About Me
As a Software Engineer at Meta Platforms, I specialize in the architecture and optimization of distributed systems, databases, and large-scale AI infrastructure. My work is centered on resolving the critical trade-offs between planetary-scale data delivery and system reliability, with a specific focus on the rigorous demands of modern artificial intelligence systems.
My professional experience at Meta, complemented by a Master of Science in Computer Science (4.0 GPA) from Arizona State University, provides me with a unique synthesis of practical engineering expertise and a strong theoretical foundation. Through my work on some of the world's largest systems, I have identified a recurring challenge: critical failures often arise not from algorithmic deficiencies, but from a lack of formal methods in system design, where data provenance and lineage are not treated as first-class citizens. This insight drives my research and engineering philosophy.
Primary Research Interests
- Trustworthy AI Data Infrastructure: Engineering robust systems where data lineage and formal provenance are integral to the architecture, ensuring verifiability and reliability for AI/ML workloads.
- Next-Generation Data Engines: Designing and implementing novel data processing engines that bridge the performance gap between conventional batch processing and real-time streaming, tailored for the unique demands of AI applications.
- Intelligent Resource Management for AI Data Centers: Developing formalized methodologies for resource allocation and scheduling to optimize for cost, energy efficiency, and performance in large-scale AI training and inference environments.
Research Experience
Formal AI Data Provenance Platform
2024 - 2025Meta Platforms
- Built a GraphSQL provenance fabric that captures stage-level lineage for 2,300+ AI pipelines with sub-5 minute freshness, enabling audit-ready replay of every dataset version.
- Codified dependency proofs using TLA+-backed model checking, shrinking SEV root-cause analysis from multi-day war rooms to < 3 hours and eliminating 60% of false-positive alerts.
- Launched schema-integrity guardrails and automated rollback triggers that reduced training data regressions by 35% and preserved 11 PB of clean feature history.
Graph-Powered Public Health Analytics
2020 - 2021Madras Institute of Technology
- Designed multi-layer graph heuristics that fused Bluetooth, GPS, and transit feeds, improving exposure-detection recall by 22% while holding precision above 90% in city-wide pilots.
- Trained CNN + temporal attention models that segmented mobility routines with 91% F1 accuracy, providing public health teams actionable micro-cluster alerts within 12 minutes of ingestion.
- Formulated an adaptive handset sampling policy that reduced radio wakeups by 38%, extending device battery life by 18% without sacrificing infection notification latency.
Autonomous Multi-UAV Coordination
2019 - 2020Madras Institute of Technology
- Authored an O(n) cooperative velocity-obstacle planner that coordinated 40+ UAVs at 30 Hz, maintaining guaranteed separation envelopes even under GPS drift.
- Implemented a ROS/Gazebo swarm test harness with high-fidelity aerodynamic perturbations, cutting field-readiness cycles from six weeks to two by simulating 1,200 sorties per night.
- Encoded airspace safety contracts with temporal logic, eliminating boundary violations across 500+ autonomous missions and satisfying DGCA flight certification checks.
Professional Experience
Software Engineer
October 2023 - PresentMeta Platforms
New York City, NY
Software Engineer
August 2023 - September 2023Zenfra, Virtual Tech Gurus
Irving, TX
Software Engineer Intern
January 2023 - May 2023Tesla Inc
Fremont, CA
Software Engineer Intern
May 2022 - August 2022Meta Platforms
Menlo Park, CA
Software Engineer Intern
March 2021 - June 2021Zoho Corporation
Chennai, India
Software Engineer Intern
June 2020 - August 2020Tesark Technologies
Chennai, India
Academic Journey
Master of Science in Computer Science
August 2021 - May 2023Arizona State University
Tempe, AZ
GPA: 4.0/4.0 (Gold Medalist)
- Research focus: Distributed Systems, AI Infrastructure, Data Management
- Teaching Assistant for CSE 573: Semantic Web Mining
Bachelor of Engineering in Computer Science
August 2017 - May 2021Madras Institute of Technology, Anna University
Chennai, India
- Research in UAV collision avoidance and contact tracing systems
- Teaching Assistant for Data Structures and Algorithms I & II
Teaching Experience
Instructor - Fundamentals of Coding & Algorithms Cohort
Arizona State University
Mentored students from first-generation and career-transitioning backgrounds through weekday sessions, providing targeted support in Python and data structures to deepen their understanding of foundational academic principles.
Teaching Assistant - CSE 573: Semantic Web Mining
Arizona State University
Assisted in course delivery, grading, and student mentoring for graduate-level semantic web mining course.
Teaching Assistant - Data Structures and Algorithms I & II
Madras Institute of Technology, Anna University
Led programming labs and tutorials for undergraduate students, covering fundamental algorithms and data structures.
Technical Skills
Programming
Python, Hack, PHP, C++, Java, MySQL, Oracle Database, PostgreSQL, MSSQL, HTML, CSS, Angular JS, React JS, ETL
Tools & Technologies
Keras, PyTorch, Tensorflow, Pandas, NumPy, SciPy, OpenCV, Scikit-Learn, Matplotlib, Apache Spark, Hive, Airflow, Presto, Xcode, Tableau, Jenkins, AWS S3, D3 JS, Docker