👋
Hi, I'm Anurag Maravi
A dedicated Software Engineer passionate about creating scalable, impactful solutions that bridge the gap between design and development. From building seamless web applications to optimizing complex systems, I thrive on transforming innovative ideas into meaningful results. Always exploring the cutting edge of technology to craft solutions that make a difference.
About Me
Summary
Passionate and results-oriented software engineer with a strong foundation in building scalable systems and intuitive tools. Skilled in full-stack development, distributed systems, and data-driven applications. Excited to contribute to challenging projects that drive innovation and enhance user experiences.
Education
University of Southern California, Los Angeles | Dec 2024
Masters in Computer Science
Key Courses: Analysis of Algorithms, Web Technologies, Machine Learning for Data Science, Database Systems, Applied Natural Language Processing
Carnegie Mellon University, Pittsburgh | Dec 2018
Exchange Vistor Student
Pursued advanced research as part of an academic exchange program
SRM Institute of Science and Technology, Chennai | Dec 2018
Bachelor of Technology in Computer Science
Key Courses: Operating Systems, Computer Networks, Database Management Systems, Software Engineering
Work Experience
Software Engineer Intern | May 2024 - Dec 2024
Data Prisms
- Led development of scalable Figma plugins for automated design exports and detached instance detection, reducing manual tracking by 30% and collaborating with designers and developers to enhance workflows (React, TypeScript, Webpack).
- Built a real-time pet feeder monitoring app with remote access, automated scheduling, and portion control capabilities, supporting optimized feeding routines for revamped user experience (Flutter, WebSocket, OpenAPI, FastAPI).
Research Software Engineer | Jul 2018 - Dec 2022
Carnegie Mellon University
- Spearheaded distributed IoT systems across 314 devices in a 90,000 sq ft smart building, enabling real-time data collection and machine learning inferences for activity monitoring with a scalable, high-reliability design (Python, Large-Scale System).
- Designed real-time apps for room occupancy, kitchen usage, noise levels, and vacuum activity, cutting down facility response time by 30% with sensor data from a university building housing 400+ offices and labs (Vue.js, RabbitMQ, Data Visualization).
- Optimized end-to-end system resources, implementing fault tolerance and lazy training of models, slashing CPU usage by 55% while preserving memory efficiency in large-scale IoT applications (Python, gRPC, System Optimization).
Software Engineering Contractor | Jan 2017 - Dec 2017
BlueBanyan Technologies Pvt. Ltd
- Delivered web and Android apps for a real-time truck tracking system for Lafarge, integrating advanced data visualization and fleet tracking features, working closely with logistics teams to boost operational efficiency by 25% (Java, Real-Time System)
My Skills
Full-Stack Web Development
Extensive experience building dynamic, scalable, and intuitive web applications.
Backend Development
Proficient in building robust backend services, APIs, and real-time systems.
Android Development
Experienced in creating dynamic and user-friendly Android applications.
UI/UX Design
Skilled in crafting intuitive designs for web and mobile applications.
DevOps & Cloud
Experience with deploying and managing applications on cloud and containerized environments.
Real-Time Systems & IoT
Built and optimized IoT systems for smart buildings and activity monitoring.
Testing & Automation
Well-versed in testing frameworks and ensuring high-quality, maintainable code.
Projects
5 projects
StockSearch - Real-Time Stock Analysis Platform
February 14, 2024
Created a full-stack real-time stock analysis platform with data visualization, stock trend insights, buy/sell simulation, and financial recommendations, improving user decision-making.
QuantumGPT - Data-Efficient LLM Augmentation Platform
January 10, 2024
Developed a platform to enhance GPT-4 for scientific applications, mitigating hallucinations and logic errors, and improving large language model accuracy in complex quantum physics tasks.
IdiotBox
August 19, 2023
MLIoT - Adaptive Machine Learning System for IoT
August 19, 2023
Built an adaptive machine learning system tailored for IoT applications, reducing prediction latency to 30 milliseconds and achieving 75% accuracy in real-time human activity recognition for smart buildings.
Mites - Scalable IoT System for Smart Buildings
March 28, 2023
Developed a scalable IoT sensing system for smart buildings, achieving a 94% packet delivery rate across 314 deployed devices, enhancing real-time applications in building management and occupant wellness.
Publications
3 papers
Context Matters: Data-Efficient Augmentation of Large Language Models for Scientific Applications
arXiv preprint
Dec 2023
This paper investigates challenges in enhancing the accuracy and reliability of large language models (LLMs) for scientific applications. It highlights issues such as hallucinations and logical errors in LLM outputs and explores methods to improve their performance. The paper demonstrates the importance of context relevance and introduces techniques to self-examine and improve LLM outputs.
View PaperMites: Design and Deployment of a General-Purpose Sensing Infrastructure for Buildings
Proceedings of the ACM on Interactive, Mobile, Wearable, and Ubiquitous Technologies (IMWUT), ACM
Mar 2023
This paper presents the Mites system, a scalable hardware-software loT platform for deploying high-fidelity, general-purpose sensing in buildings. It addresses the challenges of scalability, privacy, and security, demonstrating the extensibility of the system through real-world deployment in a university building and proof-of-concept loT applications.
View PaperMLIoT: An End-to-End Machine Learning System for the Internet-of-Things
Proceedings of the International Conference on Internet-of-Things Design and Implementation (IoTDI '21), ACM
Apr 2021
This paper introduces MLoT, a machine learning system optimized for diverse loT applications. It enables adaptive training, optimization, and serving of models tailored to the unique requirements of loT environments. The system supports the entire lifecycle of loT applications, ensuring scalability, accuracy, and performance while addressing environmental and resource constraints.
View PaperAwards
2 papers
Distinguished Paper Award (IMWUT Vol. 7)
The Association for Computing Machinery (ACM)
Oct 2024
The paper "Mites: Design and Deployment of a General-Purpose Sensing Infrastructure for Buildings" was selected as one of the winners of the IMWUT Vol. 7 Distinguished Paper Awards. This recognition highlights the paper's exemplary contribution to ubiquitous computing research, particularly for its innovative design, deployment, and evaluation of a scalable loT sensing system for smart buildings. The award was selected by a committee of 16 distinguished members from the IMWUT Editorial Board and community, from a pool of 205 papers published in IMWUT Vol. 7.
The Most Complete App Award (Hasura)
Freshdesk
May 2017
Won the "Most Complete App" award at the 48-hour hackathon "Save the Hacker," conducted by Freshdesk in Chennai, sponsored by Hasura. Developed an Android application named "Kisaan," which provides a platform for farmers to sell their products directly to customers. This achievement was recognized for its innovative use of Hasura services and impactful solution for bridging the gap between farmers and customers.
Biography
1995
Born in Bhilai, Chhattisgarh—a serene steel plant city that fostered a love for problem-solving among a diverse community of engineers.
2013
Moved to Kota, Rajasthan, to prepare for engineering entrance exams and discovered my passion for computer science during late-night coding sessions.
2014
Started my journey at SRM University, Chennai, where I developed Android apps, led a tech club, and built a foundation in computer science and software development.
2018
Selected for an exchange program at Carnegie Mellon University, joining an elite cohort of two students among 800+ applicants, diving into cutting-edge IoT research.
2019
Continued my research at CMU post-graduation, transforming a 90,000 sq. ft. building into a smart hub with real-time sensors and groundbreaking IoT systems.
2023
Moved to Los Angeles for a Master’s degree at USC, embracing the sunny weather while preparing to bring my skills to the forefront of the tech industry.
2025
Aspire to join a team of innovators developing cutting-edge technology and contributing to meaningful, transformative projects as a Software Engineer.
Let's Connect
Feel free to contact me if you have any questions or just want to say hi!
