PhD Student | Senior Backend Engineer | AI Research Enthusiast | Software Architecture Designer

I'm a first-year PhD student at the intersection of agentic AI systems, software architecture, and energy-efficient AI. My research focuses on designing green, trustworthy, human-centered agentic AI systems that can reliably design software architectures.

My PhD work addresses critical gaps in how agentic AI systems are designed and evaluated:

1. Architectural Topologies & Task Mapping – How do agentic AI systems decompose software architecture design tasks, and what orchestration patterns are most effective?
2. Engineer Role Redefinition & HITL Patterns – How should human-in-the-loop integration reshape the role of software architects when working with agentic systems?
3. Vulnerabilities & Defense Mechanisms – What are the failure modes of agentic orchestrators (especially in smaller language models), and how can we build resilient systems?
4. Green Architecture Tactics & Sustainability Metrics – How can we measure and optimize energy consumption across agentic AI workflows?

• Plan Mode & Architecture Detection – How do agentic coders understand domain structure?
• HLD/LLD Generation – Bridging high-level design intent to low-level code
• Multi-Agent Frameworks:
  • Tree-sitter-based symbol graph extraction
  • PageRank over code property graphs
  • Agent orchestration patterns (ReAct, Tree-of-Thought variants)

• Budget-forcing and constrained CoT execution
• Zero-Think, LessThink, Chain-of-Draft approaches
• Lost-in-the-Middle effect mitigation (Liu et al., TACL 2024)
• Context fill ratio optimization and energy-per-token metrics

• Phi-3 Mini, Gemma-2 2B, Qwen-1.5 evaluation
• Trade-offs between model size, latency, accuracy, and energy
• Benchmarking agentic system reliability at scale constraints

Languages & Frameworks:

• Python (NumPy, Pandas, scikit-learn, Langchain, LiteLLM)
• Java EE, Spring Framework
• Django, FastAPI
• C#, C++, Roff

Tools & Platforms:

• Git / GitHub
• Zotero (academic management)
• LaTeX & Markdown (research documentation)
• n8n (workflow automation)
• Docker & containerization
• CI/CD pipelines

AI/ML Specific:

• LLM APIs: Anthropic Claude, OpenAI, DeepSeek
• CodeCarbon, NVML (energy measurement)
• BM25, dense embeddings (retrieval)
• Structured output parsing (JSON, YAML)
• MCP (Model Context Protocol) development

• Education: PhD (Ongoing), Software Architecture & Agentic AI
• Professional Experience: Senior Backend Engineer with full-stack capabilities
• Instructional Roles: Teaching and mentoring in software engineering
• Open Source: Active contributor and maintainer of research tools
• Languages: Arabic (native), English (research & technical)

• LinkedIn: in/dr-mustafa-assaf
• Twitter/X: @MKASSAF
• GitHub: mkassaf
• Email: Research inquiries welcome on LinkedIn

"The future of agentic AI in software engineering isn't about raw reasoning power—it's about honest constraints, meaningful human integration, and measurable environmental impact."

• Energy as First-Class Constraint – Not an afterthought, but a design dimension
• SLM-First Thinking – Optimize for models that most engineers can actually deploy
• Human-Centered Orchestration – HITL isn't a fallback; it's core architecture
• Vulnerability-Driven Design – Build resilience by understanding failure modes
• Reproducible Benchmarking – Architecture-specific evaluation beats one-size-fits-all metrics

I'm always interested in:

• 🤝 Joint research on agentic AI and software architecture
• 🔍 Discussions on energy-efficient AI systems
• 📊 Benchmarking agentic AI frameworks
• 📚 Building curated resources for the community
• 🎓 Mentoring and knowledge transfer

Feel free to open issues, submit PRs, or reach out on LinkedIn for research collaborations.

Last Updated: June 2026 | PhD Year 1 | Research in Progress

"In every agentic system design decision, ask: How much energy? How much human judgment? How much risk?"