Page Not Found
Page not found. Your pixels are in another canvas.
Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Biography
About me
Page not in menu
This is a page not in th emain menu
Posts
other-publications
The critical modulatory role of spiny stellate cells in seizure onset based on dynamic analysis of a neural mass model
Published:
This study challenges the traditional view that seizures are solely caused by excessive excitation or reduced inhibition in the brain. Instead, it highlights the paradoxical role of both glutamatergic (excitatory) and GABAergic (inhibitory) neurotransmitters in seizure generation. By extending an existing thalamocortical model to include spiny stellate (excitatory interneuron) cells, the research demonstrates how these neurons are crucial for generating preictal activity—the transitional state before seizures. Through bifurcation analysis and simulations, the model replicates a wide range of brain dynamics, including normal activity, preictal spikes, absence seizures, clonic seizures, and tonic seizures. The findings reveal that the cooperation between excitatory and inhibitory mechanisms, particularly the role of spiny stellate cells and thalamic inputs, governs the transition from normal brain states to seizures. This extended mathematical model provides deeper insights into seizure prediction and may help develop more effective therapeutic strategies.
Download here
Subtyping Speech Errors in Childhood Speech Sound Disorders with Acoustic-to-Articulatory Speech Inversion
Published:
Acoustic-to-articulatory speech inversion, trained on adult ground-truth kinematic data, quantifies clinically interpretable information about tongue constriction and location for /ɹ/ → /w/, /ɹ/ → vowel, dentalized /s/, and palatalized /s/ speech sound errors in children and adolescents with speech sound disorders.
Download here
Perceptual Ratings Predict Speech Inversion Articulatory Kinematics in Childhood Speech Sound Disorders
Published:
This study provides empirical support for using inferred articulatory kinematic data to characterize perceptually rated speech sound errors in children with SSD. Articulatory kinematics were inferred using speech inversion neural networks. Findings demonstrate that inferred articulatory kinematic data were sensitive to both the phonetic category and magnitude of articulatory difference label using the PERCEPT Rating Scale, particularly for productions of /ɹ/. These results support the validation of speech inversion and the PERCEPT Rating Scale for speech science and clinical investigations of childhood SSD.
Download here
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
All-Electric NASA N3-X Aircraft Electric Power Systems
Published in IEEE Transactions on Transportation Electrification, 2022
This article introduces a fully electric version of NASA’s N3-X aircraft powered by four electrochemical energy units. It proposes and analyzes three medium-voltage DC and AC power system architectures using modified power flow solvers, evaluates cable conductors based on aircraft dimensions, and confirms the systems meet planning criteria under normal and contingency conditions.
Download here
Predictive Time-Series Analysis of Single-Qubit Quantum Circuit Outcomes for a Superconducting Quantum Computer: Forecasting Error Patterns
Published in IEEE ACCESS, 2025
In this work, we analyze and predict the output patterns of a single qubit quantum circuit by treating the results of repeated executions as a time series. Specifically, we collect measurement data from multiple runs of a quantum circuit and construct a time series from these observations. By training a predictive model, we aim to forecast future outcomes, providing insights into the error behavior of the quantum circuit. Additionally, we analyze time series data from two different circuits executed on the same qubit to investigate potential relationships and assess whether one dataset can be used to predict the other. Our findings reveal key characteristics of quantum circuit outputs, including stationarity, autocorrelation, seasonality, trends, linearity, and causality. The analysis highlights intriguing behaviors within the dataset. Furthermore, we evaluate multiple time series prediction methods and determine that XGBoost (Extreme Gradient Boosting) outperforms other approaches, demonstrating its effectiveness in accurately predicting quantum computing outputs in subsequent runs.”
Download here
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.