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Anuj Saha
SOFTWARE ENGINEER

I build intelligent software
where AI meets real-world products.

Computer Science undergraduate at IIIT Vadodara building software across AI/ML, deep learning, medical computer vision, and full-stack web applications.

View selected work→Explore research→
BASED IN

Gandhinagar / Kolkata, India

EDUCATION

IIIT Vadodara · B.Tech in Computer Science and Engineering (2023—2027)

CORE FOCUS

Full-Stack · AI/ML · Medical Imaging · Research

01 / ABOUT & IDENTITY

Building at the Intersection of Software, AI, and Research

I am a Computer Science undergraduate at IIIT Vadodara working across full-stack software development, artificial intelligence, and deep learning. My focus is on building reliable applications where modern machine learning methods connect with usable products.

My work ranges from real-time web telemetry systems and developer tooling to biomedical machine learning pipelines. Whether developing clean user interfaces or evaluating feature selection routines in complex datasets, I focus on readable code, disciplined validation, and clear architectural design.

I believe effective technical software requires rigor across every layer-treating data processing, validation routines, and user experience with equal importance.

CURRENTLY[INITIALIZED]
Computer Science & Engineering
IIIT Vadodara · 2023—2027
LOCATION: Gandhinagar, Gujarat, India
CORE TECHNICAL FOCUS
  • ▪Software Engineering
  • ▪AI / Machine Learning
  • ▪Deep Learning
  • ▪Medical Imaging
  • ▪Research & Data Applications
ENGINEERING APPROACHBUILD → RESEARCH → SHIP
01STEP 01

SYSTEM-LEVEL THINKING

Care about the complete pipeline—from data ingestion and representation to model execution and user interface design.

02STEP 02

METHODOLOGICAL RIGOR

Treat data preprocessing, feature selection, statistical validation, and leakage prevention as core engineering problems.

03STEP 03

PRODUCT RELEVANCE

Build technical software that solves real-world problems and transitions smoothly into usable, maintainable tools.

02 / EXPERIENCE

Building Through Real Technical Work

Roles where software engineering, machine learning, research, and technical problem-solving were applied in practice.

01Research Intern

Indian Institute of Information Technology Vadodara

May 2026 — July 2026
Gandhinagar, India
SCOPE & TECHNICAL OWNERSHIP

Worked as a Research Intern at IIIT Vadodara developing biomedical machine learning workflows. Responsibilities focused on data preprocessing (missing-value and outlier handling), hybrid feature selection (Mutual Information, RFE, Random Forest importance), baseline model training, and statistical cross-validation.

TECHNICAL FOCUS & METHODOLOGIES
PythonPyTorchMRI ImagingFeature SelectionMachine LearningLeakage-Aware ValidationExplainability
03 / SKILLS & TECHNICAL TOOLKIT

Technical Stack & Core Disciplines

Categorized technical stack spanning software engineering, machine learning pipelines, full-stack web development, and developer tooling.

01LANGUAGES
PythonTypeScriptJavaScriptJavaC
02FRAMEWORKS & WEB
React.jsNext.jsNode.jsExpress.jsTailwind CSSREST APIs
03AI / MACHINE LEARNING
PyTorchTensorFlowScikit-LearnNumPyPandasMatplotlibComputer Vision
04DATA & INFRASTRUCTURE
MySQLMongoDBGit
05AI / DEVELOPER TOOLS
StreamlitGenkitGoogle AI / Gemini
05 / CERTIFICATIONS & CREDENTIALS

Verified Learning & Technical Credentials

Five verified credentials spanning machine learning, deep learning, algorithms, generative/AI foundations, and cloud fundamentals.

01VERIFIED CREDENTIAL

Machine Learning Specialization

Stanford University + DeepLearning.AI

VIEW CREDENTIAL↗
06 / SELECTED WORK

Representative Software & Research Systems

A curated selection of technical projects spanning deep learning medical imaging, real-time financial telemetry, machine learning time-series forecasting, and applied AI developer tooling.

MEDICAL AI · DEEP LEARNING · RESEARCH

Lobe-wise Glioma Analysis & MGMT/IDH Glioma Prediction

01 / 04

Deep learning framework for spatial lobe-wise brain tumor analysis and molecular biomarker prediction (MGMT/IDH status) using leakage-aware validation routines.

PythonPyTorchMRI ImagingFeature Extraction
COMPUTATIONAL WORKFLOW
SPATIAL PIPELINE
SPATIAL LOBE PARCELLATION
01
MRI / MULTIMODAL DATAMultimodal Brain Imaging Datasets
INPUT
02
LOBE-WISE PARCELLATIONSpatial Anatomical Feature Extraction
FEATURES
03
FEATURE SELECTIONDimensionality Reduction & Importance
SELECTION
04
MODEL TRAININGLeakage-Aware Validation Routines
TRAINING
05
MGMT / IDH PREDICTIONMolecular Biomarker Status Profiling
TARGET
PREDICTION TARGETS:MGMT METHYLATION & IDH MUTATION
FULL STACK · REAL-TIME SYSTEMS · FINTECH

Stock Insights — Real-Time Financial Dashboard

02 / 04

Real-time telemetry dashboard integrating live WebSocket price streams, technical indicators (RSI, MACD), and automated news sentiment processing.

ReactTypeScriptNext.jsWebSocket
REAL-TIME DATA STREAM
WEBSOCKET ARCHITECTURE
LIVE TELEMETRY STREAMLOW-LATENCY FEED
TECHNICAL INDICATORRSI COMPUTATION
TREND ANALYSISMACD SIGNALS
DATA AGGREGATIONNEWS SENTIMENT
MACHINE LEARNING · TIME SERIES · FINANCIAL ANALYSIS

Market Movement Forecasting

03 / 04

Built machine learning models to predict short-term market movement using historical price data and technical indicators.

PythonScikit-learnPandasNumPy
TIME-SERIES FORECASTING PIPELINE
ML MODELING
HISTORICAL PRICE & INDICATOR SIGNALTREND DIRECTIONAL FORECAST
PREPROCESSINGPRICE CLEANING & SCALING
FEATURE ENGINEERINGTECHNICAL INDICATORS
DIRECTIONAL MODELTREND FORECASTING
APPLIED AI · LLM · DEVELOPER TOOLS

DocAtlas — AI-Powered Documentation Extractor

04 / 04

Intelligent documentation crawler and parsing pipeline powered by LLM models (OpenAI, Gemini, Groq) to transform docs into structured JSON export schemas.

PythonStreamlitLLM APIs (OpenAI/Gemini/Groq)Doc Crawling
DOCUMENTATION EXTRACTION PIPELINE
LLM PARSING
PROCESSING PIPELINE STAGES
URL CRAWL
DOM PARSE
LLM INGEST
JSON EXPORT
EXTRACTED STRUCTURAL NODES
MODULEDocumentation Source Page
HEADING & SECTIONHierarchical Document Structure
CODE BLOCK & PARAMSSyntax & Parameter Schema
STRUCTURED JSONExportable Module Metadata
PROVIDERS: OPENAI · GEMINI · GROQCLI & STREAMLIT UI
07 / RESEARCH & METHODOLOGY

Building Reliable Machine Learning Pipelines

Building reliable machine learning systems means caring about what happens between raw data and the final prediction.

01RESEARCH INTERN

Indian Institute of Information Technology Vadodara

May 2026 — July 2026
Gandhinagar, India

RESEARCH FOCUS

Engineered a leakage-free multimodal machine learning pipeline combining structural MRI features and tabular biomarker data. Applied systematic data preprocessing, hybrid feature selection (Mutual Information, RFE, Random Forest importance), baseline classification modeling, statistical validation, and anatomically interpretable MRI biomarker explainability techniques.

RESEARCH PRINCIPLE
“A model is only as trustworthy as the pipeline that produces its prediction.”
Focus: Leakage-aware cross-validation, feature importance, and anatomical interpretability.
PIPELINE STAGE OVERVIEW7 STAGES
01 RAW DATA02 PREPROCESS03 REPRESENTATION04 FEATURE SELECTION05 CLASSIFICATION06 LEAKAGE-AWARE VALIDATION07 EXPLAINABILITY
08 / LEADERSHIP & CAMPUS ENGAGEMENTS

Institutional Initiatives & Student Leadership

Coordinating placement operations, innovation policy execution, corporate relations outreach, and technical events at IIIT Vadodara.

01Training & Placement Cell Coordinator
May 2025 — Present
Gandhinagar, India
IIIT Vadodara

Coordinating student training programs, placement logistics, and industry engagement initiatives at IIIT Vadodara.

02SSIP Cell Coordinator
Feb 2024 — Present
Gandhinagar, India
IIIT Vadodara

Coordinating Student Startup & Innovation Policy (SSIP) activities, fostering student technical projects and innovation initiatives.

03Corporate Relations Lead
Jan 2024 — August 2026
Gandhinagar, India
IIITV Finance & Consulting Club

Leading corporate relations outreach, organizing guest speaker sessions, and managing club engagement.

04Core Member
May 2024 — March 2026
Gandhinagar, India
IIITV Technical Committee

Organizing institute hackathons, coding workshops, and campus-wide technical events.

09 / CONTACT & PROFILES

LET'S BUILD SOMETHING WORTH SHIPPING.

Have a project, research idea, or technical problem worth discussing? Send a message directly using the form below.

For any queries, reach out to me on anujsahabest0111@gmail.com

EXTERNAL PROFILES
GITHUB↗
Source Code & Projects ↗
LINKEDIN↗
Professional Network ↗
KAGGLE↗
Data Science & ML ↗
LEETCODE↗
Algorithms & Problem Solving ↗