgeries by offering high accuracy at extremely small scales. A prime example is drug delivery, for which a large number of microswimmers is required to deliver sufficient dosages to target sites. For this reason, the controllability of...

Metric Temporal Logic (MTL) specifications can capture complex state and timing requirements. Given a nonlinear dynamical system and an MTL specification for that system, our goal is to find a trajectory that violates or satisfies the specification. This trajectory can be used as a concrete feedback to the system designer in the case of violation o...

We consider the problem of probabilistic safety verification for stochastic hybrid systems. In particular, we propose a method that combines two existing approaches, namely, analytical techniques and randomized algorithms. Analytical techniques, such as using stochastic approximate bisimulation, are able to handle non-deterministic initial states....