Computer Engineering Graduate Student | Exploring Machine Learning, Computer Vision, and Data Science

Education

MS in Computer Engineering, California State University, Sacramento (Expected May 2026)
BS in Electronics and Telecommunication Engineering, SPPU, (May 2023)

Research Assistant - EEG and Neuroprosthetic Signal Processing (_Oct 2025 - Present)

Developed an automated EEG classification pipeline to detect neurological disorders such as epilepsy, autism spectrum disorder, and Parkinson’s disease, focusing on accuracy, scalability, and real-time processing.
Engineered multi-domain feature extraction modules — including Power Spectral Density (PSD) via Welch’s method, time–frequency analysis, and cyclostationary feature mapping — integrated with CNN, RNN, and SVM models for high-precision event classification.
Designed a closed-loop detection framework that synchronizes real-time EEG acquisition, adaptive feature extraction, and machine learning–based event detection with responsive feedback control, advancing neuroprosthetic and implantable electrode applications.
Conducted in-depth literature research via IEEE Xplore and CRCNS, refined the methodology and visuals for the research thesis, and integrated faculty feedback to ensure scientific rigor and reproducibility.

Junior Developer @ Arcasan Software Pvt Ltd (Jan 2023 - Jan 2024)

Enhanced front-end performance by converting high-resolution images to WebP format, resulting in over 50% reduction in bandwidth usage and 7% faster load times on mobile devices, improving overall user experience and responsiveness.
Designed and built a scalable customer analytics dashboard using Flask (Python) for quick prototyping and Spring Boot (Java) for robust backend services, integrating RESTful APIs and handling large-scale transactional data efficiently.
Boosted system performance by 20% through optimized database queries, structured data flow, and asynchronous processing, enabling real-time analytics and high-volume data management with minimal latency.
Defined the end-to-end technical scope of the dashboard, including feature planning, API design, database schema development, and access control ensuring strong client alignment and accelerating the development lifecycle.

Data Science Intern @ SmartKnower (Jan 2022 - March 2022)

Developed an unsupervised machine learning pipeline using K-Means clustering in Python to identify potential credit default customers, working with 150k+ records after extensive data cleaning, feature engineering, and model tuning.
Performed exploratory and predictive data analysis using Pandas and NumPy, delivering insights that supported targeted credit risk mitigation strategies.
Achieved 87% model accuracy in identifying high-risk customer segments, improving early risk flagging and aiding business decision-making.
Created interactive data visualizations to present trends and patterns, and proposed marketing strategies to the Senior Analyst based on clustering and segment analysis.

Network Engineering Intern @ Visual Securities (June 2021 - Sept 2021)

Conducted on-site assessments to identify optimal security monitoring points; installed network switches and configured IP-based CCTV cameras across Tata Motors’ manufacturing assembly line.
Integrated IP cameras with Network Video Recorders (NVRs) over a secure VLAN using SNMP routing, enabling real-time remote access while ensuring robust protection against unauthorized intrusion.
Implemented IP whitelisting and multi-factor authentication (MFA) protocols for remote monitoring, enhancing surveillance system security by 15%.
Collaborated with the IT and security teams to maintain consistent network uptime and secure video transmission, contributing to streamlined surveillance operations in a high-throughput industrial environment.

Multimodal AI Video Assistant (Oct 2025 - Nov 2025)

Developed a multimodal AI video-analysis system that combines visual frame extraction and audio transcription from local uploads to deliver structured, data-rich insights through an interactive Streamlit interface.
Optimized media processing performance by integrating FFmpeg and OpenCV for efficient audio extraction and frame sampling, while implementing advanced session state management to ensure zero data loss during file operations.
Achieved robust dynamic classification of videos into six categories, enabling specialized visual-only analysis for silent content and generating downloadable text-to-speech summaries for user-ready insights.

AI Research and Sound Bite Summarization Agent (Sept 2025 – Oct 2025)

Built an AI automation agent that streamlines research and summarization by generating concise, topic-specific executive summaries and delivering them as audio files directly to users’ inboxes.
Developed a fully automated workflow connecting topic form submissions, Perplexity API–driven research, OpenAI summarization models, and TTS synthesis within the n8n automation framework.
Debugged and optimized the pipeline by correcting node mappings, implementing text chunking logic to bypass length limits, and refining LLM prompts—resulting in a robust, scalable, and production-ready system with consistent audio output.

Food Ordering Ecommerce Web Application (August 2025 - Sept 2025)

Developed a full-stack web application for a local food delivery business, featuring a responsive product catalog, detailed item pages, and a real-time updating shopping cart to enhance ordering efficiency.
Implemented secure RESTful APIs in Flask and integrated Stripe Checkout to process payments, capture customer data, and manage pickup and delivery scheduling—resulting in improved inventory tracking and reduced food wastage.
Enhanced the front-end experience with interactive elements such as toast notifications, a dynamic mini-cart dropdown, and a free-delivery threshold banner, creating a smooth, production-grade checkout flow.

Youtube Video Summarizer (April 2025 - May 2025)

Developed a Streamlit web application that summarizes YouTube videos using Google’s Gemini LLM, offering fast and readable multi-paragraph summaries.
Built a hybrid transcription system that prioritized YouTubeTranscriptAPI and seamlessly fell back to OpenAI Whisper for local audio transcription when captions were unavailable, ensuring complete video coverage.
Engineered a robust real-time summarization pipeline, including user input validation, text preprocessing, token-length handling, and full Gemini API integration.
Enabled accurate, end-to-end summarization for a wide range of video content, enhancing accessibility and saving users time through efficient content distillation.

Density-Based Smart Traffic Light Controller (Jan 2025 - March 2025)

Designed and implemented a smart 4-way traffic signal system using ESP32 and HC-SR04 ultrasonic sensors to dynamically adjust signal timings based on real-time vehicle density.
Programmed adaptive traffic logic in Embedded C within the Arduino IDE, employing signal-skipping algorithms to minimize idle green phases and reduce vehicle wait times.
Integrated the system with the Blynk IoT platform for real-time monitoring and remote control, enabling smarter intersection management.
Enhanced traffic efficiency by automating signal duration based on sensor input, resulting in smoother flow and reduced congestion.