Akhilesh Raj

Akhilesh Raj

I am a Ph.D. candidate at Vanderbilt University specializing in reinforcement learning and HPC optimization. My research focuses on advancing AI-driven solutions for energy-efficient computing and cyber-physical systems.

Posts by Collection

portfolio

publications

Vision based obstacle avoidance and recognition system

Published in IEEE, 2015

This paper proposes a vision-based obstacle avoidance and recognition system, presented at the “2015 IEEE Workshop on Computational Intelligence: Theories, Applications and Future Directions (WCI)”.

Recommended citation: Verma, N.K., Kumar, G., Siddhant, A., Nama, P., Raj, A., Mustafa, A., Dhar, N.K., & Salour, A. (2015). "Vision based obstacle avoidance and recognition system." 2015 IEEE Workshop on Computational Intelligence: Theories, Applications and Future Directions (WCI), 1-7.
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Vision based object follower automated guided vehicle using compressive tracking and stereo-vision

Published in IEEE, 2015

This paper presents a vision-based object follower automated guided vehicle using compressive tracking and stereo-vision, published at “2015 IEEE Bombay Section Symposium (IBSS)”.

Recommended citation: Verma, N.K., Nama, P., Kumar, G., Siddhant, A., Raj, A., Dhar, N.K., & Salour, A. (2015). "Vision based object follower automated guided vehicle using compressive tracking and stereo-vision." 2015 IEEE Bombay Section Symposium (IBSS), 1-6.
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Face detection and recognition based on skin segmentation and CNN

Published in IEEE, 2016

This paper presents a face detection and recognition system based on skin segmentation and CNN, published in the “2016 11th International Conference on Industrial and Information Systems (ICIIS)”.

Recommended citation: Raj, A., Gupta, S., & Verma, N.K. (2016). "Face detection and recognition based on skin segmentation and CNN." 2016 11th International Conference on Industrial and Information Systems (ICIIS), 54-59.
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Object tracking with movement prediction algorithms

Published in IEEE, 2016

This paper discusses object tracking with movement prediction algorithms, published at the “2016 11th International Conference on Industrial and Information Systems (ICIIS)”.

Recommended citation: Raj, A., Sivaraman, A., Bhowmick, C., & Verma, N.K. (2016). "Object tracking with movement prediction algorithms." 2016 11th International Conference on Industrial and Information Systems (ICIIS), 285-290.
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Event-triggered Adaptive Distributed State Estimation by Using Active-Passive Sensor Networks

Published in IEEE, 2019

This paper discusses event-triggered adaptive distributed state estimation using active-passive sensor networks, presented at the “2019 American Control Conference (ACC)”.

Recommended citation: Raj, A., Jagannathan, S., & Yucelen, T. (2019). "Event-triggered Adaptive Distributed State Estimation by Using Active-Passive Sensor Networks." 2019 American Control Conference (ACC), 4695-4700.
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Object detection and recognition using small labeled datasets

Published in Springer, 2019

This paper discusses object detection and recognition using small labeled datasets, published in “Computational Intelligence: Theories, Applications and Future Directions”.

Recommended citation: Raj, A., Gandhi, K., Nalla, B.T., & Verma, N.K. (2019). "Object detection and recognition using small labeled datasets." Computational Intelligence: Theories, Applications and Future Directions, 407-419.
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Distributed adaptive state estimation and tracking by using active-passive sensor networks

Published in Wiley Online Library, 2020

This paper presents an approach for distributed adaptive state estimation and tracking using active-passive sensor networks, published in “International Journal of Adaptive Control and Signal Processing”.

Recommended citation: Raj, A., Jagannathan, S., & Yucelen, T. (2020). "Distributed adaptive state estimation and tracking by using active-passive sensor networks." International Journal of Adaptive Control and Signal Processing, 34(3), 330-353.
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Distributed Adaptive State Estimation and Tracking Scheme for Nonlinear Systems using Active Passive Sensor Networks

Published in IEEE, 2020

This paper proposes a distributed adaptive state estimation and tracking scheme for nonlinear systems using active-passive sensor networks, published in “2020 American Control Conference (ACC)”.

Recommended citation: Raj, A., Jagannathan, S., & Yucelen, T. (2020). "Distributed Adaptive State Estimation and Tracking Scheme for Nonlinear Systems using Active Passive Sensor Networks." 2020 American Control Conference (ACC), 2587-2592.
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Application-Architecture Agnostic Efficiency Optimization using Reinforcement Learning

Published in Community Workshop on Practical Reproducibility in HPC, 2024

This paper introduces an application-architecture agnostic approach for efficiency optimization using reinforcement learning, presented at the Community Workshop on Practical Reproducibility in HPC 2024.

Recommended citation: Raj, A., Perarnau, S., & Gokhale, A. (2024). "Application-Architecture Agnostic Efficiency Optimization using Reinforcement Learning." Community Workshop on Practical Reproducibility in HPC.
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Reinforcement Learning-based Performance-aware Energy Management in 5G Base Stations

Published in IEEE, 2024

This paper focuses on reinforcement learning-based performance-aware energy management in 5G base stations, presented at COMSNETS 2024.

Recommended citation: Raj, A., Canady, R.E., Das, S., Gokhale, A., & Perarnau, S. (2024). "Reinforcement Learning-based Performance-aware Energy Management in 5G Base Stations." 2024 16th International Conference on Communication Systems & NETworkS (COMSNETS), 568-571.
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Charon: An End-to-End Infrastructure for Connecting AI@Edge to HPC

Published in ACM, 2025

This paper presents “Charon”, an end-to-end infrastructure for connecting AI at the edge to HPC, presented at IPDPS 2025.

Recommended citation: Kim, Y., Park, S., Perarnau, S., & Raj, A. (2025). "Charon: An End-to-End Infrastructure for Connecting AI@Edge to HPC." IPDPS, to be submitted.

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.