Curriculum Vitae: pdf

Education

• B.Tech. in Mechanical Engineering (2015), Indian Institute of Technology, Kharagpur
• M.S. in Mechanical Engineering (2018), Arizona State University
• Ph.D in Mechanical Engineering (2024), Arizona State University
  • Thesis Title: Analysis, Estimation, and Control of Partial Differential Equations Using Partial Integral Equation Representation
  • Thesis Advisor: Matthew Peet (Website)

Publication Summary

I have 10 (being the first author for 5) conference papers, all published in the proceedings of IEEE CDC or ACC (listed as the number 1 and 2 top conferences in control theory based on h5-index). I also contributed a chapter as the first author for a book published by Springer on the state-of-the-art control of underwater soft robots. Lastly, I have two journal papers under review one in IEEE TAC and another in IEEE L-CSS. All publications are available for public access on CSCL website and a few key publications are listed below.

• Shivakumar, S., Das, A.,& Peet, M. M. (2020, July). PIETOOLS: A MATLAB toolbox for manipulation and optimization of partial integral operators. In 2020 American Control Conference (ACC) (pp. 2667-2672). IEEE.
• Shivakumar, S., Das, A., Weiland, S., & Peet, M. M. (2020, December). Duality and H_∞\infty-optimal control of coupled ODE-PDE systems. In 2020 59th IEEE Conference on Decision and Control (CDC) (pp. 5689-5696). IEEE.
• Shivakumar, S., Das, A., Weiland, S., & Peet, M. M. (2019, December). A generalized LMI formulation for input-output analysis of linear systems of ODEs coupled with PDEs. In 2019 IEEE 58th Conference on Decision and Control (CDC) (pp. 280-285). IEEE. %- Doroudchi, A., Shivakumar, S., et al. (2018, December). Decentralized control of distributed actuation in a segmented soft robot arm. In 2018 IEEE Conference on Decision and Control (CDC) (pp. 7002-7009). IEEE.
• Jagt, D., Shivakumar, S., Seiler, P., & Peet, M. (2022). Efficient Data Structures for Representation of Polynomial Optimization Problems: Implementation in SOSTOOLS. IEEE Control Systems Letters, 6, 3493-3498.
• Shivakumar, S. et al. (2021). Decentralized Estimation and Control of a Soft Robotic Arm. In: Paley, D.A., Wereley, N.M. (eds) Bioinspired Sensing, Actuation, and Control in Underwater Soft Robotic Systems. Springer, Cham.

Awards and Recognition

• 2024: Outstanding Graduate Research Award, School for Engineering of Matter, Transport, and Energy, Arizona State University

Work experience

• MAE Tutor (Jan 2017 - Jan 2018), FSE tutoring center, Arizona State University
  • Tutored students in the freshman, sophomore and junior courses of physics, mathematics and mechanical engineering under ASU student welfare program.

• Computer Lab Teaching Assistant (May 2017 - Jul 2017), School of Mathematical and Statistical Sciences, Arizona State University
  • Worked on setting up and maintaining Linux systems at the lab. Tutored students on using Matlab and Linux systems for courses in Applied Linear Algebra and Differential Equations.

• MAE Teaching Aide (Jan 2017 - May 2017), School for Engineering of Matter, Transport & Energy, Arizona State University
  • Lead recitation classes/tutoring sessions for the course on numerical methods in engineering for sophomores/juniors.

• Graduate Research Assistant (Jan 2018 - May 2024), Cybernetic Systems and Controls Lab, Arizona State University -Worked on solving fundamental problems in the Control of distributed parameter systems. Funded by NSF: CMMI-1935453, CNS-1739990.
  • Developed decentralized control actions for octopus-inspired soft-robotic arms. Funded by ONR: N00014-17-1-2117.
  • Solved the scalability issues, in terms of computation and memory complexity, of Sum-of-Squares programs by developing a new data structure for the representation of polynomial-valued decision variables in convex-optimization problems. Funded by NSF: CMMI-1931270, CMMI-1935453.

• Senior Engineer (Jul 2015-Jul 2016), Robert Bosch Engineering and Business Solutions pvt. ltd., Bengaluru, India
  • Optimized manufacturing processes as part of the Industry 4.0 Initiative within Bosch.
  • Developed backend data mining/prediction algorithms.
  • Devised control parameters for statistical process control and implemented a prediction-alert system to reduce field failure rates.

Skills

• Programming Languages:
  • MATLAB
  • Python
  • C++
  • Fortran
• Languages (can read, write, and speak in):
  • English
  • Kannada
  • Hindi
• Miscellaneous Hobbies:
  • Violin (classical music)
  • Boxing
  • Judo
  • Chess
  • Tennis