Bazarla Vikas

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Experience

AI Intern

Prisalis Private India Limited · Aug 2025 – Dec 2025

Not yet confirmed

Built an end-to-end NLP pipeline to normalize and classify unstructured clinical chief complaints into standardized medical categories, improving downstream data usability.
Designed a hybrid rule-based + machine learning system (regex, medical dictionaries, ML fallback) to handle spelling errors, abbreviations, negations, and multi-symptom clinical inputs.
Improved automated labeling coverage from ~80% to 90%+ by expanding rule patterns, medical vocabularies, and normalization mappings through systematic error analysis.
Implemented abbreviation expansion, spelling correction (SymSpell), fuzzy matching (RapidFuzz), and negation detection, significantly reducing noise in raw clinical text.
Trained and evaluated TF-IDF-based classifiers (Naive Bayes, Logistic Regression), iteratively optimizing preprocessing to improve classification accuracy and consistency.
Manual review effort by automating complaint normalization and categorization, enabling scalable

Skills 0 proven through work

Also works with

Software Library DevelopmentTeam SupportIdea SharingSeeking MentorshipRequirements AnalysisTaking OwnershipInterpersonal SkillsTechnical Knowledge SharingTeamworkAdaptabilityGoal setting (defining key results)OrganizationReceiving and Incorporating FeedbackProblem SolvingMachine Learning ApplicationText ClassificationText PreprocessingUnstructured Text Cleaning & PreparationAI Solution ImplementationNLP Text AnalysisPython Development

Proof of Work

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Education

Bachelor of Technology, Computer Science and Engineering

Lovely Professional University · 2022 — NaN

Junior College, Intermediate

Rishi Junior Collage · 2020 — 2022

High School, Matriculation

Mount Basil High School · 2019 — 2020

Links

linkedin.com/in/vikas-bazarla

Contact details

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