Ehsanul Haque Nirjhar
Texas A&M University
16 Papers
6 Citations
Ehsanul Haque Nirjhar is an academic researcher from Texas A&M University. The author has contributed to research in topics: Public speaking & Computer science. The author has an hindex of 3, co-authored 7 publications. Previous affiliations of Ehsanul Haque Nirjhar include Texas A&M University System.
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Papers
Exploring individual differences of public speaking anxiety in real-life and virtual presentations
Megha Yadav,Nazmus Sakib,Ehsanul Haque Nirjhar,Kexin Feng,Amir H. Behzadan,Theodora Chaspari +5 more
TL;DR: In this paper, the effect of virtual reality training on alleviating public speaking anxiety is measured through self-reported and bio-behavioral indices, which indicate the significance of such traits to modeling PSA with the proposed group-based models yielding Spearman's correlation of 0:55 (¯¯¯¯ $p \lt 0:05$ ��) between the actual and predicted outcome.
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Exploring Bio-Behavioral Signal Trajectories of State Anxiety During Public Speaking
Ehsanul Haque Nirjhar,Amir H. Behzadan,Theodora Chaspari +2 more
- 04 May 2020
TL;DR: Using data from 55 participants in a real-life public speaking task, the parameters of the proposed models are found to be significantly correlated with individuals’ trait characteristics of general and communication-based anxiety, outperforming aggregate mean bio-behavioral measures.
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Investigating Trust in Human-Machine Learning Collaboration: A Pilot Study on Estimating Public Anxiety from Speech
Abdullah Aman Tutul,Ehsanul Haque Nirjhar,Theodora Chaspari +2 more
- 18 Oct 2021
TL;DR: In this paper, the authors examine trust in AI in the context of a human-AI partnership that involves a joint decision-making task for estimating levels of public speaking anxiety based on speech signals.
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•Posted Content
Analytic Provenance Datasets: A Data Repository of Human Analysis Activity and Interaction Logs
Sina Mohseni,Andrew Pachuilo,Ehsanul Haque Nirjhar,Rhema Linder,Alyssa M. Pena,Eric D. Ragan +5 more
TL;DR: An analytic provenance data repository that can be used to study human analysis activity, thought processes, and software interaction with visual analysis tools during exploratory data analysis with textual and cyber security data is presented.
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Detecting Changes in User Behavior to Understand Interaction Provenance during Visual Data Analysis.
Alyssa M. Pena,Ehsanul Haque Nirjhar,Andrew Pachuilo,Theodora Chaspari,Eric D. Ragan +4 more
- 01 Jan 2019
TL;DR: To understand how data-driven techniques can automatically identify changes in user behavior (inflection points) based on user interaction logs collected from eye tracking and mouse interactions, the results of a supervised classification system using Hidden Markov Models to predict changes in a visual data analysis of a cyber security scenario are relay.