Lovedeep Gondara
Head of AI R&D | Vanguard
Adjunct Professor | University of British Columbia
About
I am a machine learning researcher, currently serving as Head of AI R&D at Vanguard. I also hold an Adjunct Professor position at University of British Columbia. My current work focuses on language models (large and small) and their applications in various domains. My broader research interests include general machine learning, differential privacy, and multimodal machine learning.
Research Interests
Language Models
Large and small language models with applications across various domains, particularly in resource-constrained environments. Agentic methods and model grounding.
Privacy-Preserving ML
Differential privacy and privacy-preserving machine learning techniques for sensitive data applications.
Applied Machine Learning
Applying machine learning to solve complex real-world problems using approaches for text, vision, tabular, and multimodal data. Focus on translating research into practical solutions.
Contact & Links
Contact Information
Vanguard
Enterprise AI and Research (EAiR)
Toronto, ON, Canada
University of British Columbia
School of Population and Public Health
E-mail: lovedeep.gondara@ubc.ca
Research Areas
Machine Learning, Large Language Models, Differential Privacy, Deep Learning, Decentralized Learning, Statistics, Application of ML and LLMs to various domains.
Education
Work Experience
• Designed and developed NLP models for data abstraction, classification, and summarization
• Led and guided the complete lifecycle of LLM development, including data collection and curation, pretraining, supervised finetuning, and alignment
• Developed and deployed RAG based and agentic methods to streamline operations
• Considered ethical implications in large language models, such as bias mitigation, fairness, privacy, and security concerns
• Collaborated with internal and external entities for research and to integrate NLP technologies into real-world applications and solutions
• Disseminated findings via research papers, technical reports, and documentation at conferences, workshops, and meetings
• Supervised visiting researchers and students
• Guest lectures in areas of expertise
• Chair MSc and PhD dissertation exams as needed
• Supervise graduate students
• Design and implementation of interactive dashboards to serve models for visualizing trends, performance monitoring, and predictions in real time
• Develop and implement state-of-the-art machine learning and statistical models for end-to-end operational and research pipelines
• Provide technical expertise regarding data architecture and data standards for the development and maintenance of databases to facilitate reporting and research
• Coordinate internal and external data requests for planning and research
• Participate in recruitment, selection, and training of junior data scientists, interns, and summer students
• Provide leadership to team members via technical expertise and the facilitation and demonstration of the principles of team work and collaboration
• Manage all incoming projects and ensure deliverables by assigning the projects to and coordinating with different team members
Recent Selected Publications
1. Gondara, L., Arbour, G., Ng, R., Simkin, J., & Devji, S. (2025). Bridging AI Innovation and Healthcare Needs: Lessons Learned from Incorporating Modern NLP at The BC Cancer Registry. arXiv preprint arXiv:2508.09991.
2. Gondara, L., Simkin, J., Sayle, G., Devji, S., Arbour, G., & Ng, R. Small or Large? Zero-Shot or Finetuned? Guiding Language Model Choice for Specialized Applications in Healthcare. arXiv:2504.21191.
3. Beheshti, M., Gondara, L., & Zachary, I. Leveraging Language Models for Automated Patient Record Linkage. arXiv:2504.15261.
4. Gondara, L., Simkin, J., Devji, S.Arbour, G., & Ng, R. ELM: Ensemble of Language Models for Predicting Tumor Group from Pathology Reports. arXiv:2503.21800.
2024:
5. Gondara, L., Simkin, J., & Devji, S. Clinical Trial Design Approach to Auditing Language Models in Health Care Setting. JCO Clinical Cancer Informatics, 9, e2400331.
6. Gondara, L., Simkin, J., Arbour, G., Devji, S., & Ng, R. Classifying Tumor Reportability Status From Unstructured Electronic Pathology Reports Using Language Models in a Population-Based Cancer Registry Setting. JCO Clinical Cancer Informatics, 8, e2400110.
2023:
7. Gondara, L., & Wang, K. PubSub-ML: A Model Streaming Alternative to Federated Learning. Proceedings on Privacy Enhancing Technologies, 2, 464–479.
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