About
Welcome to my blog.
I am a Machine Learning Engineer and Applied AI Researcher specializing in Generative AI, Large Language Models (LLMs), and production-grade AI systems. I focus on building scalable and robust AI solutions using domain-adaptive fine-tuning, LoRA/PEFT methods, and reinforcement learning, with hands-on experience in fast-paced startup environments.
I have end-to-end experience across the ML lifecycle, including large-scale data preprocessing, feature engineering, model training, evaluation frameworks, inference optimization, and performance benchmarking. I am proficient in Python and deep learning frameworks such as PyTorch, TensorFlow, and HuggingFace Transformers, with practical experience fine-tuning transformer models like BERT for domain-specific applications.
My work bridges research and engineering, translating state-of-the-art ML techniques into production systems through systematic experimentation, error analysis, and scalable ML pipelines on GCP and AWS.
I am a first author of two peer-reviewed research papers published in Springer Nature and PMLR proceedings, indexed in DBLP, ACM, and Google Scholar.
Education : Master of Science – Computing & Information Systems (focus on ML/NLP) Athabasca University, Canada Thesis - A Parameter-Efficient Framework for Word Sense Disambiguation through Low-Rank and Decomposed Adaptation
Grade: GPA - 4.0/4.0
1. Recipient of Outstanding Distinction Award 🏅 for Graduate Students
2. Recipient of Graduate Research Fellowship Award 🏅
Publications (First author)
Vijayalakshmi Manikandan, Dunwei Wen, M. Ali Akber Dewan. GlossAdapter: Enhancing word sense disambiguation via LoRA adapters. Proceedings of the 39th Canadian Conference on Artificial Intelligence, PMLR 318:1044-1051, 2026. Link - Link to paper
Manikandan, V., Wen, D., Dewan, M.A.A. (2027). Parameter-Efficient Multi-task Learning for Biomedical Abbreviation Disambiguation. In: Ni, H., Cafolla, D. (eds) Artificial Intelligence in Healthcare. AIiH 2026. Lecture Notes in Computer Science, vol 16875. Springer, Cham. Link - Link to paper
On my blog, you’ll find a collection of articles exploring the fascinating realms of AI and ML. My mission is simple: to share my ML journey, from experiments and coding adventures to valuable insights and learnings. Join me as we dive deep into the world of machine learning together!