Hi, my name is

Humza Tareen.

AI researcher & engineer.

I combine rigorous research methodology with large-scale industry experience. My published work applies attention-driven deep learning and explainable AI to medical imaging, while my industry career spans training LLMs for Apple, Meta, and Bytedance, and building agentic AI systems at production scale. I'm actively seeking PhD opportunities to deepen my contributions to AI research.

IEEE Published NCAI Researcher 1st Prize, SEECS Open House NUST — BS CS
Humza Tareen — AI Researcher
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IEEE EMBC 2025 Publication
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Prize — SEECS Open House for XAI Research
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Years Applied AI/ML Experience
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World-Class Companies' LLMs Trained
01.

Research

OptiGuard: Generalized, Attention-Driven & Explainable Glaucoma Classification

47th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2025

Syed Safi Ullah Shah, Muhammad Huzaifa, Humza Tareen, Muhammad Naseer Bajwa

1st Prize, SEECS Open House Deep Learning Explainable AI Medical Imaging Computer Vision

Glaucoma is a leading cause of irreversible blindness that demands early, accurate diagnosis. This work introduces OptiGuard, a generalized, attention-driven, and explainable system for glaucoma classification from retinal fundus images. The system employs a two-stage architecture: (1) optic disc and optic cup segmentation using Detectron2 with Mask R-CNN and a ResNet-50 backbone, validated with Average Precision metrics and computing diagnostic CDR and NRR values; (2) classification via EfficientNet-B0 with weighted sampling to handle class imbalance, trained on the SMDG-19 dataset with histogram equalization and CLAHE augmentation. Explainability is achieved through Grad-CAM, attention mechanisms, and LLM-generated reports, enabling clinicians to interpret and trust model predictions. The system achieved state-of-the-art results while maintaining clinical interpretability.

Research Interests

Explainable & Trustworthy AI

Developing models that are not only accurate but interpretable to domain experts. My published work uses Grad-CAM and attention-based explainability for clinical AI.

Computer Vision & Medical Imaging

Applying deep learning to healthcare challenges. Experience with fundus image analysis, optic disc/cup segmentation, and multi-dataset generalization.

Large Language Models

Hands-on experience training and evaluating LLMs for Apple, Meta, and Bytedance through RLHF, advanced reasoning benchmarks, and code interpreter development.

Agentic AI Systems

Architecting autonomous AI agents with RAG, tool-use, and multi-step reasoning. Building production-grade agentic backends with Python, FastAPI, and GCP.

02.

Research & Industry Experience

Deep Learning Researcher @ National Center of Artificial Intelligence (NCAI)

September 2023 — May 2024 · Islamabad, Pakistan

  • Authored a peer-reviewed paper (OptiGuard) published at the 47th IEEE EMBC on explainable AI for glaucoma detection, winning 1st Prize at the SEECS Open House.
  • Designed and implemented a two-stage deep learning pipeline: (a) Detectron2 + Mask R-CNN (ResNet-50 backbone) for optic disc/cup segmentation, (b) EfficientNet-B0 classifier with weighted sampling and CLAHE augmentation on the SMDG-19 dataset.
  • Integrated Grad-CAM and attention-based explainability with LLM-generated clinical reports, achieving state-of-the-art results with clinician-interpretable predictions.
  • Conducted under the supervision of Dr. Muhammad Naseer Bajwa.

Software Engineer @ Turing

July 2025 — Present · Palo Alto, CA (Remote)

  • Architected production microservices on GCP (Cloud Run, GKE, AlloyDB, Pub/Sub, Cloud Tasks) for an AI agent evaluation platform — including the core evaluation engine, automated LLM scoring service, RAG retrieval pipeline, and authentication gateway.
  • Designed event-driven orchestration using Pub/Sub with dead-letter queues, Cloud Tasks, and Cloud Scheduler to coordinate multi-phase evaluation workflows with independent retry and zero silent failures.
  • Led a platform-wide security audit identifying critical vulnerabilities (SQL injection, hardcoded credentials, unauthenticated endpoints) and implemented remediation using GCP Secret Manager and parameterized queries.

Pod Lead @ Turing

March 2025 — July 2025 · Palo Alto, CA (Remote)

  • Led a globally-distributed team of 10+ AI engineers across 3 continents, managing high-priority evaluation projects for key APAC clients.
  • Developed quality control frameworks and mentored team members on advanced reasoning and evaluation techniques.

LLM Python Developer @ Turing

September 2024 — March 2025 · Palo Alto, CA (Remote)

  • Developed and evaluated domain-specific LLMs for Apple, Meta, and Bytedance, specializing in RLHF, advanced reasoning, and Code Interpreter development.
  • Designed complex evaluation suites and benchmarking frameworks to ensure model performance, safety, and accuracy.

Software Engineer @ Royal Cyber Inc.

January 2025 — July 2025 · Naperville, IL

  • Fine-tuned Llama models on AWS Bedrock for domain-specific financial services copilots.
  • Co-developed the 'RC AI OPS' GenAI agent (Python, LangChain) automating error resolution, improving backend efficiency by 50%.
  • Delivered GenAI integrations for Fortune 500 clients using enterprise iPaaS platforms (Mulesoft, Salesforce) and event-driven architectures (Kafka).

Technical Trainee & Intern @ Royal Cyber Inc.

February 2024 — January 2025 · Naperville, IL

  • Built AI agents for enterprise Middleware Technologies (Mulesoft, IBM ACE/MQ, Salesforce OMS), reducing developer workloads by 60%.
  • Earned Mulesoft Certified Developer (Level 1). Delivered API integration POCs with Kafka, Flink, and external services.

Software Engineer @ Bitnine Global Inc.

March 2023 — August 2023 · Vancouver, BC, Canada

  • Contributed to the core of Apache AGE, developing methods for the 'agtype' datatype enhancing PostgreSQL graph database integration.
  • Engineered an enterprise automation framework for cross-platform product testing (Windows, CentOS, Red Hat, Debian, Ubuntu).
  • Authored technical content for developer marketing.
03.

Education & Certifications

National University of Sciences & Technology (NUST)

Bachelor of Science, Computer Science

October 2020 — June 2024

Final Year Project: OptiGuard (IEEE EMBC 2025) — Explainable deep learning for glaucoma classification. Advised by Dr. Muhammad Naseer Bajwa at NCAI.

Technical Skills

Research & ML

PyTorch Detectron2 Grad-CAM Attention Mechanisms CNNs EfficientNet Mask R-CNN RLHF LLM Evaluation

Programming & Tools

Python Scikit-Learn Pandas NumPy Matplotlib Seaborn FastAPI LangChain Git Cursor OpenAI Codex Claude Code

Data & Infrastructure

PostgreSQL Redis GCP AWS Docker Firebase RAG Pipelines

Certifications

04.

Leadership & Community

NUST ACM Student Chapter

President (June 2023 — May 2024)

Rose through 4 leadership roles over 3 years and 7 months (Executive, Team Lead Liaison, Treasurer, President). As DevFest'21 Event Head in collaboration with GDG Islamabad, organized a 50+ member team and managed an audience of 600+.

Uns-E-Mahroom

Founder (June 2021 — November 2022)

Founded a community dedicated to empowering underprivileged communities. "Uns-E-Mahroom" translates to "Love for Deprived" — focused on helping people establish their own businesses and achieve self-sustainability.

Royal Cyber Inc.

Campus Ambassador (Nov 2021 — Jun 2023)

Organized seminars on full-stack e-commerce development and Salesforce CRM. Coordinated at NUST Career Fair, conducting 50+ applicant interviews for recruitment screening.

05. What's Next?

Let's Connect

I'm actively seeking PhD opportunities in AI/ML, Computer Vision, and Healthcare AI. I bring a unique combination of peer-reviewed research and extensive industry experience building and evaluating production AI systems. I'd welcome the opportunity to discuss how my background aligns with your lab's research.

humzakhawartareen@gmail.com linkedin.com/in/humzakt github.com/humzakt
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