•Part of architecture team responsible for developing a Single Page Application (SPA) dashboard with a robust page state management system to enable dynamic updates and seamless navigation without reloading.•Integrated Flask and PostgreSQL for robust back-end support, ensuring smooth API communication and efficient data retrieval. •Implemented features for Static Timing Analysis comparisons and interactive floorplan rendering, enhancing design analysis capabilities. •Improved debugging efficiency by providing a centralized platform for STA data visualization using svelte, enabling quick identification of timing issues.

•Working on SnapDragon Neural Processing Engine as a part of the AI Software team.•Responsible for development and feature additions for ML QA python framework which includes SDK inference, benchmarking and stress tests.•Worked on enabling customer provided Neural Network models in Tensorflow to Qualcomm modelzoo for different customer chipset release cycles.

•Responsible for improvements and upkeep of a codebase focused on log compression. Successfully introduced a memory-saving hashing algorithm. Skillfully adapted the algorithm to diverse targets within various compilers, effectively addressing debugging challenges•Optimized TLB (Translation Lookaside Buffer) usage patterns by optimizing padding and alignment strategies for improved performance•Developed heap usage visualization on AWS Sagemaker for various tech modules•Pioneered heap usage analysis and worked on a framework to capture heap leakage.•Worked on a memory reclaim mechanism to efficiently manage memory segments that were required only once at boot up. The memory segment after bootup is reclaimed as part of heap•Proficiently utilized CrashScope and Trace32 debugging tools to investigate and troubleshoot memory-related crashes and corruption issues ensuring stability working with various team

•Part of the software development team responsible for enhancing a parser and GUI interface to view memory usage of various sections in ELF•Re-structured existing post-processing python script to execute it on standalone environment as part of an initiative. Earlier, it had dependency on other modules. Standalone environment and parallel processing helped to reduce build time •Collaborated on linker script modifications for precise memory layout of different sections in elf

Selected as one of the Top Fellows for my cohort. The Fellowship was of 3 months covering topics on Product Management along with solving case studies and networking with peers.

A small group coach mentoring about 15 students on Data Science!

- Working on developing a platform to leverage several use cases of drones. My work includes detecting anomalies for surveillance purposes from live videos recorded by a drone.- Designing the workflow of the platform and contributed in architecture of the platform

Creating content on topics of Data Science!

Engaged with other student data scientists and developers. Obtained free software, tools and libraries from Intel. Received direct access to Intel AI DevCloud.

The leading position from the student end of the Student-Faculty managed independent body.Roles include Team Leadership, Organization, Event Management, Faculty-Student Communication Interface, External and Internal Relationship Coordination.Led a team which won the Runner's up award(Mentoring Track) at the National Entrepreneurship Challenge held at IIT Bombay.

- Helped in organizing various workshops for skill development. Worked with the Joint Secretary to successfully host eminent entrepreneurs in the E-Summit. - Developed a part of the KGEC E-Cell website.

- Worked remotely on Customer Behaviour Analysis at various stages to build an entire persona for a customer.- Worked on a Machine Learning model to predict the success of a marketing campaign.- Worked on the probability of a customer to move to a particular stage in shopping.- Developed a Sequential model to predict a probability for customer retention and compute Customer Lifetime value.- Built an LSTM model to find user intent from their search query.

- Displaying the algebraic notation of a computerized chess game after it is played.- Used Deep Learning techniques to output the moves of the game as it is played.

- Built and deployed a model that analyzes the RAM, CPU and Hard Disk utilization from previous log data and predicts failure inadvanced for a system using an LSTM model.- Worked on PySpark to perform some basic visualizations on a dataset provided by a restaurant.

- Classification of MIMIC-II Dataset for Plethysmographic Signals.

Worked on Data Mining and analysis of restaurant data as a part of internship.