Hi, I'm
Nithin Manne
Software Engineer
Building scalable systems, AI-powered solutions & innovative products
About Me
Software Engineer with expertise in distributed systems, cloud infrastructure, AI/ML applications, and full-stack development. Currently building EV charging infrastructure at Argonne National Laboratory. Previously at Amazon (AWS S3) and Qualcomm. Published researcher with a Best Paper Award. MS in Computer Science from University of Chicago.
Experience
A journey through building innovative solutions at leading tech organizations and research centers
Software Engineer (RD2)
Argonne National Laboratory • Illinois
- •Developed an end-to-end EV charger reservation system with PHP Laravel backend, iOS and Android apps, handling 30k+ reservations over 2.5 years
- •Migrated backend to Docker containers on AWS ECS using AWS CDK, enabling zero-downtime deployments with CI/CD and reducing costs by 25%
- •Built message queue using Kafka and Redis caching on ElastiCache, reducing notification delay from 60s to 1s
- •Designed an LLM-powered agent using Google Gemini for automated support ticket handling and data analysis
Software Development Engineer
Amazon • Illinois
- •Built a distributed analytics engine using Java to optimize AWS S3 storage and compute fleet procurement globally, saving 8+ hours of engineering time weekly
- •Designed a React UI to monitor S3 network fleet status, cutting leadership review time by 90%
- •Developed large-scale automated system to deploy configurations to production
Software Engineer
Argonne National Laboratory • Illinois
- •Created a scheduler handling 2x vehicles under fixed power limits using Golang with RESTful API
- •Developed charging station management system with Java Spring Boot and Vue.js TypeScript UI
- •Built analytics dashboard using Python Dash for charger placement and capacity planning
- •Developed power management driver in C++ for EV charging adapter
Software Intern (Systems)
DePaul University • Illinois
- •Designed system in C to checkpoint process state in Linux for reusing high time-complexity computations
- •Published algorithm using Python Pyomo for multiversion notebook replay, reducing execution time by 80%
- •Built C application to capture input files via syscall tracing for reproducible program execution
Software Engineer
Qualcomm • India
- •Developed device drivers for peripheral buses in C for Snapdragon chipsets
- •Created Python automation scripts, saving 2+ hours per change
- •Ported Snapdragon drivers to Windows on ARM, earning Qualstar award
- •Managed all peripheral bus issues on Windows ARM platform
Software Intern (ML)
Qualcomm • India
- •Led team of 8 interns to build sign-language recognition glove with 75% accuracy
- •Built ML model for test-case failure prediction using scikit-learn
- •Created NLP model using NLTK to classify failures from logs, reducing debug time by 10%
Technical Skills
Technologies and tools I work with daily to build scalable solutions
Languages
Frameworks
Platforms
AI/ML & Data
Databases
Education
Academic background and qualifications
MS in Computer Science (Specialization in Data Analytics)
University of Chicago
Dec 2020
B Tech (Honors) in Electrical Engineering
Indian Institute of Technology (IIT) Kharagpur
May 2018
Featured Projects
Open-source contributions and research projects that showcase my work
Rezzy: AI Support Agent
LLM-powered agent for EV charger reservation app that triages tickets and automates common support actions
- →Developed internal Streamlit UI for SQL and analysis code generation from natural language
- →Led team of 4 grad students from UChicago DSI
Gesture Recognition System
Glove that translates American Sign Language subset to speech in real-time
- →On-device neural network with flex sensors and IMU data
- →Achieved ~75% accuracy on limited ASL subset
Network Attacks with GANs
Research on GAN effectiveness against ML-based Intrusion Detection Systems
- →Generated synthetic data circumventing detection with 30% success rate
Publications
Research contributions to distributed systems, reproducibility, and EV charging
V1G Frequency Regulation: Algorithm Development, Validation & Analysis at Scale
39th Electric Vehicle Symposium & Exhibition (EVS39), 2026
Nithin Manne, Jason Harper
Accepted, to appear 2026Managing Workplace Charging: Argonne National Laboratory's Reservation-Based Smart EV Charging Platform
White Paper, SEPA, 2026
Brittany Blair, Janne Knieke, Garrett Fitzgerald, Nithin Manne, Jason Harper
Improving reproducibility of interactive notebooks using application virtualization
Future Generation Computer Systems, Volume 175, 2025
Raza Ahmad, Naga Nithin Manne, Tanu Malik
CHEX: Multiversion Replay with Ordered Checkpoints
48th International Conference on Very Large Data Bases (VLDB), 2022
Naga Nithin Manne, Shilvi Satpati, Tanu Malik, Amitabha Bagchi, Ashish Gehani, Amitabh Chaudhary
A Cloud-Based Simulation and Testing Framework for Large-Scale EV Charging Energy Management
WCX SAE World Congress Experience, 2022
Zhouquan Wu, Naga Nithin Manne, Jason Harper, Bo Chen, Daniel Dobrzynski
Reproducible Notebook Containers using Application Virtualization
18th IEEE International Conference on eScience, 2022
Raza Ahmad, Naga Nithin Manne, Tanu Malik
PROV-CRT: Provenance Support for Container Runtimes
12th International Workshop on Theory and Practice of Provenance (TaPP), 2020
Raza Ahmad, Yuta Nakamura, Naga Nithin Manne, Tanu Malik
An Experimental Study of C-RAN Fronthaul Workload Characteristics
2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring)
Venu Balaji Vinnakota, Naganithin Manne, Abhijit Mondal, Debarati Sen, Sandip Chakraborty
Accomplishments
Notable achievements and certifications
Ranked 842 (top 0.1%) out of 1.3 million applicants in IIT JEE
Rated "Exceeds Expectations" (5/5) in 2025 annual appraisals
Contributed to open-source: Pandas, Linux Foundation Energy's EVerest
Built and operate home lab with OPNsense on Proxmox for 5+ years
FAA Certified Remote Pilot (14 CFR Part 107)
Qualstar Award for fast Windows ARM driver bring-up
Get in Touch
Have a question or want to work together? I'd love to hear from you.