Robotics Researcher and Engineer

I am an MS student at the University of Washington, Seattle, specializing in robotics research and engineering with a focus on computer vision and controls of robots. Currently, I hold the position of Research Assistant at the Robot Learning Lab, working with Prof. Byron Boots.


Vision-based controls and navigation

Self-supervised scene understanding

Whole-body control

Learning-based control

Full Stack Robotics


Hello there! Thanks for taking the time to visit my website. I hail from Navi Mumbai, India, and now call Seattle my home as I pursue my MS degree. My upbringing was blessed with supportive parents who encouraged me to explore beyond academics. Playing the piano, painting, and my passion for football became integral parts of my life. I cracked the IIT-JEE Advanced and got into Mechanical Engineering at the Indian Institute of Technology, Gandhinagar. As captain of the college soccer team, I represented the squad in state and national-level tournaments. Additionally, I was part of the college band, performing at various fests and arenas. I was awarded the Institute's Silver Medal and Director's Silver Medal for outstanding performance in academics and all-round performance respectively.

Research Journey

My research journey started at the Indian Institute of Technology, Gandhinagar (IIT Gn), with building an autonomous 1/10th scale race car to control at high speeds. We used a novel temporal shallow-deep neural network to detect roads, a genetic algorithm for local planning, and PID to control the car. This helped me gain insights into the interplay of perception, planning, and control and led to my first publication "Memory Guided Road Detection". Concurrently, my involvement in the All-Terrain-Vehicle (ATV) building team for off-road terrains made me question the applicability of our on-road algorithms in off-road settings. This channelized my interest in robotics for unstructured environments.

At the University of Washington, Seattle (UW), under Prof. Byron Boots, I have been working in the perception team of DARPA RACER, which focuses on running ATVs in unstructured off-road terrains. Our team uses point-cloud data for semantic segmentation to determine the local map around the vehicle. Point-cloud data becomes sparse with distance, and the segmentation model is over-confident in the sparse regions. Thus, I added an aleatoric uncertainty module to quantify the model confidence to facilitate safer navigation. Sparser point-clouds also mean the risk of undetected objects, prompting us to use object detection techniques using camera images. However, their practicality is limited without post-processing steps like object tracking and temporal aggregation, leading me to develop a real-time multi-object tracker. RACER's reliance on multiple LiDAR and camera sensors for advanced off-road navigation raises a key question for my Ph.D. research: “Is efficient locomotion and navigation with fewer sensors achievable?" Addressing this could reduce costs and power consumption, making robots more practical for real-world applications.

Working under Prof. Harish PM, at IITGn, in our journal article "Impact of Added Passive Compliance on the Performance of Tip-Actuated Flexible Manipulators" taught me the practical significance of the theoretical concepts from control theory. At UW, collaborating with Prof. Guanya Shi, I was introduced to Reinforcement Learning (RL) and Optimal Control / Model Predictive Control (MPC), deepening my appreciation for controls. In our paper "DATT : Deep Adaptive Trajectory Tracking for Quadrotor Control", we developed a novel model-free RL framework for tracking infeasible trajectories, adaptable to external conditions like wind and payload, on low-cost drones, showing a 54% improvement over MPC. Next, we identified the strengths and limitations of MPC and RL. This led us to think, "Why not blend both to leverage the robustness of model-based MPC and the adaptability of model-free RL?" Consequently, in the paper, "Deep Model Predictive Optimization", we showed that blending MPC with RL enables drones to perform high-precision tasks like agile flips. This gives me the promise that learning-based control enables robust and agile navigation on low-cost robots and has brought them closer to real-world applications.


Check My Resume


Alice Barkley

Innovative and deadline-driven Graphic Designer with 3+ years of experience designing and developing user-centered digital/print marketing material from initial concept to final, polished deliverable.

  • Portland par 127,Orlando, FL
  • (123) 456-7891


Master of Fine Arts & Graphic Design

2015 - 2016

Rochester Institute of Technology, Rochester, NY

Qui deserunt veniam. Et sed aliquam labore tempore sed quisquam iusto autem sit. Ea vero voluptatum qui ut dignissimos deleniti nerada porti sand markend

Bachelor of Fine Arts & Graphic Design

2010 - 2014

Rochester Institute of Technology, Rochester, NY

Quia nobis sequi est occaecati aut. Repudiandae et iusto quae reiciendis et quis Eius vel ratione eius unde vitae rerum voluptates asperiores voluptatem Earum molestiae consequatur neque etlon sader mart dila

Professional Experience

Senior graphic design specialist

2019 - Present

Experion, New York, NY

  • Lead in the design, development, and implementation of the graphic, layout, and production communication materials
  • Delegate tasks to the 7 members of the design team and provide counsel on all aspects of the project.
  • Supervise the assessment of all graphic materials in order to ensure quality and accuracy of the design
  • Oversee the efficient use of production project budgets ranging from $2,000 - $25,000

Graphic design specialist

2017 - 2018

Stepping Stone Advertising, New York, NY

  • Developed numerous marketing programs (logos, brochures,infographics, presentations, and advertisements).
  • Managed up to 5 projects or tasks at a given time while under pressure
  • Recommended and consulted with clients on the most appropriate graphic design
  • Created 4+ design presentations and proposals a month for clients and account managers



Deep Model Predictive Optimization

Jacob Sacks, Rwik Rana, Kevin Huang, Alex Spitzer, Guanya Shi, Byron Boots

Submitted to ICRA 2024

[ArXiv] [Website] [CoRL 2023 Workshop]

DATT: Deep Adaptive Trajectory Tracking for Quadrotor Control

Kevin Huang, Rwik Rana, Alexander Spitzer, Guanya Shi, Byron Boots

Proceedings of The 7th Conference on Robot Learning

[PMLR] [ArXiv] [Website]

Impact of Added Passive Compliance on the Performance of Tip-Actuated Flexible Manipulators

Barat S., Sushrut Surve, Rwik Rana, Madhu Vadali, Harish J. Palanthandalam-Madapusi

ASME Journal of Dynamic Systems, Measurement, and Control



Memory Guided Road Detection

Rwik Rana, Praveen Venkatesh, Varun Jain

International Conference Image Analysis and Processing (ICIAP) 2022, Lecce, Italy

[ArXiv] [Springer]


My Works

  • All
  • App
  • Card
  • Web

App 1


Web 3


App 2


Card 2


Web 2


App 3


Card 1


Card 3


Web 3



Contact Me

My Address

A108 Adam Street, New York, NY 535022

Social Profiles

Email Me

Call Me

+1 5589 55488 55

Your message has been sent. Thank you!
Designed by BootstrapMade