I’m an engineer with a creative edge and a deep technical foundation—designing and building intelligent systems that make a measurable impact. My work spans the full lifecycle of product development: from architecting scalable web platforms and deploying production-grade machine learning models, to designing data pipelines and integrating multimodal AI into real-world applications.

With a Master’s in Data Science from Northeastern University and over four years of experience across startups, research labs, and enterprise teams, I’ve contributed to solutions in healthcare, infrastructure, assistive robotics, and sustainability. I thrive at the intersection of software engineering and applied machine learning—where thoughtful design meets powerful execution.

I believe impactful systems are those that are not just intelligent, but also usable, scalable, and ethically built.

• Applied Machine Learning
• Generative AI & Large Language Models (LLMs)
• Computer Vision for Healthcare & Infrastructure
• Retrieval Augmented Generation (RAG) Systems
• ML Systems Deployment (FastAPI, Docker, CI/CD)

• 🌱 Fine-tuning transformer models for sustainability awareness (SAGE project)
• 🏥 Building interpretable cancer cell classifiers for histopathology (CVPR 2024)
• 🧠 Designing RAG systems for enterprise search and summarization
• 🏡 Using regression and SHAP to explain rental predictions (SRIE project)
• 🗺 Mapping broadband equity using geospatial ML for government planning

Rental Price Prediction with Model Explainability

• Built a regression-based price estimator for real estate listings
• Achieved R² of 0.936 using feature selection, boosting & XGBoost
• Visualized feature impact using SHAP values for trust and transparency
• Tech: FastAPI, scikit-learn, Pandas, Docker

Enterprise Search Assistant Using LLM + Vector DBs

• Combined Qdrant, LlamaIndex, OpenAI APIs & local Llamafile inference
• Parsed 500+ documents and exposed a streaming chatbot interface
• Used SentenceTransformers for optimal document embedding retrieval
• Tech: Python, Qdrant, OpenAI, Langchain, Gradio

An Environmental Awareness Chat Assistant

• Combined DistilBERT + GPT to create a domain-aligned sustainability agent
• Embedded context and fallback routing to an OpenAI assistant
• Designed front-end UI for citizens to ask carbon, energy, and waste queries

Medical Imaging Classification Using Deep CNNs

• Classified B- and T-cell cancer subtypes using U-Net & ResNet variants
• Improved detection accuracy by 20% over baseline models
• Published at CVPR 2024 (check arXiv)

• Performed brain network clustering from multi-channel EEG data
• Reduced runtime by 50% using algorithmic optimization
• Presented at Northeastern’s RISE Expo 2024

• Used PCA + K-Means to cluster behavioral health records for dropout risk
• Proposed metrics-driven interventions to boost retention

• Built tract-level broadband coverage map using FCC + census data
• Identified digital divide zones across 358 tracts for planning outreach
• Delivered insights to government for equitable infrastructure investment

Mar 2025 – Present | Seattle, WA

• Architected scalable data pipelines to track gym equipment usage and user engagement, powering analytics for facilities.
• Designed and implemented interactive dashboards to monitor session patterns and identify underutilized assets.
• Defined foundational engagement metrics used by stakeholders for decision-making on equipment investment and scheduling.
• Proposed and prototyped an NLP-based chatbot assistant to automate operational FAQs, streamlining internal support processes.
• Collaborated cross-functionally across product, frontend, and backend teams to embed real-time analytics into the Redprint platform. Tech: Python, SQL, Streamlit, React, AWS, Firebase

Jul 2024 – Aug 2024 | Boston, MA

• Designed voice-enabled UI components and integrated them with patient-facing iOS apps to improve accessibility for ALS patients.
• Trained health prediction models (XGBoost) on synthetic and real-world Apple Health data, achieving >85% accuracy in wellness estimations.
• Created a cognitive training module (Clock Game) with real-time feedback and speech support for Alzheimer’s patients.
• Worked closely with medical researchers and accessibility experts to validate use-case fit and design for inclusivity. Tech: Swift, Python, XGBoost, MediaPipe, YOLO, AudioKit, HealthKit

Jan 2024 – Jun 2024 | New York, NY

• Developed computer vision models (YOLOv8, Detectron2) for automatic detection of façade anomalies, improving structural issue identification by 25%.
• Streamlined reporting through automated JSON-based workflows and dynamic templates for ASTM-compliant inspection summaries.
• Integrated OpenAI’s LLM APIs to handle user queries on inspection results, enabling instant answers and contextual insights.
• Created modular SDK tools for rapid deployment of NLP and vision components across inspection sites.
• Tested and optimized OpenAI-based scripts for accurate JSON retrieval and response classification in production use cases. Tech: Python, PyTorch, YOLOv8, Detectron2, OpenAI API, LLMs, JSON

Mar 2022 – Aug 2022 | Hyderabad, India

• Led development of data-driven dashboards using Power BI and SSRS, enabling executive-level insights into ROI, churn, and cost allocation.
• Automated ETL pipelines across diverse data sources, improving report generation speed by 50%.
• Integrated backend optimizations and DAX modeling to streamline visualization layers and reduce load time.
• Championed full-stack + data workflows, bridging .NET and BI systems for seamless SaaS delivery.
• Mentored junior engineers, onboarded cross-functional collaborators, and was honored as "Star of the Month" for high-impact delivery. Tech: Power BI, SQL Server, .NET Core, Angular, SSRS, DAX

Dec 2019 – Mar 2022 | Hyderabad, India

• Built a multi-tier SaaS platform for IT asset disposal, integrating frontend dashboards (Angular) with backend services (C# .NET).
• Designed and deployed RESTful APIs supporting large-scale workflows across asset tagging, recycling, and lifecycle reporting.
• Created optimized SQL procedures (3000+ lines) and reduced query runtimes by 40% through advanced indexing and refactoring.
• Delivered high-performance Angular modules for real-time status tracking and audit compliance reporting.
• Gained exposure to enterprise-grade architecture and implemented end-to-end features under tight agile cycles. Tech: .NET Core, C#, Angular 8, SQL Server, REST APIs

• 🏅 Dr. Bruce Maxwell Award for Learner Service @ Northeastern
• 🏅 Star Employee @ ValueLabs
• 🥇 CVPR 2024 Paper Acceptance (Medical Imaging)
• 🧠 RISE 2024 Poster Presenter

M.S. in Data Science
Northeastern University, USA (2022–2024)

B.Tech in Computer Science
Jawaharlal Nehru Technological University, India

• Graduated with First Class Distinction

• 📘 Machine Learning Specialization by Andrew Ng
• 🤖 Deep Learning Specialization (CNNs, Sequence Models, Optimization)
• 🌐 Data Science Bootcamp (EDA, Regression, Time Series)
• 🛠️ Deploying ML Systems with FastAPI & Docker

Programming: Python, C#, SQL, JavaScript, Bash
Frameworks: PyTorch, scikit-learn, Transformers, OpenCV
DevOps: Docker, GitHub Actions, Azure, FastAPI, Streamlit
ML Techniques: LLMs, YOLO, CNN, RNN, PCA, SHAP, Clustering
Data Viz: Power BI, Matplotlib, Plotly
Databases: PostgreSQL, Qdrant, SQL Server, HealthKit
Other Tools: Langchain, LlamaIndex, FFMPEG, Postman

• 🎓 Graduate Teaching Assistant @ Northeastern (AI & Data Science courses)
• 🌱 Career Peer Advisor – mentoring 100+ students in resumes, portfolios & interview prep
• 🌟 Founder & President of Namaste – Indian cultural org at Northeastern
• 🤝 Graduate Ambassador @ Khoury College of Computer Sciences

• Cancer Cell Segmentation Using Deep CNNs – CVPR 2024 (U-Net, ResNet)
• Seizure Prediction with Brain Graphs – RISE 2024 (Clustering, Network Theory)

• 🔗 Portfolio Website
• 💼 LinkedIn
• 📩 Email: meghchillara@gmail.com
• 📄 CVPR Publication

AI for me is not just code — it’s a medium of impact. My goal is to continue building systems that help humans do better, live safer, and learn faster. If you’re building at this intersection too, let’s connect!

"Build for good. Deploy with care. Iterate with impact."