About

About

About Me

Hello! I’m Akhil Chaudhary, a Data Scientist and ML Researcher specializing in NLP, Computer Vision, and Knowledge Graphs. With a proven track record of driving multimillion-dollar cost savings, advancing AI transparency, and publishing cutting-edge research, I bridge the gap between theoretical innovation and real-world impact. Currently, I lead research projects at the intersection of explainable AI and multiverse analytics while mentoring the next generation of data professionals.

Professional Experience

Research Project Manager | St. Francis Xavier University (Sep 2024 – Present)

  • Leading NSERC-funded research on fMRI multiverse analysis and fNIRS CVR sensitivity standards for concussion diagnostics.
  • Implementing Agile methodologies to manage full-cycle projects, collaborating with cross-functional stakeholders.

Research Fellow & Sessional Instructor | Cape Breton University (Jan 2023 – Present)

  • Pioneered explainable AI frameworks for LLM transparency, improving fact retrieval speed by 50%.
  • Authored 3+ influential papers on zero-shot fact-checking and knowledge graph querying (published in Expert Systems with Applications).
  • Teach courses: Machine Learning, Data Visualization, and Python programming.

Data Scientist | Gyan AI (Mar 2023 – Jan 2024)

  • Architected a Knowledge Graph-powered research engine for universities (UPenn, UF), streamlining data mobilization into ERP systems.
  • Directed full-stack development (Java/React) and ETL pipelines for enterprise search solutions.

Data Scientist | Denave (Sep 2021 – Dec 2021)

  • Engineered a propensity model boosting lead prioritization accuracy to 80%, yielding $40M in cost savings.
  • Optimized Transformer Networks for social media summarization, increasing campaign engagement by 40%.

Data Science Consultant | Allstate (Mar 2018 – Apr 2020)

  • Invented a blur detection algorithm that slashed manual review time by 75% and improved automation efficiency by 50%.
  • Automated claims processing (98% faster), handling millions of monthly transactions.

Key Achievements

  • $40M+ Cost Savings: Delivered through ML-driven lead prioritization and process automation.
  • 96% Accuracy Object Detection Model: Reduced operational downtime by 20% at Accenture.
  • 25% Accuracy Gain in NLP: Achieved via novel knowledge graph techniques for explainable AI.
  • 2 Patents Pending: For blur detection and multiverse analysis frameworks.

Recent Publications

  • A2Q: Fact Retrieval from Knowledge Graphs (2025)Semantic attention querying framework.
  • Explainable Zero-Shot Fact Checking (2024)Leveraging knowledge graphs for transparency.
  • Top2Label (2023)Expert Systems with ApplicationsSOTA in zero-shot topic labeling.

Education

  • Dalhousie University, Halifax, Canada
    Master of Science in Computer Science
    • Cumulative GPA: 4.16/4.30Graduate Research Funding Scholarship Awardee
    • Thesis: Top2Label: Explainable Zero-Shot Topic Labelling Using Knowledge Graphs

  • Centre for Development of Advanced Computing, Bengaluru, India
    Post Graduate Diploma in Advanced Computing

  • Dr. A.P.J. Abdul Kalam Technical University, Lucknow, India
    Bachelor of Technology in Computer Science

Technical Skills

  • Languages & Tools: Python, Java, Git, Docker, Kubernetes, AWS/GCP/Azure
  • Machine Learning: PyTorch, TensorFlow, NLP, Computer Vision, Knowledge Graphs
  • Data Engineering: ETL Pipelines, CI/CD, Spring Boot, React JS, Tableau

Let’s Connect!

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Let’s collaborate to turn data into actionable innovation!