I'm Arjun A B!

     AI enthusiast with hands-on experience in various AI models. I work on the development of industry-leading high-performance and power-efficient GPUs. I am committed to broadening knowledge and leveraging expertise to contribute to game-changing advances in the field. My collaborative nature, adaptability, and meticulous attention to detail set me apart. I am looking for impactful projects where I can contribute expertise and drive innovation.

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Experience

SandLogic Technologies Pvt. Ltd.

Edge AI Developer (Sept 2022 – Present)

  • Automatic toll collection using Deep learning with Data collection of 4 different classes of vehicles containing more than 3500 images for Indian vehicles. Data analysis and data cleaning for the Implementation of toll. Model accuracy of 97.2% was achieved using YOLO.
  • Optical character recognition (OCR) with image quality assessment. A brief study of edge detection using different filtering techniques. Dot-printed character recognition for multiple day-to-day used products. Filtered and extracted text yielded 92% of accuracy.
  • Identification of abnormal ECG signals using a low-power microcontroller [Tiny ML].
    • Detection of various arrhythmias with the lowest latency of 36.424 ms and a model accuracy of 98%.
    • The dataset included 1200 datapoints from 20,000 patient records.
    • Implemented on a microcontroller STM32 Cortex-M4 with 256 KB of flash memory.
  • Deep learning accelerator was implemented on the Chromite-H core system-on-a-chip (SoC).
    • Incorporated Deep Learning Accelerators into the RISC-V SoC Incore Chromite-H core, utilizing Zynq Ultrascale+ MPSoC ZCU104 FPGA.
    • To enable the SoC and Accelerator to share the DDR Memory Controller, an integrated Multi- Port Memory Controller (MPMC) design was developed.
    • Accumulated practical understanding of the various AXI Infrastructure Architectures and the AXI Protocol.
    • Timing analysis, placement & routing, and a variety of built-in Vivado methods were used to optimize the FPGA design.
    • Ran a range of DL models and adapted Accelerator's runtime and kernel drivers to the RISC-V Linux kernel.
  • Implementation of Deep Learning Accelerator on PolarFire SoC FPGA Icicle Kit. Configuration of the RISC-V processor using MSS configurator tool. Conducted a complete study and understanding of the Libero SoC tool and Polarfire SoC.
  • Design and implementation of high-performance CSI2 MIPI camera system on ZCU104
    • Designed a dedicated MIPI Circuit with specialized filters to ensure flawless image data flow
    • Integrating VCU (Video Codec Unit) to Processes frames and transmit them to gstreamer.
    • Ensured seamless frame handling, guiding frame acquisition, configuration, and integration with gstreamer for video streaming and processing.
    • Created unique IP blocks to enhance versatility and performance, addressing specific needs.
    • Developed a tailored operating system to provide a robust foundation for camera interaction and peripheral support.
    • Utilized Xilinx Vitis to optimize application deployment within the FPGA by bridging hardware and software.

SandLogic Technologies Pvt. Ltd.

Edge AI Intern (Apr 2022 – Aug 2022)

  • Understanding the basics of AI and Designing deep learning neural nets
  • Data collection and collation for training the model for vehicle detection.
  • Data annotation and labelling using make sense.ai
  • Training, Validation, and Testing for NMIST.
  • Inference check.
  • Autopilot system for cars with Advanced Driver Assistance System.

Personal Projects

  • Smart switches using Node MCU (08/2021)
    • Best workshop project award.
    • Controlling the switch through a mobile app protected by a Google firewall.
    • It could be used in a variety of crucial situations where human assistance would be difficult.
  • Diabetes prediction using PIMA dataset (02/2022)
    • Diabetes prediction based on the PIMA Indian dataset.
  • Implementation of E-Toll using Deep Learning (12/2021 - 06/2022)
    • Best presenter award at ICAMET Conference.
    • CNN-based automatic vehicle detection.
    • Vehicle classification was archived swiftly, which reduced congestion at the toll booth.
    • A web application-based graphical user interface (GUI) was created to monitor the progress of vehicle classification and tax implementation.

    Education

    Vidyavardhaka College of Engineering – Mysore, India
    Bachelor of Engineering, Electronics and Communication; Cumulative GPA: 8.5/10 (May 2022)

    Technical Skills

    • Technical: Field-Programmable Gate Arrays (FPGA), Digital logic design, Systems Design, High Performance Computing, Computer architecture, Hardware-software co-design.
    • AI concepts: Artificial Intelligence, Machine Learning, Neural Networks, Generative AI, Large Language Models
    • Languages: Python, C/C++, Bash
    • Hardware Languages: Verilog, System Verilog
    • Design Tools: Xilinx Vivado, Vitis HLS, Microchip Libero, Matlab & Simulink
    • Protocols: UART, I2C, SPI

    Achievements

    • Best Paper Presenter Award at Second International Conference on Advances in Management, Engineering & Technology (ICAMET-2022) (June 2022)

    Certificates

    • Programming for Everybody (March 2021 - April 2021)
    • Intel Distribution of OpenVINO Toolkit (April 2021)
    • Second International Conference on Advances in Management, Engineering & Technology (ICAMET-2022) (June 2022)
    • 2022 ACM/IEEE TinyML Design Contest at ICCAD

    Feel free to get resume template source code.