I am a researcher in computer science and engineering with experience in deep learning, deep computer vision systems, and software engineering. I have been a research associate at the University of Waterloo, collaborating with Prof. Krzysztof Czarnecki. In this role, I specialized in out-of-distribution detection, 3D object detection, and domain adaptation for autonomous vehicles, contributing to advancements in autonomous driving technology.
Before this, I completed a postdoctoral fellowship at the University of Waterloo under the supervision of Prof. Krzysztof Czarnecki. During my post-doc, I focused on Explainable AI (XAI), active learning, and uncertainty estimation for deep neural networks, further honing my expertise in cutting-edge machine learning techniques.
I have obtained my Ph.D. from the University of Ottawa, where I worked under the esteemed supervision of Prof. Timothy C. Lethbridge. My doctoral research centered on modularity for model-based software engineering, and I made significant contributions to the Umple project.
3D Object Detection with Track-Based Auto-Labelling Using Very Sparsely Labelled Data
Mei Qi Tang, Vahdat Abdelzad , Chengjie Huang, Sean Sedwards, Krzysztof Czarnecki.
ITSC, 2024.
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Out-of-Distribution Detection for LiDAR-based 3D Object Detection
Chengjie Huang, Van Duong Nguyen, Vahdat Abdelzad, Christopher Gus Mannes, Luke Rowe, Benjamin Therien, Rick Salay, Krzysztof Czarnecki.
ITSC, 2022.
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LiDAR-MIMO: Efficient Uncertainty Estimation for LiDAR-based 3D Object Detection
Matthew Pitropov, Chengjie Huang, Vahdat Abdelzad, Krzysztof Czarnecki, Steven Waslander.
IV, 2022.
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The Missing Link: Developing a Safety Case for Perception Components in Automated Driving
Rick Salay, Krzysztof Czarnecki, Hiroshi Kuwajima, Hirotoshi Yasuoka, Vahdat Abdelzad, Chengjie Huang, Maximilian Kahn, Van Duong Nguyen, Toshihiro Nakae.
SAE, 2022.
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XC: Exploring Quantitative Use Cases for Explanations in 3D Object Detection
Sunsheng Gu, Vahdat Abdelzad, Krzysztof Czarnecki.
XAI4Debugging, NeurIPS, 2021.
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Umple: Model-driven Development for Open Source and Education
Timothy C Lethbridge, Andrew Forward, Omar Badreddin, Dusan Brestovansky, Miguel Garzon, Hamoud Aljamaan, Sultan Eid, Ahmed Husseini Orabi, Mahmoud Husseini Orabi, Vahdat Abdelzad, Opeyemi Adesina, Aliaa Alghamdi, Abdulaziz Algablan, Amid Zakariapour.
Science of Computer Programming, Volume 208, 2021.
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Non-divergent Imitation for Verification of Complex Learned Controllers
Vahdat Abdelzad, Jaeyoung Lee, Sean Sedwards, Soheil Soltani, Krzysztof Czarnecki.
IJCNN, 2021.
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The Effect of Optimization Methods on the Robustness of Out-of-Distribution Detection Approaches
Vahdat Abdelzad, Krzysztof Czarnecki, Rick Salay.
arXiv:2006.14584, 2020.
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Simple Continual Learning Strategies for Safer Classifers
Ashish Gaurav, Sachin Vernekar, Jaeyoung Lee, Vahdat Abdelzad, Krzysztof Czarnecki, Sean Sedwards.
SafeAI, AAAI, 2020.
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Improved Policy Extraction via Online Q-Value Distillation
Aman Jhunjhunwala, Jaeyoung Lee, Sean Sedwards, Vahdat Abdelzad, Krzysztof Czarnecki.
WCCI, 2020.
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Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer Output
Vahdat Abdelzad, Krzysztof Czarnecki, Rick Salay, Taylor Denouden, Sachin Vernekar, Buu Phan.
arXiv:1910.10307, 2019.
Out-of-distribution Detection in Classifiers via Generation
Sachin Vernekar, Ashish Gaurav, Vahdat Abdelzad, Taylor Denouden, Rick Salay, Krzysztof Czarnecki.
Safety and Robustness in Decision Making Workshop, NeurIPS, 2019.
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Analysis of Confident-Classifiers for Out-of-distribution Detection
Sachin Vernekar, Ashish Gaurav, Taylor Denouden, Buu Phan, Vahdat Abdelzad, Rick Salay, Krzysztof Czarnecki.
SafeML, ICLR, 2019.
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Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance
Taylor Denouden, Rick Salay, Krzysztof Czarnecki, Vahdat Abdelzad, Buu Phan, Sachin Vernekar.
arXiv:1812.02765, 2018.
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Calibrating Uncertainties in Object Localization Task
Buu Phan, Rick Salay, Krzysztof Czarnecki, Vahdat Abdelzad, Taylor Denouden, Sachin Vernekar.
The Third Bayesian Deep Learning Workshop, NeurIPS, 2018.
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Collaborative Software Design and Modeling in Open Source Systems
Omar Badredd, Wahab Hamou-Lhad, Vahdat Abdelzad, Rahad Khandoker, Maged Elassar.
SAM, 2018.
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Merging Modeling and Programming using Umple
Timothy Lethbridge, Vahdat Abdelzad, Mahmoud Husseini Orabi, Ahmed Husseini Orabi, Opeyemi Adesina.
ISoLA, 2016.
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fSysML: Foundational Executable SysML for Cyber-Physical System Modeling
Omar Badreddin, Vahdat Abdelzad, Timothy Lethbridge and Maged Elaasar.
GEMOC, 2016.
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The Role of Semiotic Engineering in Software Engineering
Vahdat Abdelzad, Timothy C. Lethbridge, Mahmood Hosseini.
TOSE, ICSE, 2016.
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Promoting Traits into Model-Driven Development
Vahdat Abdelzad, Timothy C. Lethbridge.
Software & Systems Modeling, 2015.
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Extended Traits for Model-Driven Software Development
Vahdat Abdelzad.
Doctoral Symposium at MoDELS, 2015.
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Adding a Textual Syntax to an Existing Graphical Modeling Language: Experience Report with GRL
Vahdat Abdelzad, Daniel Amyot, Timothy C. Lethbridge.
SDL, 2015.
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A Textual Syntax with Tool Support for the Goal-oriented Requirement Language
Vahdat Abdelzad, Daniel Amyot, Sanaa A. Alwidian, Timothy C. Lethbridge.
The i* Workshop, 2015.
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A Model-Driven Solution for Financial Data Representation Expressed in FIXML
Vahdat Abdelzad, Hamoud Aljamaan, Opeyemi Adesina, Miguel A. Garzon, Timothy C. Lethbridge.
TTC, STAF, 2014.
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Testing Aspect-Oriented Programs with UML Activity Diagrams
Somayeh Madadpour, Seyed-Hassan Mirian-Hosseinabadi, Vahdat Abdelzad.
IJCA, vol. 33, no. 8, 2011.
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Aspect-Oriented Software Development Versus Other Development Methods
Vahdat Abdelzad, Fereidoon Shams Aliess.
JATIT, vol. 31, no. 2, 2011.
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A Method Based on Petri Net for Identification of Aspects
Vahdat Abdelzad, Fereidoon Shams Aliess.
Early Aspects, AOSD, 2010.
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