Kieran Lachmansingh

About Me

Hello! I'm a passionate robotics and high-performance computing graduate exploring the frontier between intelligent algorithms, real-time systems, and scalable design.

I've recently finishing my Master's in Applied Science at Queen's University. My journey included applying data analysis tools like Excel, programming design and testing using ROS and ROS2 for robotics, and experience working with data center-sized systems.

With a background in electrical engineering and hands-on experience in Python, C, and C++, I aim to combine technical depth and creative problem-solving to develop high-impact solutions in robotics.

Affiliations

MItHRIL

Ingenuity Labs Research Institute

CAESAR

Research & Publications

Research centered at the intersection of robotics, real-time systems, and high-performance computing.

SHARP: Supercomputing for High-speed Avoidance and Reactive Planning

ICRA 2026

Kieran Lachmansingh, José R. González-Estrada, Jacob Chisholm, Ryan E. Grant & Matthew K. X. J. Pan

SHARP investigates whether high-performance computing can be used for reactive robot control without violating real-time constraints. Motion planning is offloaded to HPC clusters using a hash-distributed, multi-goal A* planner. The system enables millisecond-scale avoidance behaviors and reframes HPC offloading as a viable pathway toward dependable, reactive robots in dynamic environments.

Project page Paper Code

A computer connected to several servers.

Scaling Parallel Graph Computing for Real-time Robotics

ICS 2026 (in review)

Kieran Lachmansingh, José R. González-Estrada, Jacob Chisholm, Matthew K. X. J. Pan & Ryan E. Grant

This paper presents a systematic scaling analysis of a repre- sentative robotics planning algorithm, motivated by the emerging need for robots to leverage data center-scale compute resources. To study this interaction, we implement a hash-distributed multi- goal graph search that computes collision-avoidance trajectories. We evaluate its performance under stress, examining both strong and weak scaling across a range of graph sizes and process counts.

Project page Code

Projects

Selected robotics projects focused on artificial intelligence, robotics, and autonomous navigation.

Point cloud of camera used for training.

VLA Development Pipeline and Evaluation

March 2023 - Present

Ingenuity Labs Research Institute & Taiga Robotics

Investigated the use of vision-language action (VLA) models for manufacturing applications.
Developed a pipeline through teleoperation using Mujoco in simulation to develop datasets for training robots.
Designed a methodology through demonstration and camera capture on real-world data through physical task execution using the end-effector to create trainable data.
Created notebooks and programs that detail the training steps and Google Colab notebooks for logging.

An RC Car outfitted with sensors and computers for autonomous racing.

Mechanical Team Lead of Ingenuity Labs Racing

September 2025 - Present

Ingenuity Labs Research Institute

Founding member of Ingenuity Labs Racing - a Roboracer autonomous racing vehicle challenge.
Managed physical upgrades to vehicle, maintenance, and on-the-fly adjustments.
Oversaw additional members design and creation of AutoCAD parts.
Assisted in layout design, programming, and troubleshooting of vehicle.
For more information on the Roboracer competition, see https://roboracer.ai/

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