Hello, I'm
Sankalp Naik
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Passionate about intelligent systems, edge inference, and hardware‑aware ML. I love turning research into production—fast, reliable, and delightful.
Skills
On Device and Applied ML
Performance Critical Systems
Silicon Aware Computing
Infrastructure and Reliability
Experience & Education
Experience
Associate Applications Developer
2022 – 2025Infra team for a banking platform; owned performance-critical components.
Research Assistant
2025 - CurrentWork on Hardware and software codesign for processors.
Education
M.S. (Artificial Intelligence – ECE)
2025 – 2026Interests: Hardware-aware NAS, edge inference, systems for ML.
B.Tech (ECE)
2018 – 2022Top of class; coursework in Algorithms, Signals, VLSI, ML.
Research & Publications
ARMPC - ARIMA Based Model Predictive Control for Adaptive Bitrate in Streaming
Proposed an ARIMA-based (Auto Regressive Integrated Moving Average) technique, to substitute the Harmonic Mean predictive algorithm used in the original Model Predictive Control scheme to determine the best possible bitrate for the given network conditions. Mathematically demonstrated that the proposed model provides us with improvements in the prediction of optimal bitrate for given bandwidth and buffer capacity within computational constraints of practical implementation. Analyzed and compared various methods, including deep learning techniques, to improve adaptive bitrate schemes for improved Quality of Experience (QoE) in video streaming.
Youtube Universe of Comments: A Machine Learning Approach for Systematic Classification of YouTube Comments on Custom Prepared Dataset
Prepared a Custom dataset of Hinglish YouTube Comments by web scraping & designing a comprehensive annotation scheme, considering various dimensions such as sentiment, topic, toxicity, and engagement. Leveraged robust ML classification models and NLP techniques to accurately capture the sentiment of Hinglish comments and identify abusive comments. Introduced the concept of Gravity of comments which will act as a reward mechanism for comments based on the computed sentiment and help YouTube reorder the display order of comments.
Looking for Internship opportunities for Summer 2026!
Machine Learning Engineering roles focused on on-device inference, model optimization, and hardware-aware ML systems, where tight integration between algorithms, software, and silicon is critical.
Systems Engineering roles involving performance-critical software, accelerator/GPU optimization, and building reliable, scalable infrastructure that brings research ideas into production-quality systems.
Thank You!