Works (5)

Updated: July 5th, 2023 15:33

2020 article

Debugging Hiring: What Went Right and What Went Wrong in the Technical Interview Process

2020 IEEE/ACM 42ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: SOFTWARE ENGINEERING IN SOCIETY (ICSE-SEIS 2021), pp. 71–80.

By: M. Behroozi n, S. Shirolkar n, T. Barik* & C. Parnin n

author keywords: career; hiring practices; interview feedback; opinion mining; reviews; software engineering; technical interviews; whiteboard
TL;DR: The findings provide a set of guidelines to help companies improve their hiring pipeline practices, such as being deliberate about phrasing and language during initial contact with the candidate, providing candidates with constructive feedback after their interviews, and bringing salary transparency and long-term career discussions into offers and negotiations. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: November 1, 2021

2019 article

Beyond the Code Itself: How Programmers Really Look at Pull Requests

2019 IEEE/ACM 41ST INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: SOFTWARE ENGINEERING IN SOCIETY (ICSE-SEIS 2019), pp. 51–60.

By: D. Ford n, M. Behroozi n, A. Serebrenik* & C. Parnin n

author keywords: transparency; code contributions; open source software development; eye-tracking; socio-technical ecosystems
TL;DR: It is found that after the code snippet, the second place programmers spent their time fixating is on supplemental technical signals, such as previous contributions and popular repositories, and it is also found that programmers fixated on social signals more than recalled. (via Semantic Scholar)
UN Sustainable Development Goal Categories
5. Gender Equality (OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: October 5, 2020

2018 article

Dazed: Measuring the Cognitive Load of Solving Technical Interview Problems at the Whiteboard

2018 IEEE/ACM 40TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: NEW IDEAS AND EMERGING TECHNOLOGIES RESULTS (ICSE-NIER), pp. 93–96.

By: M. Behroozi n, A. Lui*, I. Moore n, D. Ford n & C. Parnin n

Contributors: M. Behroozi n, A. Lui*, I. Moore n, D. Ford n & C. Parnin n

author keywords: technical interviews; cognitive load; eyetracking
TL;DR: An approach where a head-mounted eye-tracker and computer vision algorithms are used to collect robust metrics of cognitive state to create a vision for creating a more inclusive technical interview process through future studies of interventions that lower cognitive load and stress. (via Semantic Scholar)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: December 3, 2018

2016 journal article

A multiple-classifier framework for Parkinson's disease detection based on various vocal tests

International Journal of Telemedicine and Applications, 2016.

By: M. Behroozi* & A. Sami*

Contributors: M. Behroozi* & A. Sami*

TL;DR: A new framework that applies an independent classifier for each vocal test is introduced that enhances classification accuracy up to 15% and also enhances filter-based feature selection. (via Semantic Scholar)
Source: ORCID
Added: June 9, 2019

2013 conference paper

Presenting a new cascade structure for multiclass problems

2013 International Conference on Electronics, Computer and Computation, ICECCO 2013, 192–195.

By: M. Behroozi* & R. Boostani*

Contributors: M. Behroozi* & R. Boostani*

TL;DR: A new architecture of cascaded classifiers is proposed to handle multi-class tasks and LogitBoost is used as the base classifier due to its low sensitivity to the noisy samples. (via Semantic Scholar)
Source: ORCID
Added: June 9, 2019

Employment

Updated: October 10th, 2018 20:27

2016 - present

North Carolina State University Raleigh, NC, US
Research Assistant Computer Science

2014 - 2016

Shiraz University Shiraz, Fars, IR
Researcher Computer Science & Engineering

Education

Updated: September 10th, 2020 23:46

2011 - 2014

Shiraz University Shiraz University, Fars, IR
Artificial Intelligence M.Sc. Computer Science & Engineering

Citation Index includes data from a number of different sources. If you have questions about the sources of data in the Citation Index or need a set of data which is free to re-distribute, please contact us.

Certain data included herein are derived from the Web of Science© and InCites© (2024) of Clarivate Analytics. All rights reserved. You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.