Skills
⟨/⟩
Programming & Tools
Python, SQL, Java, JavaScript, TypeScript, R, C++, Scala, Git, Docker, Kubernetes, Excel, Tableau, Power BI, Jupyter, VS Code
🧠
Machine Learning & AI
Deep Learning (CNNs, UNet, ResNet, EfficientNet, MobileNet), XGBoost, Random Forest, NLP, LLMs (GPT, BERT, Claude), Computer Vision, Time Series Forecasting, Predictive Modeling, Reinforcement Learning, Neural Networks, MLOps, AutoML, Model Deployment
📊
Data Science & Analytics
Data Cleaning, Feature Engineering, Exploratory Data Analysis (EDA), Visualization (Matplotlib, Seaborn, Plotly), Statistical Analysis, A/B Testing, Hypothesis Testing, Big Data (Apache Spark), Data Mining, ETL Pipelines, Data Warehousing
☁️
Software & Cloud
Full-Stack Development (React, Next.js, FastAPI, Flask, Django), REST APIs, GraphQL, Microservices, AWS (S3, EC2, Lambda, SageMaker), GCP (BigQuery, Vertex AI), Azure, Terraform, CI/CD, Scalable Pipelines
⚙️
Automation & Optimization
OCR / NLP Pipelines, Workflow Optimization, End-to-End ML Systems, Model Monitoring, Performance Tuning, Process Automation, RPA, DevOps, Infrastructure as Code, Continuous Integration
👥
Team & Project Skills
Agile Development (Scrum, Kanban), Cross-Functional Collaboration, Leadership, Mentoring, Research & Analytics Reporting, Technical Documentation, Stakeholder Management, Product Strategy, Problem Solving
Key Projects
Here are a few projects where I've built scalable software and data-driven solutions, applying ML, Data Science, and Software Development skills to real-world problems.
AI-Powered Multimodal Chronic Disease Risk Screener
Multimodal chronic disease risk screener using retinal + nailbed images with CNNs and gradient-boosted trees. AUC 0.999 (retina), 96.7% accuracy (nailbed).
Tech Stack: CNNs, EfficientNet, Gradient Boosted Trees, FastAPI, React
Impact: Near-clinical performance and low-cost screening for early detection in resource-limited settings.
Multi-Organ Segmentation in Medical Imaging (UNet-ResNet34)
Automated multi-organ CT segmentation with UNet-ResNet34 and mixed-precision training. 88.2% Dice, 4× faster inference.
Tech Stack: UNet-ResNet34, Mixed Precision Training, Pixel-Based Dataset Balancing
Impact: Reduces radiologist workload and speeds up treatment planning for abdominal imaging.
Intelligent Urban Traffic Management System
Computer-vision traffic monitoring with MobileNet-based detectors and ML policies. 15% congestion reduction in simulation.
Tech Stack: MobileNet Transfer Learning, End-to-End Inference Pipeline
Impact: Enables scalable, camera-based traffic control without expensive sensor infrastructure.
Publication
Selected research on reliable LLM-based code generation and applied AI.
Professional Experience
I've contributed to impactful projects across AI, ML, Data Science, and Software Development, translating complex problems into actionable solutions.
Research Assistant – CalTAP
California Transportation Analytics Program
Translated complex technical research into decision-oriented insights for non-technical stakeholders
• Synthesized peer-reviewed studies, evaluation reports, and real-world datasets
• Authored data-driven briefs, newsletters, and analytical articles
• Supported iterative research refinement aligned with evolving metrics and policy frameworks
AI/ML Intern – Finlogic Technologies
Finlogic Technologies India Pvt. Ltd.
Developed and deployed LLM-based agents, predictive models, and computer vision pipelines
• Built XGBoost and Monte Carlo models achieving 97% accuracy
• Developed ConvNeXt + OCR pipelines, reducing human effort by 70%
• Managed end-to-end ML systems: data preprocessing, model training, API deployment, and performance tuning
• Optimized inference pipelines, improving response latency by 30%
AI Developer & Data Scientist Intern – Daira Edtech
Daira Edtech Pvt. Ltd.
Improved ML workflows and extracted insights from large-scale user data
• Developed NLP-based sentiment analysis and topic modeling, improving response workflows by 20%
• Refactored ML pipelines for 78% faster training and scalable deployment
• Translated insights from 5,000+ users into actionable recommendations connecting AI outputs with business decisions
Education
🎓
Master of Science in Computer Science – California State University, Long Beach | GPA: 3.4/4.0
Jan 2026 – Present
Enterprise AI, Machine Learning, Machine Vision, Scalable AI Systems
🎓
Bachelor of Technology in Computer Engineering with Honors – SCET | GPA: 3.9/4.0
June 2021 – June 2025
Artificial Intelligence, Machine Learning, Deep Learning, Predictive Analytics, Data Mining, Big Data Analytics
Get in Touch
Open to full-time roles and internships in AI, Machine Learning, and Software Engineering. Recruiters and hiring managers can reach me directly at niyatikapadia111@gmail.com or via LinkedIn