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Ph.D scholar with the Engineering Graduate Fellowship at Vanderbilt University.
A motivated researcher in the field of control of cyber physical systems and machine learning with hands on experience in problem solving - theory and application, using math and math-tools. The knowledge seeker and the team player in me helped gain experience in electronic assembly and Python coding.
Areas of Interest: Reinfrocement Learning, Control Systems, Distributed Estimation, Surrogate Modeling, Machine Learning.
Project: Composition of surrogate models.
Positons holding/ held: Advisory Board Member, Bayesian ways.LLP Lead Project Engineer, DropVault Tech. Pvt. Ltd.
Having pursued my research career as an M‑Tech graduate from IIT Kanpur, I gained experience and expertise in problem formulation, solving and experimenting using various software and hardware tools like LABview and ROS. My M.Tech thesis work was the development of an Automated Guided Vehicle (AGV), which I did at IDEA Lab (IIT‑Kanpur). The Boeing Company funded project demanded automation of their warehouse vehicles for material handling using a minimal number of sensors. Therefore the hardware was designed and developed at a minimal cost and the sensors for object detection, obstacle avoidance, line following, tracking,recognition etc. were replaced with a camera. The simulations were performed using MATLAB and the backend support was provided using python with the added library support from OpenCV and Arduino Uno.
Following my Master’s degree, my urge towards research studies pulled me to the Missouri University of Science and Technology, Missouri, USA, to work in the field of control theory. My research was in distributed state estimation with the objective of estimating the position and velocity of an unknown moving target in real time. The algorithm was developed using adaptive observers and neural networks, and mathematical proofs were provided to support the proposed theory. Similarly, the simulations were performed using MATLAB, and were shown supporting the proposed theory. The project was funded by the Intelligent System Center and Dynamic Data Driven Application of the Air Force office for Scientific Research, USA.
I have 9 publications in various international conferences and journals, which has over 35 citations. These first authored works span a wide range of research areas which include distributed estimation, control, machine learning, computer vision etc. I also have abook Chapter related to learning and estimation published from IIT Kanpur in Computational Intelligence: Theories, Applicationsand Future Directions ‑ Volume II.
Currently I am an Engineering Graduate Fellow at the Vanderbilt University, Nashville, Tennessee, USA in the department of Electrical and Computer Engineering, working towards my PhD. in the area on control of cyber‑physical systems
Role: W.J Cody Associate
Period: May 2022 - August 2022
ARGO node resource management: At Argonne National Lab I worked as a W.J Cody associate as a part of UChicago Argonne summer internship program. I was employed in the Argo Project under the department of Mathematics and Computer Science. During the internship I developed a novel power optimization algorithm for high performance computers (HPCs) using a reinforcement learning approach leveraging the capabilities of Intel Running Average Power Limit (RAPL) technology. Power consumption of HPCs have been a topic of research since its development. The main bottleneck was to determine the relation between the performance and power which was pivotal for the control of power provided to a compute-node or a processor, without effecting its net performance. The execution time required for a standard STREAM application was used to evaluate the performance and the workload or the application heartbeats provided an instantaneous measure of the performance of a node. During my period of employment there at Argonne National Lab, I was able to come up with a reinforcement learning based algorithm that used a Proximal Policy Optimization (PPO) agent to learn a policy which optimized the power cap that was provided to the RAPL actuators. By performing the evaluation of the algorithm against the minimum and maximum performance configurations, it was shown that our results fell in the region of optimal performance.
Role: Project Associate
Period: March 2021 - July 2021
Intersection Management: This project in the Networked Control Systems Lab aimed at developing Intersection Management algorithms for connected and automated vehicles (CAV). The requirement of the project was:
Role: Lead Project Engineer
Period: October 2020 - February 2021
Secure package delivery system: The Bangalore based start up recruited for making a fully functioning prototype of their dream product.
Role: Research Consultant
Period: August 2020 - Oct 2020
A short term challenge hosted by one of the upcoming startups in India. The challenge was to solve an optimization problem associated with optimal Operation Room scheduling in the hospitals. Accomplishments include:
Role: Research Associate
Period: January 2017 - December 2019
Role: Project Engineer
Period: July 2016 - December 2016
Phone: +1-615-938-8594
E-Mail: akhileshraj91@gmail.com