Hi, my name is

Shashi Prakash Shah.

Looking for Opportunity

Crafting software solutions with passion and precision.

Backend-focused Senior Software Engineer with 3.5+ years of experience building reliable, high-performance systems. Strong in scalable backend design, data integrity, debugging, and performance optimization—applying systems-level rigor to build secure, resilient platform services.

About Me

Hi! I'm Shashi Prakash Shah, a computer enthusiast whose journey began in high school when tinkering PC paved the path for me to learn to assemble my Desktop and introduced me to Linux !!!.

My fascination with computers inspired me to pursue a Master's in Computer Science. During my post-graduation, I spearheaded the development of a text summarizer using a transformer-based encoder-decoder architecture, achieving a remarkable 15% improvement in summarization accuracy.

Fast forward to the present, I’ve had the privilege of delving into web and desktop product development. Currently, at Interra Systems, my focus revolves around crafting customer-centric solutions. I'm a passionate C++ developer adept at optimizing software performance. Leveraging my data structures, algorithms, and memory management expertise to identify and resolve performance bottlenecks efficiently.

As a driven and results-oriented professional, I'm eager to contribute my skills to a challenging C++ role, dedicated to crafting high-performance and scalable software solutions.

Here are a few technologies I’ve been working with recently:

  • C++ 11/14/17
  • Python 3
  • JavaScript
  • HTML & CSS
  • GNU GDB
  • Valgrind
  • Purify & Coverity
  • SVN & Perforce
  • Algorithm Optimization
  • Memory Optimization
  • Programming languages: C, C++, Python(automation, log extraction) , JavaScript
  • Backend & Web: Django REST, Node.js (learning), REST APIs, SQL, JWT auth, React (learning)
  • Tools: GDB, Valgrind, Purify, Coverity, SVN, Perforce, MakeFiles, Linux, flex, Yacc
  • Scripting: Python, CShell, Tcl
  • Strength: Data Structures & Algorithms (DSA), OOP, Memory & Algorithm Optimization

Where I’ve Worked

Sr. Software Engineer(R&D) @ Synopsys India Pvt. Ltd.

July 2024 - Present

  • Accelerated cross-probing (xref) injection by over 90%, reducing runtime from 6 minutes to 49 seconds and delivering a 2-3X speedup on designs with 75% missing metadata.
  • Implemented DFS-based traversal logic using internal graph-walk infrastructure, cutting redundant propagation and lowering runtime from 65 minutes to 5 minutes on 2.7M-instance netlists.
  • Improved metadata accuracy and propagation reliability by 40% by re-engineering the injection algorithm to address synthesis-induced xref gaps.
  • Identified and resolved hierarchy-generation defects across 7+ optimization and transformation steps, reducing hierarchy-related errors by 30% across 20+ flows.
  • Built and enhanced a hierarchy validation utility that reduced debug time by over 50% and improved detection of incorrect hierarchy generation across 36+ design flows.
  • Expanded regression and QoR coverage with missing-xref scenarios across 20+ customer-scale designs, increasing diagnostic completeness by 15% and ensuring stable metadata propagation across refinement stages.
  • Automated hierarchy-reporting and integrity checks, improving failure-isolation efficiency by 35-50%.
  • Delivered memory optimizations in xref and hierarchy-infrastructure utilities, achieving stable regression results
  • and eliminating recurring crashes in complex design environments.
  • Added advanced debugging utilities that reduced issue reproduction and failure-isolation time from hours to under 20 minutes.
  • Enhanced RTL support for concatenation assignments with ternary operators, improving synthesis-tool compatibility and reducing RTL-read failures.
  • Developed script-generation pipelines to streamline migration between internal EDA projects, reducing manual integration overhead.
  • Delivered multiple enhancements and bug fixes across compiler, hierarchy, and infrastructure modules.
  • Led cross-functional technical discussions and produced analysis reports that influenced future metadata-handling and xref-injection roadmap decisions.

Engineer @ Interra Systems India Pvt. Ltd.

July 2022 - July 2024

  • Developed a GDSII layer editing utility, empowering users to directly modify multiple elements across files, boosting productivity by 20%.
  • Implemented GDB tracing in MC2, reducing debug time by 5%.
  • Developed comprehensive and user-friendly error messages for invalid MDL syntax, reducing debugging time by upto 10%.
  • Enhanced inbuilt support for array and hash functionalities in MDL, ensuring correct and consistent behavior when working with arrays in the software, and preventing potential data corruption.
  • Analyzed and increased parallel compiler execution by 33%, utilizing 40 additional instances on a 200-core system.
  • Rectified proper initialization of arrays in MDL, ensuring code reliability and stability, and preventing potential memory leaks.
  • Improved memory usage by 34% through leak detection and error removal, enhancing system stability and resource efficiency.
  • Implemented a GDSII-based GUI view, offering a visual representation of sub-circuit and cell ports for improved debugging, reducing error resolution time by 5%.
  • Implemented GDSII element hierarchy copying, significantly improving user experience in memory design, boosting user experience.
  • Enhanced netlist clarity by adding user-specified instance naming to generated netlists in MDL,facilitating debugging and clarity.
  • Implemented support for creating arrays from multiple scalar variables in MDL, enhancing language flexibility and usability.

My Code Creations

  • Developed a module in C to convert XML data into C structures and arrays. Utilized Flex and Bison for parsing, leveraging parse trees and intermediate tree representations.

    This module facilitates handling XML data within C applications.

    • C
    • Lex
    • YACC
    • XML
  • Developed a Convolutional Neural Network inspired by VGG-16 and AlexNet to classify bird species, using the Caltech-UCSD Birds 200 dataset. Focused on 20 bird categories, we compared our model with state-of-the-art neural networks, fine-tuning parameters for optimal performance. Initialized networks with both pre-trained ImageNet weights and random weights. Achieved testing accuracy on par with ResNet-50 and surpassed it in training accuracy. Gained insights into neural network training through detailed analysis of training graphs."

    • Python
    • Keras
    • CNN
    • Image-data-Augmentation
  • During my summer internship at CSIR-CMERI, Durgapur, I developed an innovative application for voice-based translation using Google APIs. The project involved:

    • Speech-to-Text and Text-to-Speech Integration: Leveraged Google's APIs to convert voice to text and vice versa.
    • Language Translation: Utilized Google's Translation API to translate between Bengali and English.
    • Chatbot Development: Scaled the application into a chatbot based on a Question Answering System, capable of processing voice inputs and generating responses from a predefined corpus.
    • Testing: Used a Wikipedia page about computers to test the application's functionality and accuracy.

    • Python
    • API-integration
    • Tkinter
    • NLP

Get in Touch

If you'd like to connect with me, feel free to reach out and send me a connection request. And if you're interested in checking out some of my coding work, head over to my GitHub profile. Don't hesitate to reach out if you have any questions or want to connect with me further. I'm always open to meeting new people and expanding my network on these platforms.