Maliha Sanjana
@malihasanjana
I build computer vision and machine learning pipelines for medical imaging and real-world prediction problems.
What I'm looking for
I've built and evaluated machine learning and deep learning models at Neurootix across diverse computer vision datasets, contributing to model selection, pipeline refinement, and research-driven AI development.
My work includes fine-tuning MedSAM ViT-B for FLARE22 liver tumor segmentation, where validation Dice reached approximately 0.84 and accuracy approximately 0.98. I've also developed diabetic retinopathy segmentation models, PlantVillage crop disease classifiers, and a heart disease prediction pipeline.
I pair AI development with practical product work, including responsive web applications and a browser-based phishing detection dashboard. I also lead hands-on Python and image-processing workshops that connect theory with deployment.
Experience
Work history, roles, and key accomplishments
AI/ML Engineer
Neurootix
Aug 2025 - Present (1 year)
Designed, tested, and evaluated multiple machine learning and deep learning models across diverse computer vision datasets. Conducted applied experiments aligned with ongoing AI projects, contributing to model selection, pipeline refinement, and research-driven development. Directed technical skill development workshops on Python and Image Processing.
Built a rule-based chatbot prototype to interpret financial data from 10-K and 10-Q reports. Processed structured financial datasets and generated user-friendly outputs.
Data Science Job Simulation
British Airways
May 2025 - May 2025 (0 months)
Analyzed customer review data to extract themes linked to satisfaction and buying behavior. Built a predictive model to identify key drivers of purchase decisions.
Education
Degrees, certifications, and relevant coursework
Northern University Bangladesh
Bachelor of Science, Computer Science and Engineering
2021 - 2025
Grade: 3.669/4.0
Pursued a Bachelor of Science in Computer Science and Engineering, achieving a CGPA of 3.669 out of 4.0.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
Skills
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