Open to opportunities

Deepam Ahuja

@deepamahuja

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Autonomous systems engineer specializing in perception, control, and embedded robotics for high-performance vehicles.

India

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What I'm looking for

I seek roles building perception and control stacks for autonomous systems where I can apply ML and embedded expertise, work on real-world validation, and contribute to safety-focused engineering and research.

I am an autonomous systems engineer focused on perception, control, and embedded systems for robotics and vehicles. I combine computer vision, machine learning, and real-time control to create robust autonomy pipelines.

My work includes perception stacks using YOLO, OpenCV, ROS2, LiDAR processing, and EKF-SLAM, and I have implemented MPC and PID-Stanley controllers as well as powertrain and brake/steer-by-wire control algorithms.

I have research and industry experience building thermal-face segmentation models, biometric authentication systems, and simulation-to-cloud pipelines for semantic mapping; I also contributed to a provisional patent on continuous-time model-based RL for vehicle control.

I have led competition teams (Formula Bharat, Bosch Future Mobility finalist) and delivered end-to-end projects—from embedded hardware integration on Jetson/Arduino to cloud analytics on Azure—while maintaining a focus on safety, latency resilience, and real-world validation.

Experience

Work history, roles, and key accomplishments

Research Intern

Indian Institute of Technology Roorkee

May 2025 - Jul 2025 (2 months)

Fine-tuned MMSFormer for face-region segmentation on thermal images to enable privacy-preserving, human-centric control of kinetic facades and integrated MediaPipe-based face alignment for backend processing.

MMSFormer Thermal Imaging Mediapipe Face Segmentation Python Computer Vision Deep Learning Data Analysis

IT Intern

Encrypta

Dec 2024 - Mar 2025 (3 months)

Built a biometric authentication system using FaceNet-512 for facial recognition and DeePixBis for anti-spoofing, and implemented a PSK-based challenge-response mechanism for secure local-network device sync.

FaceNet DeePixBis Biometrics Python & Security Embedded Systems Network Protocols

Autonomous Driving Software Engineer

Formula Manipal

Implemented MPC and PID-Stanley path tracking, developed embedded brake-by-wire and steer-by-wire control, built stereo camera and LiDAR perception pipelines, and delivered EKF-SLAM fusion for robust localization, contributing to a 3rd-place finish at Formula Bharat 2025.

MPC PID Stanley YOLOv8 EKF SLAM LiDAR Computer Vision

Education

Degrees, certifications, and relevant coursework

Manipal Institute of Technology

Bachelor of Technology, Computer and Communication Engineering

2023 -

Grade: 8.45 CGPA

Activities and societies: Relevant coursework and scholarship recipient; involved in robotics/autonomous vehicle projects with Formula Manipal.

Pursuing B. Tech in Computer and Communication Engineering with coursework in DSA, OOP, DBMS, Operating Systems, Computer Networks, Embedded Systems, and Information Security; awarded the Scholar’s Scholarship for academic excellence.