About me

I am passionate about robotics, with a focus on perception, particularly SLAM, state estimation, and sensor fusion.

My interests lie in developing robust perception and localization algorithms and pipelines that enable autonomous systems to operate reliably in real-world environments. I enjoy building robust, real-time pipelines while integrating multi-modal sensors, combining theoretical estimation with practical, scalable software solutions.

What i'm doing

  • design icon

    Robotics Engineer

    Working on Inspection Robots for Oil & Gas Industry.

Projects

  • Visual Odometry

    Visual Odometry

    Developed a visual odometry pipeline in C++.

  • Multi-Agent

    Multi-Agent Prey Predator

    Implemented a multi-agent prey vs predator in Petting Zoo environment using Deep Deterministic Policy Gradient architecture and Prioritized Experience Replay.

  • Monocular Depth Estimation via Transfer learning

    Implemented an encoder-decoder convolutional neural network architecture for computing a high-resolution depth map given a single RGB image with the help of transfer learning.

Daniel lewis
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Daniel lewis

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Resume

Education

  1. State University of New York at Buffalo (SUNY)

    2021 - 2022

    Masters in Engineering Science with focus on Robotics and Artifical Intelligence.

    Relevant Course Work - Robotics Algorithm, Computer Vision, Deep Learning, Reinforcement Learning.

  2. University of Mumbai

    2015 - 2019

    Bachelor's in Electrical and Telecommunication Engineering.

Experience

  1. Digital Deployment Engineer - SLB (Schlumberger)

    2023 — Present

      Led the deployments of robots at five major customers' sites in the oil and gas industry, allowing the routine autonomous inspection in hazardous locations and improving the efficiency in data collection
      Led the design and implementation of workflow automation and system integration between multiple Fleet Management Systems and the Data Layer, enabling seamless deployment of ANYmal D and Boston Dynamics Spot robots for routine inspections and data acquisition at a large-scale oil and gas facility.
      Developed a proof of concept (PoC) for real-time vibration anomaly detection in rotating equipment using an event camera and RGB-D camera; implemented a target-less extrinsic calibration algorithm and a multi-threaded sensor data processing pipeline for efficient data fusion and analysis.

  2. Computer Vision Intern - Circle Optics

    August 2022 - December 2022

    Implemented a C++-based visual odometry pipeline for Hydra, a 360° parallax-free camera, enabling vision-based localization in indoor environments.

My skills

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