I'm Wesley Deklich, a freshman at the University of Illinois Urbana-Champaign, pursuing a dual major in Computer Science and Economics. My academic journey is driven by a passion for leveraging technology to solve complex economic challenges.
With a strong foundation in data processing and analytics, I am particularly interested in their applications at the intersection of finance and computer science. My skills in product development and design complement my technical abilities, allowing me to approach problems with both analytical rigor and creative innovation.
I am deeply fascinated by machine learning research and its potential to revolutionize industries. My goal is to contribute to cutting-edge technologies that can drive progress in both the tech and financial sectors.
→ Immersed in hands-on experiences, lectures, and company visits across Silicon Valley
→ Generated a new business idea and assessed its profit potential, built innovative business models, and iterated toward product-market fit
→ Attended lectures and presentations from Wharton faculty, alumni, and successful entrepreneurs
→ Presented "Tessero" in front of Wharton faculty, alumni, and successful entrepreneurs
→ Won first place overall, nominated "Most likely to be the next Steve Jobs"
→ Designed and developed a scalable ticket reselling platform integrating AI-driven demand forecasting for dynamic pricing optimization
→ Implemented AWS cloud infrastructure ensuring 99.9% uptime and secure Stripe API payment processing
→ Developed a personalized recommendation algorithm to enhance user engagement and increase conversion rates
→ Developed a Random Forest model to identify network conditions that precede video quality degradation with 78% accuracy
→ Built interactive visualizations with D3.js and Tableau, enabling real-time analysis of video performance metrics
→ Optimized server architecture and data compression techniques, reducing video latency by 20% for over 1 million users
→ Developed a Bayesian Classification algorithm using TensorFlow and NumPy, improving meteorite classification accuracy by 20%
→ Analyzed 10,000+ historical meteorite impact data points, refining feature selection for more reliable classifications
→ Presented findings at AGU Fall Meeting, engaging over 25,000 attendees from 100+ countries
→ Processed, analyzed, and visualized real-time global video usage data using Python and Tableau
→ Identified performance bottlenecks in video streaming services, contributing to improved infrastructure optimizations
→ Created interactive dashboards to illustrate shifts in work-from-home trends, used by marketing and product teams
GPA: 4.0
GPA: 3.93 UW, 4.4 W (10-12), SAT: 1520
GPA: 4.0
→ Founded a nonprofit organization by filing LLC status forms and bylaws, aimed at monitoring sea turtle birth nests, tracking migration patterns, and organizing large-scale beach cleanup initiatives (62,000+ Clicks).
→ Partnered with marine conservation groups like the Isla Mujeres Marine Conservatory Group to raise awareness about climate change impacts on sea turtles and marine ecosystems.
→ Successfully raised $13,000+ in donations, allocating funds to large conservation groups and aquariums to support preservation efforts.
→ Developed the foundation's website using HTML5 and SCSS, optimizing it for mobile responsiveness and accessibility.
→ Established a Kindle reselling business leveraging Amazon FBA (Fulfillment by Amazon), handling logistics, inventory management, and automated order fulfillment.
→ Developed a full-stack web application for Kindle sales using HTML, CSS, JavaScript, and Swift, integrating real-time price tracking APIs to optimize sales strategies.
→ Implemented automated marketing campaigns to increase traffic and conversions, resulting in consistent revenue growth.
→ Developed an enterprise-grade fintech platform to facilitate secure decentralized transactions.
→ Designed and deployed a Polygon (ERC20) blockchain-based token, ensuring compliance with smart contract best practices using Solidity.
→ Integrated with UniSwap (decentralized exchange) to enable token liquidity and peer-to-peer transactions.
→ Achieved 1000 total supply, 5+ token holders, and 10+ successful transactions, showcasing real-world blockchain implementation.
→ Developed an AI-based classification model to distinguish between meteorites, craters, and ordinary landscapes using computer vision techniques .
→ Leveraged TensorRT & PyTorch to optimize real-time inference for deployment on NVIDIA Jetson Nano and other edge computing hardware.
→ Implemented a convolutional neural network (CNN) trained on high-resolution geospatial imagery to identify key morphological differences between meteorites and terrain.
→ Designed an automated drone-based scanning system, enabling researchers to survey large areas efficiently and detect potential meteorite sites.
→ Conducted data-driven research on educational inequalities in low-income communities by analyzing student performance metrics and resource allocation disparities.
→ Collaborated with school districts and policymakers to propose solutions for closing the achievement gap.
→ Published findings on ERIC.GOV (2021), contributing to ongoing educational policy discussions.
→ Built a cross-platform AI-powered note-taking app using Electron, TypeScript, and Tailwind CSS to create a lightweight yet powerful knowledge management tool.
→ Integrated TensorFlow.js-based NLP models to provide automated tagging, contextual content recommendations, and smart categorization.
→ Engineered a real-time Markdown editor with live preview and persistent storage, leveraging Electron's IPC for seamless data handling.
→ Optimized app performance to ensure low memory usage and smooth user experience across Windows, macOS, and Linux.
→ Developed an AI-powered NLP pipeline to analyze and extract insights from financial news, earnings reports, and social media discussions.
→ Implemented FinBERT and VADER sentiment analysis models, processing 500,000+ data points daily to track investor sentiment trends.
→ Designed a high-performance MongoDB schema for structured storage and retrieval, reducing query time by 30% and improving data processing efficiency.
→ Integrated FastAPI and Axios to ensure real-time API responses, maintaining 99.9% uptime for users accessing sentiment insights.