ModelMatrix
Unified benchmarking framework for comparing Tabular Foundation Models, GBDT models, and ensemble learning architectures using statistical evaluation and interactive analytics.
Computer Science student at RIT with a strong foundation in Java and full-stack development. I enjoy building scalable digital solutions — from web platforms to network simulations — where clean code meets real-world impact.
Computer Science Engineering student at Ramaiah Institute of Technology passionate about software engineering, distributed systems, and emerging technologies. Experienced in developing full-stack applications, blockchain-based solutions, and machine learning platforms, with a strong interest in designing scalable, efficient, and impactful systems that solve real-world problems.
B.E, Computer Science and Engineering
CGPA: 9.25
Sept 2023 - July 2027
Samsung Research & Development Institute, Bangalore
Distributed Inference on Edge Devices
A research-driven project focused on reducing inference latency by distributing deep neural network workloads across heterogeneous edge devices. The system explores model partitioning, workload scheduling, and efficient communication strategies to enable faster, scalable, and cloud-independent AI inference at the network edge.
Unified benchmarking framework for comparing Tabular Foundation Models, GBDT models, and ensemble learning architectures using statistical evaluation and interactive analytics.
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I'm always open to new opportunities and collaborations.