Machine Learning Artificial Intelligence

TRIVED KATRAGADDA

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EDUCATION

Master of Science in Artificial Intelligence, Boston University (GRS), Boston, MA Sep 2022 - Jan 2024 Coursework: Artificial Intelligence, Deep Learning, Principles of Machine Learning, Image and Video Computing Bachelor of Technology in Computer Science, SRM University, AP, India Jun 2018 - May 2022 Coursework: Data Structures and Algorithms, Image Processing, Natural Language Processing TECHNICAL SKILLS

Languages: Python, SQL, R, Java, C, C++, HTML, JavaScript Libraries: Pandas, Numpy, PyTorch, Matplotlib, React.js, Scikit-Learn, TensorFlow, Keras, ggplot2 Tools: AWS, GCP, Azure, Redux Toolkit, Tableau, Docker, SSRS, Google Analytics Development Tools: GitHub, Git, Rasa, Hugging Face, Langchain, Langgraph, Poe, Azure DevOps, Jenkins, Conda, Vertex AI Key Skills: GEN AI, Multi Agent systems, RAG, CI/CD, Distributed computing, Reinforcement Learning, Predictive Modeling, Deep Learning, Neural Networks, Containerization, Object Detection, LLMs, MLOps, Test Design, Kubernetes, Visualization CERTIFICATIONS

AWS Certified Cloud Practitioner (CLF-C02) - Certificate AWS Certified Machine Learning - Specialty (MLS-C01) - Certificate SNOWFLAKE SnowPro Core Certification (COF-P02) - Certificate PROFESSIONAL EXPERIENCE

Machine Learning Engineer - Qcentrio Technologies LLC. Feb 2024 - Jun 2025

● Fine-tuned LLaMa-70B using Hugging Face PEFT and DeepSpeed Inference for distributed, memory efficient fine-tuning.

● Built a HybridRAG system (Milvus + Neo4j) via LangChain for contextual knowledge retrieval across agents.

● Integrated multi-modal context (text, graph) into Retrieval-Augmented Generation (RAG) pipelines, paving way for future video/audio integration.

● Developed a multi-agent chatbot handling complex queries through shared context and coordinated reasoning via LangGraph.

● Deployed distributed inference pipelines across GPUs with real-time human-in-the-loop feedback. AI/Machine Learning Intern - Cox Quality Solutions Pvt. Ltd. May 2021 - Jun 2022

● Developed an advanced CNN leveraging GPU (CUDA) for Prostate Cancer detection, achieving 98% accuracy.

● Conceived a comprehensive Tableau dashboard to deliver key insights such as recall score of 0.99.

● Engineered a new ETL process using Python scripts, resulting in an 18% reduction in operational costs.

● Led A/B testing and applied T-tests to test which ETL process was better and achieved a 95% statistical significance. Machine Learning Intern - Indian Servers Jun 2020 - Sep 2020

● Guided over 500 students in selecting masters university by using RoBERTa for feature extraction and XGBoost for predictions.

● Developed object detection systems through Mask R-CNN with an accuracy of over 95% on diverse proprietary datasets.

● Applied SSD frameworks to the model, reducing processing duration by 30%. RELEVANT PROJECTS

Damage Analysis Application Nov 2023 - Jan 2024

● Designed an end-to-end application for damage detection on any surface which will specify the type, severity and locations of the damage using custom fine-tuned YOLOv8 models for every requirement.

● Established a CI/CD pipeline, modified the configuration file and model definition script for each model according to its specific function and achieved a mAP score of 0.82.

● Trained the custom models using AWS SageMaker's distributed training toolkit to enable multi-GPU parallelism and employed HTML script for front-end and Flask for back-end application, hosting it on Amazon EC2 for handling high user traffic. Harvard ML Herbaria Jan 2023 - April 2023

● Digitized 130K+ historical specimens using TrOCR (95% accuracy) for climate research, collaborating with Harvard teams and using Git for scalable version control.

● Deployed a KerasOCR pipeline for text masking and built a custom image classifier, improving prior model accuracy by 13%.

● Fine-tuned a Swin Transformer for instance segmentation of buds, flowers, and fruits, achieving 85% precision, with strongest performance on fruit classification.

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