I'm a passionate Applied Mathematics & Computer Science student at NJIT with a focus on AI/ML and data science. Currently conducting research on Beyond Next-Token Prediction paradigms for Large Language Models, while leading impactful community organizations.

current_focus:
  - Novel LLM architectures (intent-inference over next-token prediction)
  - Advanced transformer architectures & Graph-RAG systems
  - Model Context Protocol (MCP) implementation

collaboration:
  - AI/ML projects
  - Hackathons & competitions
  - Community tech initiatives

achievements:
  - Raised $70K for student organization
  - Led 100+ students to national conferences
  - 2x increase in student internship placements

• Advanced MLOps & Model Deployment
• Graph Neural Networks (GNNs)
• Quantum Computing Applications
• Agentic AI Systems

What it does: Real-time collaborative chat platform powered by GPT models for enhanced team ideation and brainstorming sessions.

Key Features:

• 🔄 Real-time collaborative chat with Socket.IO
• 💾 Persistent conversation threads with Supabase
• 🧠 Context-aware summarization using GPT models
• 🎭 Role-specific AI assistants with agentic design patterns
• 📊 Conversation memory for improved context understanding

Impact: Enables teams to leverage AI assistance during brainstorming while maintaining conversation context and history.

// Agentic Design Pattern
const agents = {
  facilitator: {
    role: "guide discussion",
    model: "gpt-4"
  },
  critic: {
    role: "challenge ideas",
    model: "gpt-4"
  },
  summarizer: {
    role: "synthesize insights",
    model: "gpt-3.5-turbo"
  }
}

Tech Stack:

Performance Metrics:

# Computational Complexity Reduction
classical_complexity = O(n²)
quantum_complexity = O(√n)

# Results
complexity_reduction = 75%
speedup_factor = 4x
accuracy_improvement = 12%

Tech Stack:

What it does: Quantum-enhanced financial modeling platform that leverages quantum algorithms to optimize stochastic processes.

Key Achievements:

• 🚀 75% reduction in computational complexity vs classical methods
• ⚛️ Implemented Quantum Monte Carlo simulations
• 🔍 Applied Grover's Search for portfolio optimization
• 🎯 Quantum Walks for market trend analysis
• ⚡ Parallelized stochastic modeling engine

Why it won: First practical application of quantum algorithms to real-world financial modeling, demonstrating measurable performance improvements over classical approaches.

What it does: Advanced multi-modal deep learning system that recommends music based on emotional state analysis from audio, text, and user metadata.

Architecture Highlights:

• 🎼 Audio Analysis: CNN-based mel-spectrogram processing with librosa
• 📝 Text Analysis: BERT embeddings for lyric sentiment analysis
• 🔀 Late Fusion: Neural architecture combining all modalities
• 🎯 Prediction: Seq2Seq model for personalized recommendations
• 🎧 Integration: Real-time Spotify API integration

Technical Innovation: Novel late-fusion architecture that outperforms single-modality systems by 23% in recommendation accuracy.

# Multi-Modal Architecture
class EmotionMusicModel(nn.Module):
  def __init__(self):
    self.audio_cnn = MelSpectrogramCNN()
    self.text_bert = BERTEncoder()
    self.metadata_fc = MetadataEncoder()
    self.fusion = LateFusionLayer()
    self.seq2seq = RecommendationDecoder()

  def forward(self, audio, text, meta):
    audio_feat = self.audio_cnn(audio)
    text_feat = self.text_bert(text)
    meta_feat = self.metadata_fc(meta)

    fused = self.fusion([
      audio_feat, text_feat, meta_feat
    ])

    return self.seq2seq(fused)

Tech Stack:

Society of Hispanic Professional Engineers

team_size: 20+ officers
member_base: 300+ students
funding_raised: $70,000+
conference_attendees: 100+ students

Key Achievements:

• 🤖 Built CLARA - AI Assistant for operations
  • Email management & auto-response
  • Event planning & logistics
  • Member engagement tracking
• 📈 2x increase in student internship placements
• 🎯 Led 100+ students to SHPE National Conference
• 🤝 Established partnerships with 15+ tech companies

Technologies Used: Python LangChain GPT-4 Gmail API Google Calendar API

Association of Latino Professionals For America

status: First ALPFA chapter at NJIT
focus: Non-engineering Latino professionals
partnerships: 5+ local ALPFA chapters

Key Achievements:

• 🏢 Established first professional Latino org for non-engineers
• 🌐 Built external partnerships network
  • Connected with NYC ALPFA chapters
  • Formed corporate partnerships
• 📚 Organized professional development workshops
• 🎤 Hosted industry speaker series
• 💼 Created mentorship program matching students with professionals

Impact: Expanded professional opportunities beyond engineering, creating an inclusive community for all Latino students.

Beyond Next-Token Prediction

Currently exploring novel paradigms for Large Language Models that reframe training from simple next-token prediction toward intent-inference and reasoning capabilities.

Key Areas:

• 🧠 Intent-based learning architectures
• 🔄 Interactive reasoning systems
• 📊 Multi-modal transformers
• 🎯 Context-aware embeddings

Building the Future of AI

• 🤖 CLARA 2.0: Enhanced AI assistant with advanced reasoning
• 📊 Graph-RAG Framework: Novel retrieval architecture for LLMs
• 🔗 MCP Implementations: Model Context Protocol integrations
• 🎓 ML Education Platform: Teaching AI/ML to fellow students