Hello, I'm Kulbir Singh Ahluwalia

Teaching Assistant - CS 440/ECE 448: Artificial Intelligence

Instructor: Prof. Margaret Fleck
• Grading Moodle quizzes and testing the machine-problem autograders.

Teaching Assistant - CS498GC: Mobile Robotics for Computer Scientists

Co-developed with Prof. Girish Chowdhary
• Co-developed the course curriculum on mobile robotics, ROS2, sensor fusion, and SLAM algorithms.
• Managed coding exercises and problem sets on Extended Kalman Filtering and odometry implementation.
• Held office hours and helped students with ROS2 development and debugging.
• Built and maintained the course website; maintained the autograding infrastructure on Gradescope.
• Special Topic Fall 2025: SLAM-ing on Mars
• Teaching highlight: SLAM-ing Mars TA reference runs (Husky + UR3 in the Mars Gazebo world, mapped with SLAM Toolbox; clip below at 10x speed).

Teaching Assistant - CS444: Deep Learning for Computer Vision

Instructor: Dr. Svetlana Lazebnik
• Updated and verified starter code for assignments, and answered student questions during office hours and through Campuswire.
• Assessed student submissions via SpeedGrader on Canvas, and designed multimodal quiz questions, including single-choice, multiple-choice, and matching formats.

Teaching Assistant - CS519: Scientific Visualization

Instructor: Dr. Eric Shaffer
• Created multimodal exam questions with integrated visualizations using Python and matplotlib for assessing student understanding of scientific visualization concepts.
• Assisted students with implementation of advanced visualization algorithms including ray marching, transfer functions, and interactive widget development.

Product Management Intern - Qualcomm Technologies, Inc. (Compute Chipset)

Team: Compute Chipset Product Management (Snapdragon X Elite / X2 Elite AI-PC platforms)
• Conducted market and competitive analysis of on-device AI, generative AI, and vision-language model (VLM) features for AI-PC platforms.
• Synthesized feedback into product requirements and roadmap inputs.
• Evaluated VLM workloads on Snapdragon silicon for power, thermal, and latency on the Hexagon NPU.
• Worked with engineering teams on AIMET and AI Hub Models, and prepared internal briefings on edge AI trends.

AI Intern - Earthsense Inc.

Supervisor: Michael McGuire, Lead Computer Vision Engineer
• Key Achievement: Contributed to developing a natural language-conditioned waypoint generation pipeline for agricultural robot navigation.
• Implemented state-of-the-art NLP and CV pipelines for Mobile Manipulators, enabling natural language instruction following.
• Created an automatic labeling pipeline for large outdoor robot navigation datasets using Grounded SAM2, streamlining data processing.
• Deployed and integrated open-source Visual Language Models (Molmo-7B-D, Gemma-3-27B, Qwen-2.5-VL-72B, Qwen3-30B-A3B, Llama4-Scout, Spatial-VLM; 3B-72B params) for robot reasoning in image space and open-world natural language instruction conditioned question answering for 4 wheeled skid steer outdoor robots.
• Enhanced ROS-based systems for real-world agricultural applications, directly supporting the advancement of Physical AI.

First prize in B.Tech. Major Project, 2019

First prize in final year MAJOR PROJECT in the B.Tech. Examination of Electrical Engineering, 2015-19 titled Teleoperated Gesture controlled Robotic arm.

Certificate of Appreciation, (2017,2018)

Received certificate of appreciation for contributions to IEEE PEC (2017,2018).

Programming in Python, 2019

Data Structures & Algorithms in Python, 2022

National Bal Shree Award, 2011

Awarded with the National Bal Shree Award in Creative Scientific Innovations by the Ministry of Human Resource Development, Govt. of India. It consisted of a series of scientific hands-on tests and interviews at city, zonal and national level.