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<!DOCTYPE html>
<html lang="en">
<head>
<!-- Basic Meta Tags -->
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Rishikesh Sivakumar | Machine Learning | Computer Vision | NLP | Data Science | Data Analytics</title>
<!-- Meta Description and Keywords for SEO -->
<meta name="description" content="Rishikesh Sivakumar - Data Scientist specializing in Machine Learning, Computer Vision, NLP, and Data Analysis. Explore my projects and get in touch.">
<meta name="keywords" content="Rishikesh Sivakumar, Data Scientist, Machine Learning, Computer Vision, NLP, Data Analysis, Portfolio">
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<meta property="og:title" content="Rishikesh Sivakumar | Machine Learning | Computer Vision | NLP | Data Science | Data Analytics">
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]
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<link rel="stylesheet" href="style.css">
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</head>
<body>
<!-- Navigation Menu -->
<nav id="navbar">
<div class="container">
<h1 class="logo"><a href="#home">Portfolio</a></h1>
<ul id="nav-menu">
<li><a href="#home" class="current">Home</a></li>
<li><a href="#skills">Skills</a></li>
<li><a href="#work-experience">Experience</a></li>
<li><a href="#projects">Projects</a></li>
<li><a href="#education">Education</a></li>
<li><a href="#contact">Contact</a></li>
</ul>
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<i class="fas fa-bars"></i>
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<!-- Header Section with Parallax Effect -->
<header id="home">
<div class="hero-content">
<h1 class="animate__animated animate__fadeInDown">Hey There, I’m <span>Rishikesh Sivakumar</span></h1>
<p class="animate__animated animate__fadeInUp">Machine Learning | Computer Vision | NLP | Data Science | Data Analytics </p>
<a href="#contact" class="btn animate__animated animate__fadeInUp">Get in Touch</a>
</div>
</header>
<!-- Main Content -->
<main>
<!-- Skills Section -->
<section id="skills" data-aos="fade-up">
<h2>Skills</h2>
<div class="skills">
<!-- Skill 1 -->
<div class="skill" data-aos="zoom-in" data-aos-delay="100">
<i class="fas fa-code"></i>
<h3>Programming Languages</h3>
<p>Python, R, SQL, MATLAB</p>
</div>
<!-- Skill 2 -->
<div class="skill" data-aos="zoom-in" data-aos-delay="200">
<i class="fas fa-cubes"></i>
<h3>Frameworks & Libraries</h3>
<p>Scikit-learn, TensorFlow, PyTorch, Keras, OpenCV, NLTK, XGBoost, NumPy, Pandas, Matplotlib, Seaborn</p>
</div>
<!-- Skill 3 -->
<div class="skill" data-aos="zoom-in" data-aos-delay="300">
<i class="fas fa-brain"></i>
<h3>Machine Learning & Deep Learning</h3>
<p>Neural Networks (CNN, ANN, RNN, LSTM), Vision Transformers, LLMs, Time Series Forecasting, Predictive Analytics, Automation Pipelines, Generative AI </p>
</div>
<!-- Skill 4 -->
<div class="skill" data-aos="zoom-in" data-aos-delay="400">
<i class="fas fa-eye"></i>
<h3>Computer Vision</h3>
<p>Object Detection (YOLO, SSD, Faster R-CNN), Image Classification (CNN and Vision Transformers), Semantic Segmentation (UNet, Mask R-CNN), Generative AI, Medical Image Analysis, Feature Extraction, Motion Tracking, Depth Estimation</p>
</div>
<!-- Skill 5 -->
<div class="skill" data-aos="zoom-in" data-aos-delay="500">
<i class="fas fa-language"></i>
<h3>Natural Language Processing</h3>
<p>NLTK, Hugging Face Transformers, Longformer Transformers, GPT Models, BERT, RoBERTa, Text Preprocessing, Sentiment Analysis, Text Classification, Machine Translation, Chatbots, Summarization, Text generation </p>
</div>
<!-- Skill 6 -->
<div class="skill" data-aos="zoom-in" data-aos-delay="600">
<i class="fas fa-chart-line"></i>
<h3>Data Analytics & Visualization</h3>
<p>PowerBI, Excel, Matplotlib, Seaborn, Time Series Analysis, Distributions, Chi-square Analysis, Bayesian Inference, A/B Testing, Regression, Statistical Inference</p>
</div>
<!-- Skill 7 -->
<div class="skill" data-aos="zoom-in" data-aos-delay="700">
<i class="fas fa-cloud"></i>
<h3>Cloud Platforms & Tools</h3>
<p>AWS, Azure, GitHub, CI/CD Pipelines, GitLab</p>
</div>
<!-- Skill 8 -->
<div class="skill" data-aos="zoom-in" data-aos-delay="800">
<i class="fas fa-database"></i>
<h3>Data Engineering</h3>
<p> MLOps, ETL Pipelines, MySQL, Google Maps API</p>
</div>
<div class="skill" data-aos="zoom-in" data-aos-delay="900">
<i class="fas fa-building"></i>
<h3>Business Platforms & Tools</h3>
<p>CRM, ERP, Dynamics 365, Navision</p>
</div>
</div>
</section>
<!-- Work Experience Section -->
<section id="work-experience" data-aos="fade-up">
<h2>Work Experience</h2>
<div class="timeline">
<!-- Experience 1 -->
<div class="timeline-item" data-aos="fade-left" data-aos-delay="400">
<div class="timeline-icon">
<i class="fas fa-briefcase"></i>
</div>
<div class="timeline-content">
<h3>Business Intelligence Intern</h3>
<p><strong>ABS Atlantic Bearing Services (Doral, Florida)</strong> | <em>Jan 2025 – present</em></p>
<ul>
<li>Engineering AI-driven predictive models and automated ETL pipelines that optimize data workflows, reducing manual reporting time by 30% and enhancing decision-making efficiency across departments.</li>
<li>Designing advanced machine learning algorithms for anomaly detection and forecasting, leading to a 20% improvement in identifying operational risks and optimizing maintenance schedules.</li>
<li>Leveraged SQL and PowerBI dashboards to transform raw data into actionable KPIs, providing leadership with real-time insights that improved strategic planning by 15%.</li>
</ul>
</div>
</div>
<!-- Experience 2 -->
<div class="timeline-item" data-aos="fade-right" data-aos-delay="100">
<div class="timeline-icon">
<i class="fas fa-briefcase"></i>
</div>
<div class="timeline-content">
<h3>Data Analytics Intern</h3>
<p><strong>ZF Marine Propulsion Systems (Miramar, Florida)</strong> | <em>May 2024 - present</em></p>
<ul>
<li>Extracted and analyzed ZF's transmission sales data across multiple marine crafts using SQL, PowerBI and Data Analytics techniques.</li>
<li>Performed Time Series Analysis and deployed LSTM models using Python and TensorFlow, achieving inventory optimization and reducing production costs with a forecasting error of 1.5 units per quarter.</li>
<li>Enhanced ZF Ramp Assist, ZF's first Computer Vision application by integrating Google Maps API, creating a dynamic ramp database to identify high-traffic ramps and improve operational planning.</li>
<li>Developing an AI-powered chatbot system designed to send personalized emails, automate tasks, and provide real-time support to employees, aiming to boost productivity by 20%.</li>
</ul>
</div>
</div>
<!-- Experience 3 -->
<div class="timeline-item" data-aos="fade-left" data-aos-delay="200">
<div class="timeline-icon">
<i class="fas fa-briefcase"></i>
</div>
<div class="timeline-content">
<h3>Data Analytics Intern</h3>
<p><strong>ZF Wind Power</strong> | <em>Jan 2023 - Jul 2023</em></p>
<ul>
<li>Automated the detection of rare grinding burn defects (0.6% cases) using Python, Apache Spark, and machine learning pipelines, ensuring zero false negatives and minimizing production defects.</li>
<li>Built predictive models like LSTM, ARIMA, RandomForest using Time Series Analysis on 5 years of data to forecast grinding burn risks pre-production, reducing rework and improving efficiency.</li>
<li>Maintained cloud infrastructure on Microsoft Azure and optimized data engineering workflows using DevOps practices, ensuring seamless data processing and server uptime.</li>
</ul>
</div>
</div>
<!-- Experience 4 -->
<div class="timeline-item" data-aos="fade-right" data-aos-delay="300">
<div class="timeline-icon">
<i class="fas fa-briefcase"></i>
</div>
<div class="timeline-content">
<h3>Computer Vision Intern</h3>
<p><strong>Samsung R&D</strong> | <em>Feb 2022 - Sep 2022</em></p>
<ul>
<li>Engineered a real-time video deblurring solution using Python, PyTorch, and DeblurGAN, reducing motion blur during live video calls within 50 nanoseconds on Samsung mobile devices.</li>
<li>Developed and optimized the deblurring pipeline into a lightweight TFLite API, ensuring seamless integration as a feature in Samsung phones while maintaining minimal CPU and memory usage.</li>
<li>Enhanced video quality and user experience by achieving 20% improvement in visual clarity, contributing to higher customer satisfaction and potential feature adoption in premium models.</li>
</ul>
</div>
</div>
</div>
<div class="timeline-item" data-aos="fade-left" data-aos-delay="200">
<div class="timeline-icon">
<i class="fas fa-briefcase"></i>
</div>
<div class="timeline-content">
<h3>Machine Learning Intern</h3>
<p><strong>Nanyang Technological University</strong> | <em>May 2022 - Jul 2022</em></p>
<ul>
<li>Built an end-to-end pipeline using Python to extract seismic data from seismographs, convert them into waveforms, and accurately detect P-wave onset for early seismic event detection.</li>
<li>Developed and trained neural network models with Time Series Analysis, improving earthquake occurrence prediction accuracy above 80%, aiding in proactive disaster response strategies.</li>
<li>Enhanced seismic monitoring systems by automating real-time data processing and P-wave detection, reducing manual analysis time and supporting faster decision-making in risk management.</li>
</ul>
</div>
</div>
<div class="timeline-item" data-aos="fade-left" data-aos-delay="200">
<div class="timeline-icon">
<i class="fas fa-briefcase"></i>
</div>
<div class="timeline-content">
<h3>Full Stack Intern</h3>
<p><strong>HighRadius</strong> | <em>Jan 2022 - Apr 2022</em></p>
<ul>
<li>Designed and implemented a B2B Fintech cloud application capable of predicting loan repayment durations and delays with 87% accuracy using optimized XGBoost models.</li>
<li>Evaluated and compared multiple machine learning algorithms, enhancing prediction precision and reducing forecasting errors by 15% over baseline models.</li>
<li>Streamlined credit risk assessments by automating repayment forecasts, enabling faster decision-making and improving financial planning for lending institutions.</li>
</ul>
</div>
</div>
<div class="timeline-item" data-aos="fade-left" data-aos-delay="200">
<div class="timeline-icon">
<i class="fas fa-briefcase"></i>
</div>
<div class="timeline-content">
<h3>Data Science Intern</h3>
<p><strong>MaxByte Technologies</strong> | <em>Jun 2021 - Dec 2021</em></p>
<ul>
<li>Developed a predictive model using LSTM and Time Series Analysis to estimate the Remaining Useful Lifetime (RUL) of machine components with an accuracy of 90%</li>
<li>Applied PCA-based Dimensionality Reduction to optimize model training on large, high-dimensional datasets, reducing computational overhead by 30%.</li>
<li>Enabled proactive maintenance scheduling by providing real-time RUL predictions, minimizing downtime and preventing unexpected machine failures.</li>
</ul>
</div>
</div>
</section>
<section id="projects" data-aos="fade-up">
<h2>Projects</h2>
<div class="projects-container">
<!-- Project 1 -->
<div class="project-item">
<h3 class="project-heading">Glaucoma Detection through Multi-Modal Integration of Retinal Images and Clinical Biomarkers</h3>
<div class="project-image">
<img src="retina.jpg" alt="Project Image">
</div>
<div class="project-details">
<p><em>Research Project - Dr.Anita Penkova (USC Big Data in Biotransport Center)</em></p>
<p>Paper published in "Engineering Applications of Artificial Intelligence" journal (Elsevier)</p>
<ul>
<li>Developed a comprehensive hybrid model that integrates Vision Transformers and CNN blocks to detect glaucoma from retinal scan images.</li>
<li>The final multi-model architecture combines both images and biomarkers using fusion techniques to better detect glaucoma.</li>
<li>Our Swin Transformer makes prediction with a test accuracy of 99.4% detecting 2857 out of 2874 patients’ data correctly.</li>
</ul>
<a href="https://www.sciencedirect.com/science/article/abs/pii/S0952197625000107" class="btn" target="_blank">Read More</a>
</div>
</div>
<!-- Project 2 -->
<div class="project-item">
<h3 class="project-heading">Patent Claims Generation from US Patent Office Data Using Long-T5</h3>
<div class="project-image">
<img src="slide_6_image.png" alt="Project Image">
</div>
<div class="project-details">
<p><em>Academic Project - Dr.Xuezhe Ma</em></p>
<p>Developed a novel approach to generate legally tailored patent claims by fine-tuning Google's LongT5 transformer model on a large corpus of patent data.</p>
<ul>
<li>Fine-tuned the LongT5 transformer on 16,000 patents using PyTorch, enabling domain-specific adaptation for legal patent claim generation.</li>
<li>Integrated Low-Rank Adaptation and Parameter-Efficient Fine-Tuning techniques to reduce trainable parameters and improve computational efficiency.</li>
<li>Outperformed baseline models with a 4-point and 1.5-point increase in BLEU score over fine-tuned T5 and GPT-3.5, and 10-15 point higher ROUGE scores compared to traditional approaches.</li>
</ul>
<a href="https://github.com/rishusiva/Patent-Claims-Generation-from-US-Patent-Office-Data" class="btn" target="_blank">Read More</a>
</div>
</div>
<div class="project-item">
<h3 class="project-heading">MindMapAI – Multi-Modal Emotion Detection Diary Application</h3>
<div class="project-image">
<img src="mindmapAI.jpeg" alt="Project Image">
</div>
<div class="project-details">
<p><em>Academic Project - Dr.Dani Yogatama</em></p>
<p>Created an Emotion Detection Diary Application using Transformers and custom CNNs to analyze both texts and images providing tailored mental health recommendations based on user entries.</p>
<ul>
<li>Developed facial image emotion classifier powered by VGG16, trained on FER2013 dataset, achieving 90.33% accuracy rate in classifying 7 emotions.</li>
<li>Fine-tuned RoBERTa on GoEmotions dataset for multi-label classification in text across 14 emotions, achieving 10% performance improvement over baseline models.</li>
</ul>
<a href="https://github.com/rishusiva/emotion-classification" class="btn" target="_blank">Read More</a>
</div>
</div>
<div class="project-item">
<h3 class="project-heading">Depth Prediction through Object Detection to Facilitate Navigation for the Visually Impaired</h3>
<div class="project-image">
<img src="blindaid.png" alt="Project Image">
</div>
<div class="project-details">
<p><em>Research Project - Dr. C. Jothi Kumar</em></p>
<p>Paper presented in "Eighth International Conference on Information System Design and Intelligent Applications" and published in Springer</p>
<ul>
<li>Developed an automated navigation system through Computer Vision to assist the visually impaired people to navigate their environments independently.</li>
<li>Used Object Detection (YOLO) and Depth Estimation to detect the objects in front of the visual aid system.</li>
<li>Used a voice alert command system with PYTTSX3 to notify the user if an object is closer than 6 feet from the visually impaired individual.</li>
</ul>
<a href="https://link.springer.com/chapter/10.1007/978-981-97-4895-2_40" class="btn" target="_blank">Read More</a>
</div>
</div>
<div class="project-item">
<h3 class="project-heading">Graph Based Recommendation System using NetworkX and Girvan Newman Algorithm</h3>
<div class="project-image">
<img src="SNAP.jpg" alt="Project Image">
</div>
<div class="project-details">
<p><em>HackRx Hackathon - Bajaj Finserv</em></p>
<p>Finalist (Top 30) of Pan-India Hackathon HackRx conducted by Bajaj Finserv for their problem statement SNAP Recommendation System</p>
<ul>
<li>Engineered a graph-based recommendation engine using Girvan-Newman Algorithm, identifying communities of frequently co-purchased items from Amazon’s SNAP dataset, improving product suggestions through hierarchical community detection on directed subgraphs.</li>
<li>Enhanced e-commerce strategies by developing modular recommendation systems for Books, DVDs, Videos, and Music-CDs, leveraging graph analytics to recommend co-purchased items.</li>
<li>Boosted product visibility for retailers by integrating transaction data and meta-data features, enabling prediction of top-level and second-level co-purchases, effectively prioritizing items for targeted recommendations and sales growth.</li>
</ul>
<a href="https://github.com/rishusiva/Turing_Twins_HackRx_3.0" class="btn" target="_blank">Read More</a>
</div>
</div>
<div class="project-item">
<h3 class="project-heading">TrashOverflow - Computer Vision Based Trash Monitoring System</h3>
<div class="project-image">
<img src="trash.png" alt="Project Image">
</div>
<div class="project-details">
<p><em>Mindspark 2.0 Hackathon - University of Southern California</em></p>
<p>Secured Third Place in Mindspark 2.0 Hackathon hosted at University of Southern California. </p>
<ul>
<li>Engineered a custom CNN architecture for waste overflow detection, achieving a test accuracy of 80% by leveraging data augmentation techniques for real-world generalization.</li>
<li>Implemented an end-to-end workflow including data scraping, preprocessing, and augmentation using KNIME and Python, processing large datasets to optimize model performance and real-world deployment.</li>
<li>Developed an interactive GUI for end-user engagement, allowing real-time waste bin classification as clean or overflowing, with potential applications for city-wide waste management optimization.</li>
</ul>
<a href="https://github.com/rishusiva/TrashOverflow" class="btn" target="_blank">Read More</a>
</div>
</div>
</section>
<!-- Education Section -->
<section id="education" data-aos="fade-up">
<h2>Education</h2>
<div class="education-container">
<!-- Education 1 -->
<div class="education-item" data-aos="flip-left" data-aos-delay="100">
<i class="fas fa-graduation-cap"></i>
<h3>Master of Science in Computer Science</h3>
<p><strong>University of Southern California</strong> | <em>Aug 2023 - May 2025</em></p>
<p>Autonomous Cyber-Physical Systems, Deep Learning and its Applications, Machine Learning, Applied Natural Language Processing,
Foundations of AI, Predictive Analytics, Analysis of Algorithms</p>
</div>
<!-- Education 2 -->
<div class="education-item" data-aos="flip-right" data-aos-delay="200">
<i class="fas fa-graduation-cap"></i>
<h3>Bachelor of Technology in Computer Science</h3>
<p><strong>SRM Institute of Science and Technology</strong> | <em>July 2019 - May 2023</em></p>
<p>Pattern Recognition Techniques, Digital Image Processing, Applied Data Science with Venture Application, Data Mining and Analytics, Artificial Intelligence, Database Management Systems, Machine Learning - Core Concepts with Applications</p>
</div>
</div>
</section>
<!-- Contact Section -->
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<h2>Contact Me</h2>
<div class="contact-container">
<div class="contact-info">
<p><i class="fas fa-map-marker-alt"></i> Los Angeles, CA 90007</p>
<p><i class="fas fa-phone"></i> +1 (323) 864-8852</p>
<p><i class="fas fa-envelope"></i>
<a href="mailto:[email protected]">[email protected]</a>
</p>
<div class="social-links">
<a href="https://www.linkedin.com/in/rishikesh-s/" aria-label="LinkedIn"><i class="fab fa-linkedin-in"></i></a>
<a href="https://github.com/rishusiva" aria-label="GitHub"><i class="fab fa-github"></i></a>
<a href="https://scholar.google.com/citations?user=by3N8AgAAAAJ&hl=en&oi=ao" aria-label="Google Scholar" target="_blank">
<i class="fas fa-graduation-cap"></i>
</a>
</div>
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<p>© 2025 Rishikesh Sivakumar | All Rights Reserved.</p>
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AOS.init({
duration: 800,
easing: 'slide',
once: true,
});
</script>
</body>
</html>