Leads TAILab research on the theory and practice of trustworthy machine learning, with emphasis on statistical and adversarial robustness, uncertainty, security, privacy, and dependable AI systems.
Trustworthy AIML robustnessSecurity & privacyOptimization
Research record +
Thesis / project
Not applicable / in progress.
Abstract / research summary
Public abstract not currently available.
PhD · Computer Engineering · 2026
Hamed Karimi
Postdoctoral Fellow, Toronto Metropolitan University · TAILab
Develops statistically grounded uncertainty-quantification methods for reliable deep learning, spanning conformal prediction, evidential learning, out-of-distribution detection, medical AI, and LLM reliability.
Uncertainty quantificationConformal predictionOOD detectionTrustworthy AI
Research record +
Abstract / research summary
Studies theoretical and practical foundations for predictive uncertainty in deep learning, with methods that connect uncertainty representations to calibrated decisions and reliability guarantees under distribution shift and high-stakes deployment.
PhD · Computer Engineering · 2026
Mohammadreza Maleki
Postdoctoral Fellow, Toronto Metropolitan University · TAILab
Researches scalable certification and verification of neural-network robustness, with emphasis on optimization-based bounds and efficient model-agnostic verification.
Certified robustnessNeural network verificationOptimization
Research record +
Abstract / research summary
Addresses the accuracy–scalability tension in certified robustness through tighter optimization relaxations, cascading verification strategies, class-aware robust evaluation, and certification methods for neural-network ensembles.
PhD Student · Computer Engineering
Cassandra Czobit
Toronto Metropolitan University · TAILab
Researches trustworthy learning for clinical and mental-health applications, including neuroimage translation and language-model methods for health prediction.
Medical AIGenerative modelsLLMsMental health
Research record +
Abstract / research summary
Developed and evaluated CycleGAN-based translation of neuroimages across MRI field strengths, comparing generated images using quantitative image-quality measures and adversarial baselines.
PhD Candidate · Computer Engineering
Luzalen Marcus
Toronto Metropolitan University · TAILab
Investigates trustworthy machine learning at the intersection of language, computation, and model reliability.
Trustworthy MLComputational linguisticsLanguage models
Research record +
Thesis / project
Doctoral research in progress
Abstract / research summary
Current doctoral work; thesis title and abstract will be added when formally available.
Selected publications are not separately indexed here; see the lab publication record.
PhD Candidate · Computer Science
Akihiro Sakasegawa(Co-supervised with Dr. Antoine Deza)
McMaster University · TAILab
Spectral Graph Theory.
GNNGraph TheoryDiffusion, Transportation
Research record +
Thesis / project
Doctoral research in progress
Abstract / research summary
Current doctoral work; thesis title and abstract will be added when formally available.
Selected publications are not separately indexed here; see the lab publication record.
MASc · Computer Engineering
Nathan Kowal
Graduate Researcher
Master’s research focused on AI Safety.
Confidence measurementUncertainty QuantificationMachine learning
Research record +
Abstract / research summary
.
Selected publications are not separately indexed here; see the lab publication record.
MASc · Computer Engineering · 2026
Vaishali Meyappan
Machine Learning Engineer, Pinterest
Graduate research focused on uncertainty and confidence for language models, including semantic uncertainty and conformal risk control.
LLM confidenceConformal predictionSemantic uncertainty
Research record +
Thesis / project
MASc thesis · title not yet publicly indexed in repositories checked
Abstract / research summary
Graduate research centered on reliable LLM uncertainty quantification using semantic disagreement, adaptive uncertainty inflation, and conformal calibration for risk-controlled model responses.
PhD · Computer Engineering · 2025
Hirad Daneshvar
Applied Researcher (Query Science), eBay
Works on trustworthy deep learning for healthcare and graph learning, with research in uncertainty quantification, calibration, efficient graph learning, and mental-health outcome prediction.
Trustworthy GNNsHealthcare AICalibrationUncertainty
Research record +
Abstract / research summary
Doctoral work developed trustworthy graph-learning methods for healthcare predictive modelling, emphasizing mental-health outcomes, model calibration, uncertainty quantification, and efficient learning from patient graphs.
PhD · Software Engineering · 2024
Mini Thomas(Co-supervised with Dr. Antoine Deza (McMaster Univ.))
Associate Dean / Professor, Mohawk College
Developed formal, data-driven methods for quantifying trust in wearable medical devices under uncertainty.
Trust quantificationWearable medical devicesBayesian networks
Research record +
Abstract / research summary
Identifies and validates factors that influence trust in wearable medical devices, then models trust as a probabilistic Bayesian network. The framework supports data-driven parameter estimation, inference, and configurable comparison of device trustworthiness.
MASc · Computer Engineering · 2024
Md. Mahmud Ferdous
Data Engineer, Tata Consultancy Services
Worked on security, privacy, and machine learning, including health-sensing research associated with Mitacs/iMD Research.
Security & privacyMachine learningHealth sensing
Research record +
Thesis / project
MASc thesis · formal repository title not located in public search
Abstract / research summary
Publicly available lab records connect this research to trustworthy machine learning, privacy, and multi-sensor health applications; a formal thesis abstract was not located in the repositories checked.
Selected publications are not separately indexed here; see the lab publication record.
MASc · Computer Engineering
Daniel Sadig
Graduate Researcher
Master’s research focused on robustness certification for ensemble neural networks.
Certified robustnessEnsemble networksMachine learning
Research record +
Abstract / research summary
Developed certification ideas for ensemble networks, studying how aggregation and probabilistic reasoning can be used to produce robustness guarantees beyond single-model verification.
MEng · Computer Engineering
Ashkan Khademi Gharalar
Graduate Researcher
Master’s research focused on LLM Safety.
LLM SafetyMachine LearningLLM Toxicity
Research record +
Abstract / research summary
.
Selected publications are not separately indexed here; see the lab publication record.
MEng · Computer Engineering
Abraham Sandoya
Graduate Researcher
Master’s research focused on power grids cybersecurity and anomaly detection using AI.
CybersecurityPower GridsMachine learning
Research record +
Abstract / research summary
.
Selected publications are not separately indexed here; see the lab publication record.
MEng · Computer Engineering
Nashira Nasrudeen
Graduate Researcher
Master’s research focused on robustness certification for ensemble neural networks.
LLM SafetyLLM as a JudgeMachine learning
Research record +
Abstract / research summary
.
Selected publications are not separately indexed here; see the lab publication record.
MEng · Computer Engineering · 2025
Saeideh Mousavi
---
Studied security of medical vision-language models against prompt-injection attacks.
Medical AIVision-language modelsPrompt injection
Research record +
Thesis / project
MEng project: An Investigation into Prompt Injection Attacks Against Medical Vision-Language Models
Abstract / research summary
Evaluated how prompt-injection attacks can alter or compromise the behavior of medical vision-language systems and explored implications for safe clinical deployment.
Selected publications are not separately indexed here; see the lab publication record.
MEng · Computer Engineering · 2025
Hao Luo
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Studied ensemble robustness and confidence analysis using CrossMax and provable-defense perspectives.
Certified robustnessEnsemblesConfidence analysis
Research record +
Thesis / project
MEng project: Exploring Ensemble Robustness with CrossMax: From Provable Defenses to Confidence Analysis
Abstract / research summary
Examined ensemble prediction under adversarial perturbations, connecting provable robustness concepts to confidence behavior and CrossMax-style aggregation.
Selected publications are not separately indexed here; see the lab publication record.
MASc · Computer Engineering · 2024
Bradley Rose
Research Engineer, Huawei
Researched model generalization under distribution shift and adversarial perturbations.
OOD generalizationAdversarial robustness
Research record +
Thesis / project
MASc research: OOD Generalization and Adversarial Robustness
Abstract / research summary
Studied the relationship between out-of-distribution generalization and robustness to adversarial inputs; formal thesis metadata was not located in public repository search.
Selected publications are not separately indexed here; see the lab publication record.
MEng · Computer Engineering · 2023
Magdalean Singarajah
Senior Consultant, Deloitte
Investigated privacy–utility trade-offs in transformer-based medical language models.
Medical LLMsDifferential privacy
Research record +
Thesis / project
MEng project: Benchmarking Differentially Private Transformer-Based Medical LLMs
Abstract / research summary
Benchmarked transformer-based medical language models trained or adapted with differential-privacy mechanisms, emphasizing the practical privacy–performance trade-off.
Selected publications are not separately indexed here; see the lab publication record.
MEng · Computer Engineering · 2023
Bipin Aasi
Educator, Durham College
Developed a framework for systematically comparing adversarial attacks against language models.
LLM robustnessAdversarial attacks
Research record +
Thesis / project
MEng project: Framework to Benchmark Adversarial Attacks on Language Models
Abstract / research summary
Structured evaluation of attack strategies and robustness behavior for language models; formal project report was not located in the public repositories checked.
Selected publications are not separately indexed here; see the lab publication record.
PhD · Computer Science · 2023
Moe Sabry(Co-supervised with Dr. Douglas Stebila (Waterloo Univ.) and Dr. Emil Sekirinski (McMaster Univ.))
Software engineering leadership, Fortra
Research in cryptographic systems and secure, durable digital archiving.
SecurityCryptographyLong-term archives
Research record +
Abstract / research summary
Designed secure long-term archival mechanisms intended to preserve confidentiality, integrity, and verifiability as cryptographic assumptions and systems evolve over long time horizons.
MASc · Computer Engineering · 2023
Mina Yazdani
Data Scientist, Manulife
Researched diversity and randomized/noisy-logit mechanisms for improving neural-network robustness.
ML securityAdversarial robustnessEnsembles
Research record +
Abstract / research summary
Investigated ensemble diversity and noise-based logit transformations as practical mechanisms to improve robustness, with evaluation against adversarial attacks and reliability trade-offs.
PhD · Biomedical Engineering · 2021; Postdoctoral Fellow · 2023
Omar Boursalie(Co-supervised with Dr. Thomas Doyle (McMaster Univ.))
Assistant Professor, Schulich School of Engineering · University of Calgary
Researches digital health, remote monitoring, and AI-enabled clinical decision support.
Medical AIRemote monitoringPredictive health
Research record +
Thesis / project
Temporally-Embedded Deep Learning Model for Health Outcome Prediction
Abstract / research summary
Developed temporally aware deep-learning models for health-outcome prediction from longitudinal physiological and clinical data, building on earlier work in mobile cardiovascular monitoring.
MSc · Computer Science · 2020
Yuting Liang
Postdoctoral Fellow, University of Toronto
Works at the intersection of privacy-preserving data analytics and secure machine learning.
PrivacyOptimizationAdversarial robustness
Research record +
Abstract / research summary
Developed optimization methods for privacy-preserving data anonymization and investigated defensive techniques for adversarially robust machine learning.
MSc · Computer Science · 2020
Yifan Ou
Director of Software, Billionspectra Innovation Inc.
Applied game theory to strategic interactions between poisoning attackers and machine-learning defenders.
Data poisoningGame theoryML security
Research record +
Abstract / research summary
Models poisoning defense as an attacker–defender game, characterizes Nash-equilibrium behavior for distance-based defenses, and derives an efficient approximation strategy for robust defense selection.
Selected publications are not separately indexed here; see the lab publication record.
MSc · Computer Science · 2020
Vanessa Calero Bravo
---
Studied practical privacy risks in online social platforms.
PrivacySocial networksRisk measurement
Research record +
Thesis / project
A Framework for Measuring Privacy Risks of YouTube
Abstract / research summary
Proposed a framework for evaluating privacy risk on YouTube by representing and assessing the ways personal information may be exposed or inferred through platform activity; a repository record was not located in public search.
Selected publications are not separately indexed here; see the lab publication record.
MEng · 2020
Saman Dhindsa(Co-supervised with Dr. Gail Krantzberg)
Technical Service Analyst, DependableIT
Studied privacy principles and governance concerns for facial-recognition technologies.
PrivacyFacial recognitionSecurity
Research record +
Thesis / project
MEng project: Privacy Principles for Facial Recognition Technology
Abstract / research summary
Analyzed privacy principles relevant to facial-recognition systems and translated them into practical considerations for responsible deployment.
Selected publications are not separately indexed here; see the lab publication record.
MSc · Computer Science · 2019
Karl Knopf(Co-supervised with Dr. Douglas Stebila)
PhD Student, University of Waterloo
Developed cryptographic protocols for secure real-world secret leaking.
SecurityCryptographyWhistleblowing
Research record +
Abstract / research summary
Designed protocols that allow a confidential leaker to disclose information while enabling recipients to verify origin and authenticity, with a focus on practical security and formal guarantees.
Selected publications are not separately indexed here; see the lab publication record.
MEng · Computer Science · 2019
Pouyan Momeni
Senior Software Developer, Scotiabank
Worked on machine-learning techniques for smart-contract security and a Mitacs project on decentralized software validation.
Smart contractsBlockchainSoftware security
Research record +
Abstract / research summary
Explored machine-learning approaches for smart-contract security analysis alongside blockchain-based mechanisms for distributing software validation across minimally trusted parties.
Selected publications are not separately indexed here; see the lab publication record.
MSc · Computer Science · 2018
Andrew Sutton
Blockchain Application Developer, RBC
Studied verifiable trust and privacy-aware collaboration in health research.
BlockchainHealth dataVerifiable trust
Research record +
Abstract / research summary
Proposes a blockchain-enabled architecture for verifiable trust in collaborative health research so institutions, researchers, and AI systems can share and analyze sensitive data while preserving provenance, integrity, and accountability.
Selected publications are not separately indexed here; see the lab publication record.
MSc · eHealth · 2018
Mingyuan Li
Solution Developer, CIHI
Developed semantic representations for privacy-aware data-sharing agreements.
Privacy ontologyData sharingSemantic web
Research record +
Abstract / research summary
Introduced an ontology for representing privacy constraints and policies in data-sharing agreements, supporting machine-readable privacy requirements and more systematic auditing.
MSc · eHealth · 2018
Sameen Ateeq
Principal Chief Executive Officer, Sam's Home Care, Psalm's Digital Studi
Applied predictive analytics to identify factors associated with fall-related injuries.
Health analyticsRisk prediction
Research record +
Abstract / research summary
Used Canadian Community Health Survey data with PCA and random forests to identify high-priority behavioural and health predictors of fall-related injuries, emphasizing population-level prevention and the sensitivity–accuracy trade-off of the resulting models.
Selected publications are not separately indexed here; see the lab publication record.
MSc · eHealth · 2017
Ali Ariaeinejad
Software Developer, Faculty of Health Sciences, McMaster University
Used machine learning to identify residents who may need additional educational support.
Clinical predictionCompetency-based educationHealth analytics
Research record +
Abstract / research summary
Uses competency-based medical-education data to develop predictive models that can identify emergency-medicine residents at risk of underperformance and support earlier educational intervention.
Selected publications are not separately indexed here; see the lab publication record.
USRA · Arts & Science · 2020
Anna Lindsay-Mosher
Undergraduate research alumna
Completed a McMaster Undergraduate Student Research Award with TAILab on data and semantic methods for understanding police violence in Ontario.
Machine learningSemantic modellingSocial good
Research record +
Abstract / research summary
The project used machine learning and semantic structure ideas to organize and analyze police-report information as a basis for studying and mitigating police violence. This was an undergraduate research project rather than a graduate thesis.
Selected publications are not separately indexed here; see the lab publication record.
MEng · Computer Science · 2017
Qian Shan
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Developed a mobile augmented-reality system for real-time 3D brain-tumor visualization.
Augmented realityMedical imaging3D visualization
Research record +
Abstract / research summary
Built a mobile AR pipeline that uses facial features for tracking and camera-pose estimation, then overlays a reconstructed 3D brain-tumor model at the corresponding anatomical location for real-time visualization.
MEng · Computer Science · 2017
Farshad Rahimi Asl(Co-supervised with Dr. Fei Chiang)
Software Engineer, IBM
Worked on privacy-aware web services and secure cloud-system design.
PrivacyCloud servicesData engineering
Research record +
Thesis / project
MEng project: Privacy Aware Web Services in the Cloud
Abstract / research summary
Developed privacy-aware mechanisms for cloud web services, connecting service design and access to explicit privacy constraints. A public project-report repository record was not located.
MEng · Computer Science · 2016
Xiao Dong
Senior Software Engineer, BlueCat
Developed semantic models for privacy-aware access control in healthcare.
Health privacyOntologyAccess control
Research record +
Abstract / research summary
Defines a machine-computable circle-of-care ontology for reasoning about legitimate access to patient records, including use with FHIR data and audit logs to identify potentially illegitimate access.
MEng · Computer Science · 2016
Salman Khawaja
Lead iOS Developer, RBC
Studied privacy and security controls for accessing electronic health records from mobile devices.
Health privacyMobile securityElectronic health records
Research record +
Thesis / project
MEng project: Securing the Privacy of Electronic Health Records on Mobile Phones
Abstract / research summary
Examined mechanisms for protecting sensitive electronic health-record data in mobile access scenarios. A public project report or current professional affiliation was not located in the sources checked.
Selected publications are not separately indexed here; see the lab publication record.
Repository and employment links are from publicly available sources as of August 2026.
