Computer Engineer & 6G / Edge AI Researcher | Building gunnchOS3k MLV to end the digital divide through equitable wireless access and community-driven education.

I'm an MS Computer Engineering graduate from NYU Tandon specializing in 6G URLLC beam management, edge AI systems, and AI-native RAN controllers. As founder of gunnchOS3k MLV, I lead initiatives like WAIKE Gary UPNOW (Wireless + AI Kinesthetic Education for Gary, Indiana) to bridge the digital divide in underserved communities.

• Completing MS Computer Engineering at NYU Tandon (Dec 2025) | Focus: 6G URLLC, Secure SoC Design, Edge AI
• SpectrumX Student Competition: Building AI-native RAN controller for equitable spectrum allocation (Gary, IN focus)
• Purdue Lean Six Sigma Black Belt | Process optimization for research workflows
• Targeting 6G PhD at University of Oulu 6G Flagship or equivalent programs | Research interests: AI-native RAN, spectrum sharing, digital equity in smart societies

Mathematical Modeling | Statistical Analysis | AI-Native RAN

Developing predictive beam selection algorithms for 6G Ultra-Reliable Low-Latency Communication (URLLC) systems. Combining statistical time-series analysis, deep learning (LSTM/Transformer/GNN), and physics-based baselines to optimize mmWave beam management under mobility and blockage constraints.

• 🔬 Research: URLLC optimization, beam selection algorithms, channel modeling, sub-ms inference
• 📊 Methods: Statistical analysis, time-series modeling, deep learning, hybrid ML+physics approaches
• 🛠️ Tech: Python, MATLAB, PyTorch, Sionna, DeepMIMO
• 🚀 Applications: Autonomous vehicles, Industrial IoT, Mission-critical 6G systems

Edge AI | Real-Time Systems | Linux Engineering | Qualcomm Hackathon Winner

Real-time gesture recognition system achieving <50ms latency on ARM-based Linux systems. Features on-device ML (ONNX Runtime), voice control (Whisper ASR), and systems programming. Part of gunnchOS3k MLV's edge computing platform for low-latency, privacy-preserving applications.

• ⚡ Performance: <50ms latency, edge-optimized models, offline operation
• 🐧 Systems: Linux kernel-level optimization, systems programming, ARM architecture
• 🧠 AI: ONNX Runtime, PyTorch, Whisper ASR, Keyword Spotting
• 💻 Languages: C++, Python, Systems Programming

NASA Space Apps NYC Winner | Data Science | Edge Computing

AI-powered system predicting shark activity hotspots using NASA satellite data. Features real-time 3D visualization (Deck.gl), statistical analysis, and cloud infrastructure (Cloudflare R2, Workers). Won Best Use of Google Gemini at NASA Space Apps NYC 2025.

• 🏆 Achievement: NASA Space Apps NYC Winner - Best Use of Google Gemini
• 📊 Data Science: Statistical analysis, pattern recognition, predictive modeling with NASA MODIS/VIIRS data
• 🌐 Infrastructure: Cloudflare R2 (zero-egress), Edge Computing, Real-time Processing
• 🔬 Tech: Python, TypeScript, Machine Learning, Data Pipelines, Deck.gl

AI-Native RAN | Digital Equity | SpectrumX Competition

Designing an AI-native RAN controller for the SpectrumX Student Data & Algorithm Competition, focusing on equitable spectrum allocation for cities like Gary, Indiana. Combines contextual bandit/RL approaches with fairness constraints and spectral emission compliance.

• 🎯 Mission: Equitable spectrum allocation, digital divide reduction
• 🤖 AI: Contextual bandits, reinforcement learning, fairness-aware optimization
• 📡 Wireless: Sionna, DeepMIMO, 6G channel modeling
• 🏙️ Impact: Gary, IN digital equity focus

Cybersecurity | Automation | Enterprise Systems

Enterprise network security automation reducing manual errors by 60% and accelerating security operations. Includes threat modeling, incident response, and security controls for production systems maintaining 99.9% uptime.

• 🛡️ Security: Threat modeling, vulnerability analysis, incident response
• 🔧 Automation: Python scripting, network traffic analysis, ServiceNow integration
• 📊 Tools: Palo Alto Panorama, Splunk, Wireshark, ServiceNow
• ✅ Impact: 60% error reduction, 40% faster review cycles

Aligned with University of Oulu 6G Flagship and global 6G research priorities:

• 6G Testbeds & Smart Societies: Digital twins, edge computing infrastructure, community-driven deployments
• AI-Native RAN: Machine learning for radio resource management, beam selection, spectrum sharing
• Digital Equity: Bridging the digital divide through accessible 6G technologies, WAIKE Gary UPNOW initiative
• Spectrum Sharing & Coexistence: Dynamic spectrum access, spectral emission constraints, multi-operator coordination
• Edge AI Systems: Low-latency inference, privacy-preserving ML, on-device processing

Leading research and development for 6G wireless systems, edge AI platforms, and community education initiatives. Founded WAIKE Gary UPNOW (Wireless + AI Kinesthetic Education) to provide accessible technology education in underserved communities.

• Quantitative research and algorithm development for 6G wireless systems
• Linux-based systems engineering and infrastructure automation
• Community education initiatives serving 50+ students
• Digital divide reduction through accessible technology

Network security automation and operations for enterprise healthcare infrastructure.

• Network security automation reducing errors by 60%
• Cybersecurity operations and incident response
• Security infrastructure management and vulnerability analysis
• Production systems support maintaining 99.9% uptime

Technical instruction and curriculum development for Python, Java, data structures, and algorithms.

• Technical instruction in Python, Java, data structures, and algorithms
• Curriculum development and student support
• Mentoring students from diverse backgrounds

• 🎓 MS Computer Engineering - New York University, Tandon School of Engineering

  • Focus: 6G URLLC Beam Management, Secure SoC Design, Edge AI
  • Graduated: May 2026 | GPA: 3.4

• 🎓 BS Computer Information Technology - Purdue University

  • Graduated: December 2021 | GPA: 3.71
  • Dean's List, Lean Six Sigma Green Belt

• 6G URLLC Beam Management - Research presentation and demo (2024-Present)
• FINDS Project - NASA Space Apps NYC presentation and slides | Winner: Best Use of Google Gemini (2025)
• EdgeGesture Arcade - Qualcomm Edge AI Hackathon presentation | <50ms latency achievement (2025)
• SpectrumX AI-RAN Gary - SpectrumX Student Data & Algorithm Competition (2025-2026)

Building equitable 6G systems, securing infrastructure, and bridging the digital divide 🚀