Swapnil Sinha Email & Phone Number

San Francisco, CA, US

San Diego, California, United States

• Developing a real-time telephony system with personal AI using FastAPI, integrating NVIDIA Riva for speech-to-text and text-to-speech conversion.

San Diego, California, United States

Led the quantization of LLaMA3 and Personal Language Conversational AI Models using Qualcomm AI Stack and AIMET, preserving model accuracy for On-Device AI inference.Created an integration C++ API for the loading and execution of quantized LLM model binaries, for inference on Windows and Android edge devices.Integrated with FastAPI by creating a Python.

San Diego, California, United States

• Data Science/Machine Learning Platform (DSMLP)
• Update MTL-Attendance for student attendance tracking at UCSD, utilizing Python, AWS Lambda, S3, and Terraform.
• Redesigned the Cluster and Pods Status dashboard using React.js, enhancing real-time monitoring of GPU and CPU resources, resulting in a 25% reduction in troubleshooting time.
• Developed Airflow DAGs to fetch enrollment data, and manage user drops and adds, enhancing class roster management for over 150 courses.
• Enhanced Canvas middleware integration with course management systems by implementing CI/CD regression testing pipelines, resulting in 3% faster enrollment processing and improved deployment stability.
• Worked on spinning up Jupyter Notebook environment with GPU support on AWS EKS containerizing JupyterHub instance using Docker and Kubernetes, enabling the on-demand creation of Jupyter instances.

San Diego, California, United States

• Released an LLM-based Retrieval-Augmented Generation (RAG) medical chatbot, leveraging Langchain and LlamaIndex, enabling faster and more efficient access to data and information from medical publications for.
• Fine-tuned the Llama3-8B model using LoRA resulting in a 15% increase in response accuracy improving the chatbot’s ability to provide precise medical information.

Trivandrum, Kerala, India

• Collaborated with the E-commerce service team to develop backend microservices using Python, Django, and Flask, directly contributing to an annual revenue increase of $500k.
• Implemented a Customer onboarding microservice that led to a 20% increase in user registrations in Q1 2023. Enhanced user engagement through personalized onboarding experiences.
• Developed an inventory management microservice incorporating real-time updates via Kafka, Lambda, and EventBridge, reducing inventory sync lag by 30% and minimizing stock discrepancies.
• Created a delivery tracking microservice with Google Maps integration, which decreased delivery time delays by 8%.
• Wrote SQL queries in PostgreSQL for supporting business operations including inventory management, and sales analytics
• Built a Backend For Frontend (BFF) service using Node.js, which reduced API response times by 20% increasing the scalability of front-end applications.

Pune, Maharashtra, India

• Co-authored published two papers on the topics
• A Neural Network Model to Predict the Radiation Resistance of Dipole Antenna. (https://ieeexplore.ieee.org/document/9847856)
• A Neural Network Model for Effective Dielectric Constant Prediction of a Two-Layered Microstrip TransmissionLine (https://ieeexplore.ieee.org/document/9848322)
• Developed Deep Learning solutions for antenna and transmission line design challenges.
• Calculated the ideal values for the parameters using Python, TensorFlow, PyTorch, Keras, and TensorFlow.js

Worked under the project, Melioration of IEEE802.15.4 wireless communication standard under avionics department in VSSC

Master Of Science - Ms, Machine Learning And Data Science

Fall 23 CSE 258 Recommender System & Web Mining ECE 143 Programming for Data Analysis ECE 271A Statistical Learning I WI 24 ECE 269 Linear.

Bachelor Of Technology - Btech (Honours), Electronics And Communications Engineering, 9.43

Activities and Societies: Chairman IEEE Antennas and Propagation Society IEEE Microwave Theory and Technology Society Link Rep IEEE.