Arghadip Das
Computer Science · Purdue University West Lafayette
Publications
24
Citations
70
Est. group size
~1
Recurring co-author estimate
Active years
30
Publishing since 1997
Arghadip Das works on designing energy-efficient computer hardware for processing signals and running machine learning models, especially for small, low-power devices used at the 'edge' (away from large data centers). This includes building specialized chips and accelerators for tasks like detecting patterns in signals, tracking moving objects, and running neural networks faster while using less electricity.
Publication output was minimal or absent for most of the past decade but has grown sharply in 2025 and 2026, suggesting a recent surge in research activity.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- RamForm: A Ramanujan Wavelet Transform-Based Accelerator for Energy-Efficient Signal Processing
2026
- A Scalable Parallel Architecture for Fast Walsh Hadamard Transform
Circuits Systems and Signal Processing · 2026
- KATANA: A Fast, Low-Power Mapping of Kalman Filters onto Edge NPUs for Real-Time Tracking
arXiv (Cornell University) · 2026
- KATANA: A Fast, Low-Power Mapping of Kalman Filters onto Edge NPUs for Real-Time Tracking
arXiv (Cornell University) · 2026
- LLM-NPU: Towards Efficient Foundation Model Inference on Low-Power Neural Processing Units
2025
- F-25 | Comparative Analysis of Machine Learning Algorithms for Predicting Coronary Artery Disease Across Diverse Populations
Journal of the Society for Cardiovascular Angiography & Interventions · 2025
- Demo Abstract: A Low-Power Real-Time Hardware Accelerator for Edge Detection Using Stochastic Computing
2025
- SparseDroop: Hardware–Software Co-Design for Mitigating Voltage Droop in DNN Accelerators
Journal of Low Power Electronics and Applications · 2025
- HIPED<sub>AP</sub>: Energy-Efficient Hardware Accelerators for Hidden Periodicity Detection
IEEE Transactions on Computers · 2023
- HIPER: Low Power, High Performance and Area-Efficient Hardware Accelerators for Hidden Periodicity Detection using Ramanujan Filter Banks
2021
- An Efficient Multiplier-less Hardware for Hidden Periodicity Detection Using Ramanujan Filter Bank
2020
- arXiv (Cornell University)×8
- IEEE Internet of Things Journal×1
- IEEE Transactions on Computers×1
- IEEE Embedded Systems Letters×1
- Journal of the Society for Cardiovascular Angiography & Interventions×1
- Qi Guo
Computer Science · Purdue University West Lafayette
- Surya Selvam
Computer Science · Purdue University West Lafayette
- Cheng Chu
Computer Science · Indiana University
- Isha Garg
Computer Science · Purdue University West Lafayette
- Xuwei Tan
Computer Science · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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