CV

Curriculum vitae and resume.

Contact Information

Name Christo Aluckal
Professional Title Graduate Research Assistant / PhD Candidate
Email [email protected]
Phone +1-716-344-0215
Location Buffalo, New York 14208
Website https://christoaluckal.com

Professional Summary

I focus on creating adaptive and practical tools that make robotic autonomy more robust, deployable, and impactful across real-world applications.

Experience

  • 2022 - Present

    Buffalo, United States

    Graduate Research Assistant / PhD Candidate
    DRONESLab
    • Developed TERA, a ROS-based simulation framework in Unity3D for autonomous excavators with customizable hardware parameters and sensor specifications.
    • Created a ROS wrapper for low-level excavator control to enable autonomous operation.
    • Developed an incremental training strategy for 3D Gaussian Splatting that enabled real-time, memory-efficient scene reconstruction on edge and low-power devices with a 33 percent reduction in training time.
    • Assisted in developing software for autonomous inspection in low-light environments such as culverts.
  • 2020 - 2022

    Mumbai, India

    Intern / Part-Time
    InfiCorridor Solutions Pvt. Ltd.
    • Developed PixTrigger, an open source framework for capturing and geotagging images, interfaceable with more than 100 cameras in Python and C/C++.
    • Developed the No Permission No Take-off system in C/C++ to verify digital signatures in compliance with Directorate General of Civil Aviation standards.
    • Audited, validated, and improved data workflows for GIS applications.
    • Planned and executed autonomous UAV missions to generate imagery and maps for Digital Elevation and Terrain Models.

Education

  • 2025 - Present

    Buffalo, United States

    Doctor of Philosophy
    University at Buffalo
    Computer and Information Science
  • 2022 - 2025

    Buffalo, United States

    Master of Science
    University at Buffalo
    Computer and Information Science
    • GPA: 3.53/4.00
    • Relevant Courses: Machine Learning, Reinforcement Learning, Robotics Algorithms, Computer Vision and Image Processing, Learning for Autonomous Systems
  • 2016 - 2021

    Mumbai, India

    Bachelor of Engineering
    Mumbai University
    Computer Engineering
    • Grade: 8.44/10.00
    • Relevant Courses: Machine Learning, Digital Signal and Image Processing

Projects

  • Master's Thesis: TERA: Simulation Environment for Terrain Excavation Robot Autonomy

    Tools: Unity, C#, ROS

    • Designed TERA, a simulator supporting real-time operation and high-fidelity modeling of autonomous excavators and terrain interaction.
    • Incorporated time-varying dynamics to study the challenges of full excavation autonomy.
    • Enabled users to spawn multiple sensors including cameras, IMUs, and LiDARs with configurable characteristics.
    • Validated the simulator with track deformation, velocity profile, and real-to-sim similarity scenarios for systematic evaluation of excavation autonomy algorithms.
  • Splat-by-Splat: Progressive Gaussian Splatting for Efficient Scene Reconstruction

    Tools: Python, PyTorch, CUDA, COLMAP

    • Proposed an incremental training strategy for 3D Gaussian Splatting to overcome memory and compute limitations of full-dataset training.
    • Developed a partitioning algorithm that splits a COLMAP scene into user-defined chunks sequentially or based on geometric constraints.
    • Built a sequential dataset integration approach for real-time scene reconstruction on edge and low-power devices.
    • Extended the original 3DGS implementation to support incremental updates to the training dataset.
  • Learning Visual Information Utility with PIXER

    Tools: Python, BNNs, PySLAM, Optuna

    • Conducted experimental evaluation of PIXER, a probabilistic feature-selection method for visual odometry.
    • Collected and curated a custom Davis dataset using a ZED 2i camera and Mosaic X5 GNSS mounted on a Boston Dynamics Spot.
    • Integrated PIXER outputs into PySLAM and implemented Optuna-driven parallel hyperparameter optimization across six concurrent studies.
    • Demonstrated 34 percent mean RMSE reduction and 41 to 49 percent keypoint reduction while maintaining or improving accuracy.

Publications

Skills

Programming Languages: Python, C, C++, C#, OCaml
Web Technologies: HTML, CSS, JavaScript, Bootstrap, Flask, Django
Data Science and Machine Learning: NumPy, Pandas, Matplotlib, OpenCV, PyTorch, Keras, TensorFlow, Optuna, WandB
Specialized Areas: ROS 1/2, Robotics, Unity, MATLAB, CAD, LaTeX, Metashape
Research Skills: Data Collection and Analysis, Literature Review, Academic Writing
Other Tools and Technologies: Git, Adobe Photoshop, GIMP, Adobe Premiere, KDENLive, Blender

Awards

  • 2019
    Just Joe Sportsmanship Award
    Student Unmanned Aerial Systems Competition
  • 2025
    CSE Faculty Choice Award
    University at Buffalo

References

  • Dr. Karthik Dantu

    Associate Professor, Department of Computer Science and Engineering, School of Engineering and Applied Sciences, University at Buffalo. Email: [email protected]. Phone: +1-716-645-2670. Relationship: Thesis Advisor, Research Advisor.