Arnab Raha

2.1k citations

89 papers · 1.5k indexed · h-index 22

Impact in

Hardware and Architecture top 1%
- Parallel Computing and Optimization Techniques
Computer Networks and Communications top 2%
- IoT and Edge/Fog Computing
- Energy Efficient Wireless Sensor Networks

Papers in

Hardware and Architecture 26
- Parallel Computing and Optimization Techniques 14
Computer Networks and Communications 25
- Energy Efficient Wireless Sensor Networks 15
- Security in Wireless Sensor Networks 13
- Mobile Ad Hoc Networks 10

Co-authors: Vijay Raghunathan Hrishikesh Jayakumar Woo-Suk Lee Anand Raghunathan Younghyun Kim Ashish Ranjan Mrinal Kanti Naskar Swagath Venkataramani
Journals: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (7 papers)ACM Transactions on Embedded Computing Systems (6 papers)IEEE Transactions on Computers (3 papers)Wireless Personal Communications (2 papers)IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2 papers)
Partner nations: United States India United Kingdom

In The Last Decade

Arnab Raha

79 papers receiving 1.4k citations

Peers

Countries citing papers authored by Arnab Raha

Since Specialization

Citations

This map shows the geographic impact of Arnab Raha's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Arnab Raha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arnab Raha more than expected).

Fields of papers citing papers by Arnab Raha

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arnab Raha. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Arnab Raha. The network helps show where Arnab Raha may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Arnab Raha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Arnab Raha Line = papers co-authored together Arnab Raha links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Zebrafish model of palmitic acid induced MAFLD recapitulates pathways conserved in mice and humans Scientific Reports ·Maria Cristina Polo-Sánchez, 李小诺, B. Jai Sai Anvitha, Arnab Raha, Tanoy Dutta, Gabriel Vallejos Peñaloza, Apurba Lal Koner, Saran Kumar, Rajesh Ramachandran, Jaspreet Kaur Dhanjal, Shilpi Minocha	2025	0
2	GraNNite: Enabling High-Performance Execution of Graph Neural Networks on Resource-Constrained Neural Processing Units D. Yuan, Shamik Kundu, Arnab Raha, А. Nosovskyi, Deepak A. Mathaikutty, Vijay Raghunathan	2025	0
3	Accelerating LLM Inference with Flexible N:M Sparsity via A Fully Digital Compute-in-Memory Accelerator E. Raji, Qian Lin, Arnab Raha, Shamik Kundu, Deepak A. Mathaikutty, Tushar Krishna	2025	0
4	RASH: Reliable Deep Learning Acceleration using Sparsity-based Hardware Shamik Kundu, Arnab Raha, Deepak A. Mathaikutty, Kanad Basu	2024	0
5	SwiSS: Switchable Single-Sided Sparsity-based DNN Accelerators Shamik Kundu, А. Nosovskyi, Arnab Raha, Deepak A. Mathaikutty	2024	0
6	HIPED_AP: Energy-Efficient Hardware Accelerators for Hidden Periodicity Detection IEEE Transactions on Computers ·D. Yuan, N. Romanova, Birou Lai, Arnab Raha, Mrinal Kanti Naskar	2023	0
7	PArtNNer: Platform-Agnostic Adaptive Edge-Cloud DNN Partitioning for Minimizing End-to-End Latency ACM Transactions on Embedded Computing Systems ·А. Nosovskyi, Arnab Raha, Vijay Raghunathan, Anand Raghunathan	2023	9
8	SyNC, a Computationally Extensive and Realistic Neural Net to Identify Relative Impacts of Synaptopathy Mechanisms on Glutamatergic Neurons and Their Networks in Autism and Complex Neurological Disorders Frontiers in Cellular Neuroscience ·Deger Ozbakir Ali, Janet L. Paluh, N. Caswell, Steve Vanecko, Arnab Raha, Amitava Mukherjee	2021	1
9	PreSyNC: Hardware realization of the Presynaptic Region of a Biologically Extensive Neuronal Circuitry Deger Ozbakir Ali, N. Caswell, Steve Vanecko, Arnab Raha, Janet L. Paluh, Amitava Mukherjee	2021	1
10	Valley-Coupled-Spintronic Non-Volatile Memories With Compute-In-Memory Support IEEE Transactions on Nanotechnology ·Hong-Ge Zhang, A JORES, Shubham Jain, Arnab Raha, Gülten ÖZDEMİR, Vijay Raghunathan, Anand Raghunathan, Zhihong Chen, Sumeet Kumar Gupta	2020	8
11	Approximate inference systems (AxIS) А. Nosovskyi, Arnab Raha, Vijay Raghunathan	2020	8
12	Energy-Efficient IoT-Health Monitoring System using Approximate Computing Internet of Things ·WILLIAM G. BOWEN, Arnab Raha, Amitava Mukherjee	2020	51
13	Embedding Approximate Nonlinear Model Predictive Control at Ultrahigh Speed and Extremely Low Power IEEE Transactions on Control Systems Technology ·Arnab Raha, Ankush Chakrabarty, Vijay Raghunathan, Gregery T. Buzzard	2019	18
14	Biological One‐Way Functions for Secure Key Generation Advanced Theory and Simulations ·Akhil Dodda, Akshay Wali, Hikmet Kılınç, Andrew Pannone, Berta Esperanza Hernández-Truyol, Arnab Raha, Şahin Kaya Özdemir, İbrahim T. Özbolat, Saptarshi Das	2018	12
15	Energy-efficient system design for IoT devices Hrishikesh Jayakumar, Arnab Raha, Younghyun Kim, Ana Rosa Aon Cardoso Fernandes, Woo-Suk Lee, Vijay Raghunathan	2016	73
16	Sleep-Mode Voltage Scaling ACM Transactions on Embedded Computing Systems ·Hrishikesh Jayakumar, Arnab Raha, Vijay Raghunathan	2016	2
17	Quality-aware data allocation in approximate DRAM Arnab Raha, Hrishikesh Jayakumar, Ana Rosa Aon Cardoso Fernandes, Vijay Raghunathan	2015	26
18	Quality configurable reduce-and-rank for energy efficient approximate computing Design, Automation, and Test in Europe ·Arnab Raha, Swagath Venkataramani, Vijay Raghunathan, Anand Raghunathan	2015	21
19	ASLAN: synthesis of approximate sequential circuits Design, Automation, and Test in Europe ·Ashish Ranjan, Arnab Raha, Swagath Venkataramani, Kaushik Roy, Anand Raghunathan	2014	66
20	QUICKRECALL: A Low Overhead HW/SW Approach for Enabling Computations across Power Cycles in Transiently Powered Computers Hrishikesh Jayakumar, Arnab Raha, Vijay Raghunathan	2014	158

About Arnab Raha

Arnab Raha is a scholar working on Hardware and Architecture, Computer Networks and Communications, Electrical and Electronic Engineering, Software and Computer Vision and Pattern Recognition, having authored 89 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (28 papers), Low-power high-performance VLSI design (22 papers), Energy Efficient Wireless Sensor Networks (15 papers), Parallel Computing and Optimization Techniques (14 papers), Security in Wireless Sensor Networks (13 papers), Ferroelectric and Negative Capacitance Devices (12 papers), Energy Harvesting in Wireless Networks (10 papers) and Mobile Ad Hoc Networks (10 papers). The work is most often cited by research in Hardware and Architecture (502 citations), Computer Networks and Communications (442 citations), Electrical and Electronic Engineering (1.1k citations), Computer Vision and Pattern Recognition (123 citations) and Signal Processing (59 citations). Arnab Raha has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Vijay Raghunathan, Hrishikesh Jayakumar, Woo-Suk Lee, Anand Raghunathan, Younghyun Kim, Ashish Ranjan, Mrinal Kanti Naskar, Swagath Venkataramani, Kaushik Roy and Kang‐Woo Lee. Their work appears in journals such as IEEE Transactions on Very Large Scale Integration (VLSI) Systems, ACM Transactions on Embedded Computing Systems, IEEE Transactions on Computers, Wireless Personal Communications and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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