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<!-- ============================================
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<h1 class="hero__name">Abdul<br>Rahman</h1>
<p class="hero__tagline">AI/ML Engineer · PhD Candidate · IEEE VIS Best Paper</p>
<p class="hero__description">
I build production LLM systems and the data science pipelines behind them.
My work spans RAG pipelines, LLM fine-tuning (LoRA/QLoRA), multi-agent workflows,
predictive modeling, and interactive visual analytics, delivering 4× LLM throughput,
26% retrieval gains, and 38% hallucination reduction in production.
10+ peer-reviewed papers, 100+ citations, and prior ML experience at Amazon.
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<span class="status-badge__text">Open to AI/ML & Data Science roles · Available now</span>
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<div class="text-2xl font-semibold tracking-tight">8+</div>
<p class="text-[11px] text-white/50 mt-1">Years in ML</p>
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<div class="text-2xl font-semibold tracking-tight">10+</div>
<p class="text-[11px] text-white/50 mt-1">Publications</p>
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<p class="text-[11px] text-white/50 mt-1">Paper · IEEE VIS</p>
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</div>
<!-- Two-column: Bio + Education | Skills -->
<div class="grid grid-cols-1 lg:grid-cols-12 gap-6">
<!-- Left: Bio + Education -->
<div class="lg:col-span-7 flex flex-col gap-6 reveal-item fade-scale" style="transition-delay: 100ms">
<div class="text-sm text-white/70 leading-relaxed space-y-3 max-w-2xl">
<p>
AI/ML engineer and data scientist completing a PhD in Computer Science at
Northern Illinois University (GPA 3.9). My research spans large language models,
multimodal learning, predictive modeling, and interactive visual analytics, with
publications at IEEE VIS, TVCG, JCDL, and Scientometrics.
</p>
<p>
Before my PhD, I built data pipelines at Amazon that reduced query latency by 30%
across 500K+ daily records. At NIU, I lead the Visual Analytics Lab and build
production AI and data science systems — from RAG pipelines (82% precision@5,
−38% hallucination rate) and fine-tuned LLMs (LoRA/QLoRA, 4× throughput) to
predictive models (94.5 F1, 88 AUC) and A/B-validated deployments.
Currently building LLM-driven systems to reshape multi-view data exploration.
</p>
</div>
<!-- Education -->
<div class="rounded-xl border border-white/10 bg-white/5 p-5 flex-grow">
<div class="flex items-center gap-2 mb-3">
<i data-lucide="graduation-cap" class="w-4 h-4 text-white/70"></i>
<h3 class="text-sm font-medium tracking-tight">Education</h3>
</div>
<div class="space-y-3">
<div class="flex justify-between items-start">
<div>
<p class="text-sm font-medium">Ph.D. Computer Science</p>
<p class="text-xs text-white/50">Northern Illinois University</p>
</div>
<div class="text-right">
<p class="text-xs text-white/50">2020 – Present</p>
<p class="text-xs font-medium accent-text">GPA 3.9</p>
</div>
</div>
<div class="flex justify-between items-start">
<div>
<p class="text-sm font-medium">M.S. Computer Science</p>
<p class="text-xs text-white/50">Northern Illinois University</p>
</div>
<div class="text-right">
<p class="text-xs text-white/50">2018 – 2020</p>
<p class="text-xs font-medium accent-text">GPA 3.9</p>
</div>
</div>
<div class="flex justify-between items-start">
<div>
<p class="text-sm font-medium">B.E. Computer Science</p>
<p class="text-xs text-white/50">Osmania University, Hyderabad</p>
</div>
<div class="text-right">
<p class="text-xs text-white/50">2013 – 2017</p>
</div>
</div>
</div>
</div>
</div>
<!-- Right: Skills -->
<div class="lg:col-span-5 reveal-item fade-scale" style="transition-delay: 200ms">
<div class="rounded-2xl border border-white/10 bg-white/5 p-5 h-full">
<div class="flex items-center gap-2 mb-4">
<i data-lucide="sparkles" class="w-4 h-4 text-white/80"></i>
<h3 class="text-sm font-medium tracking-tight">Core Stack</h3>
</div>
<div class="space-y-4">
<div>
<h4 class="text-xs font-medium text-white/40 uppercase tracking-wider mb-1.5">ML & Data Science</h4>
<div class="flex flex-wrap gap-1.5">
<span class="skill-tag">PyTorch</span>
<span class="skill-tag">HuggingFace</span>
<span class="skill-tag">Scikit-learn</span>
<span class="skill-tag">XGBoost</span>
<span class="skill-tag">LoRA/QLoRA</span>
<span class="skill-tag">CLIP</span>
<span class="skill-tag">SHAP/LIME</span>
<span class="skill-tag">OpenCV</span>
<span class="skill-tag">A/B Testing</span>
<span class="skill-tag">Feature Engineering</span>
<span class="skill-tag">Statistical Modeling</span>
<span class="skill-tag">Evidently</span>
</div>
</div>
<div>
<h4 class="text-xs font-medium text-white/40 uppercase tracking-wider mb-1.5">LLM / GenAI</h4>
<div class="flex flex-wrap gap-1.5">
<span class="skill-tag">LangChain</span>
<span class="skill-tag">LangGraph</span>
<span class="skill-tag">AutoGen</span>
<span class="skill-tag">CrewAI</span>
<span class="skill-tag">FAISS</span>
<span class="skill-tag">RAG</span>
<span class="skill-tag">Ragas/TruLens</span>
<span class="skill-tag">DeepEval</span>
<span class="skill-tag">RLHF/DPO</span>
</div>
</div>
<div>
<h4 class="text-xs font-medium text-white/40 uppercase tracking-wider mb-1.5">Data & Infrastructure</h4>
<div class="flex flex-wrap gap-1.5">
<span class="skill-tag">PostgreSQL</span>
<span class="skill-tag">MongoDB</span>
<span class="skill-tag">Snowflake</span>
<span class="skill-tag">BigQuery</span>
<span class="skill-tag">Docker</span>
<span class="skill-tag">Kubernetes</span>
<span class="skill-tag">FastAPI</span>
<span class="skill-tag">MLflow</span>
<span class="skill-tag">AWS</span>
<span class="skill-tag">Kafka</span>
</div>
</div>
<div>
<h4 class="text-xs font-medium text-white/40 uppercase tracking-wider mb-1.5">Languages & Visualization</h4>
<div class="flex flex-wrap gap-1.5">
<span class="skill-tag">Python</span>
<span class="skill-tag">SQL</span>
<span class="skill-tag">JavaScript</span>
<span class="skill-tag">R</span>
<span class="skill-tag">C/C++</span>
<span class="skill-tag">Pandas</span>
<span class="skill-tag">NumPy</span>
<span class="skill-tag">D3.js</span>
<span class="skill-tag">Tableau</span>
<span class="skill-tag">Power BI</span>
<span class="skill-tag">Streamlit</span>
</div>
</div>
</div>
</div>
</div>
</div>
</section>
<!-- ============================================
3. EXPERIENCE
============================================ -->
<section id="experience" class="max-w-7xl sm:px-6 sm:mt-20 border-t border-white/10 mt-16 mx-auto pt-10 px-4 scroll-mt-24">
<h2 class="text-2xl sm:text-3xl tracking-tight mb-2 reveal-item fade-scale">Experience</h2>
<p class="text-sm mt-1 mb-8 reveal-item fade-scale" style="color: var(--color-text-secondary); transition-delay: 60ms">Research and industry, with measurable outcomes.</p>
<div class="exp-cards">
<!-- AI/ML Engineer -->
<div class="exp-card reveal-item fade-scale" style="transition-delay: 0ms">
<div>
<span class="exp-card__date">2024 – Present</span>
<span class="exp-card__location">Plano, TX (Remote)</span>
</div>
<div class="exp-card__main">
<h3 class="exp-card__title">AI/ML Engineer & Data Scientist</h3>
<p class="exp-card__org">Visual Technologies</p>
<ul class="exp-card__desc" style="list-style:none;padding:0;margin:0;display:flex;flex-direction:column;gap:0.35rem;">
<li>· Architected RAG pipelines (5K+ daily queries, AWS ECS, p95 < 900ms), improving retrieval from 61% MRR to 82% precision@5; cut hallucination rate 38% via Ragas/TruLens regression suites.</li>
<li>· Fine-tuned Llama-3-8B & Mixtral-8x7B with LoRA/QLoRA (−60% GPU memory, −45% training time); boosted inference throughput 4× via INT4/INT8 quantization and speculative decoding.</li>
<li>· Built A/B-validated predictive pipelines (0.88 R², +20% AUC) with Evidently drift monitoring and Tableau/Power BI dashboards for stakeholder self-service.</li>
</ul>
</div>
<div class="exp-card__aside">
<span class="exp-card__tag">4× LLM throughput</span>
<span class="exp-card__tag">−38% hallucinations</span>
<span class="exp-card__tag">+26% precision@5</span>
<span class="exp-card__tag">5K+ daily queries</span>
<span class="exp-card__tag">88 AUC · 0.88 R²</span>
</div>
</div>
<!-- NIU Researcher -->
<div class="exp-card reveal-item fade-scale" style="transition-delay: 0ms">
<div>
<span class="exp-card__date">2020 – 2024</span>
<span class="exp-card__location">DeKalb, IL</span>
</div>
<div class="exp-card__main">
<h3 class="exp-card__title">AI/ML Researcher</h3>
<p class="exp-card__org">Northern Illinois University · DATA Lab, VA Lab & WASTE Lab</p>
<ul class="exp-card__desc" style="list-style:none;padding:0;margin:0;display:flex;flex-direction:column;gap:0.35rem;">
<li>· Built multimodal pipelines (1M+ records, 300K+ images) using CLIP, BERTopic, and FAISS; LLM-assisted exploration system cut analyst task time 35% and improved insight accuracy 45% (25+ participants).</li>
<li>· Developed predictive models on 800K+ scholarly records (94.5 F1); benchmarked 5 model families before deploying XGBoost at 88 AUC with 20ms p95 inference.</li>
<li>· Standardized reproducible ML workflows across 3 labs, supporting 10+ peer-reviewed publications and mentoring 5+ researchers.</li>
</ul>
</div>
<div class="exp-card__aside">
<span class="exp-card__tag">1M+ records</span>
<span class="exp-card__tag">94.5 F1 · 88 AUC</span>
<span class="exp-card__tag">−35% task time</span>
<span class="exp-card__tag">10+ publications</span>
</div>
</div>
<!-- Lab Head -->
<div class="exp-card reveal-item fade-scale" style="transition-delay: 100ms">
<div>
<span class="exp-card__date">2021 – 2026</span>
<span class="exp-card__location">DeKalb, IL</span>
</div>
<div class="exp-card__main">
<h3 class="exp-card__title">Lab Head, Visual Analytics Lab</h3>
<p class="exp-card__org">Northern Illinois University</p>
<ul class="exp-card__desc" style="list-style:none;padding:0;margin:0;display:flex;flex-direction:column;gap:0.35rem;">
<li>· Leading AI-driven visualization research; mentored 6 grad students to 100% completion with 4 co-authored publications.</li>
<li>· Served as PC member at CIKM, WWW, and JCDL.</li>
</ul>
</div>
<div class="exp-card__aside">
<span class="exp-card__tag">6 mentored</span>
<span class="exp-card__tag">4 papers</span>
<span class="exp-card__tech">LLMs · ML · User Studies</span>
</div>
</div>
<!-- Research Assistant -->
<div class="exp-card reveal-item fade-scale" style="transition-delay: 80ms">
<div>
<span class="exp-card__date">2018 – 2020</span>
<span class="exp-card__location">DeKalb, IL</span>
</div>
<div class="exp-card__main">
<h3 class="exp-card__title">Research Assistant</h3>
<p class="exp-card__org">Northern Illinois University</p>
<ul class="exp-card__desc" style="list-style:none;padding:0;margin:0;display:flex;flex-direction:column;gap:0.35rem;">
<li>· Built applied-ML models for research-impact prediction integrating YouTube (180K+ videos), Twitter, and scholarly metadata; contributed to publications in Scientometrics and IEEE TVCG.</li>
<li>· Designed end-to-end pipelines (collection, cleaning, feature engineering, cross-validation) that reduced experiment iteration time ~40% across 4 concurrent projects.</li>
</ul>
</div>
<div class="exp-card__aside">
<span class="exp-card__tag">180K+ videos</span>
<span class="exp-card__tag">−40% iteration time</span>
<span class="exp-card__tech">Python · Scikit-learn · APIs</span>
</div>
</div>
<!-- Amazon -->
<div class="exp-card reveal-item fade-scale" style="transition-delay: 200ms">
<div>
<span class="exp-card__date">2016 – 2017</span>
<span class="exp-card__location">Hyderabad, India</span>
</div>
<div class="exp-card__main">
<h3 class="exp-card__title">Data Analyst</h3>
<p class="exp-card__org">Amazon</p>
<ul class="exp-card__desc" style="list-style:none;padding:0;margin:0;display:flex;flex-direction:column;gap:0.35rem;">
<li>· Reduced query latency 25–30% by optimizing SQL and MongoDB pipelines processing 500K+ daily records.</li>
<li>· Automated ETL validation with Python, Pandas, and NumPy, eliminating ~15 hours of weekly manual reconciliation.</li>
</ul>
</div>
<div class="exp-card__aside">
<span class="exp-card__tag">−30% latency</span>
<span class="exp-card__tag">500K+ daily</span>
<span class="exp-card__tech">SQL · Python · Pandas</span>
</div>
</div>
<!-- Teaching -->
<div class="exp-card reveal-item fade-scale" style="transition-delay: 300ms">
<div>
<span class="exp-card__date">2018 – 2023</span>
<span class="exp-card__location">DeKalb, IL</span>
</div>
<div class="exp-card__main">
<h3 class="exp-card__title">Teaching Assistant</h3>
<p class="exp-card__org">Northern Illinois University · ML, Algorithms, Databases, C/C++, Java</p>
<ul class="exp-card__desc" style="list-style:none;padding:0;margin:0;display:flex;flex-direction:column;gap:0.35rem;">
<li>· Led recitations, designed assignments, and graded for 40 students across 8 semesters in ML, Algorithms, Databases, C/C++, and Java.</li>
<li>· Contributed to a 20% improvement in overall class performance.</li>
</ul>
</div>
<div class="exp-card__aside">
<span class="exp-card__tag">40 students · 8 sems</span>
<span class="exp-card__tag">+20% perf</span>
</div>
</div>
</div>
</section>
<!-- ============================================
4. RESEARCH
============================================ -->
<section id="research" class="max-w-7xl sm:px-6 sm:mt-20 border-t border-white/10 mt-16 mx-auto pt-10 px-4 pb-10 scroll-mt-24">
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<!-- Left sticky content -->
<div class="w-full md:w-1/3 md:sticky md:top-[20vh] md:self-start pb-2 md:pb-20 reveal-item fade-scale">
<h2 class="text-3xl md:text-6xl font-display font-bold leading-[0.9] mb-3 md:mb-8">Research</h2>
<p class="text-neutral-400 text-sm md:text-lg leading-relaxed mb-3 md:mb-8">
Peer-reviewed work in AI, LLMs, data visualization, and scientometrics.
</p>
<!-- Filter pills -->
<div class="flex flex-wrap gap-2 mb-0 md:mb-8">
<button id="filter-selected" class="filter-btn filter-btn--active px-3 py-1.5 text-xs rounded-full font-medium transition-all duration-300" aria-pressed="true" data-filter="selected">Selected</button>
<button id="filter-published" class="filter-btn filter-btn--inactive px-3 py-1.5 text-xs rounded-full transition-all duration-300" aria-pressed="false" data-filter="published">Published</button>
<button id="filter-preprint" class="filter-btn filter-btn--inactive px-3 py-1.5 text-xs rounded-full transition-all duration-300" aria-pressed="false" data-filter="preprint">Preprints</button>
</div>
<!-- Stats -->
<div class="hidden md:grid grid-cols-3 gap-4">
<div>
<div class="text-3xl font-bold tracking-tight">10+</div>
<p class="text-xs text-white/50 mt-1">Publications</p>
</div>
<div>
<div class="text-3xl font-bold tracking-tight">100+</div>
<p class="text-xs text-white/50 mt-1">Citations</p>
</div>
<div>
<div class="text-3xl font-bold tracking-tight">3</div>
<p class="text-xs text-white/50 mt-1">In Review</p>
</div>
</div>
</div>
<!-- Right scrolling papers -->
<div id="papers-container" class="w-full md:w-2/3 flex flex-col gap-4 md:gap-8 md:pt-20">
<!-- Paper 1: YouTube and Science, SELECTED + PUBLISHED -->
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<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-blue-500/20 text-blue-400 border border-blue-500/30">Featured</span>
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-amber-500/20 text-amber-400 border border-amber-500/30">Published</span>
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-white/5 text-white/50">Scientometrics 2023</span>
</div>
<h3 class="text-xl md:text-2xl font-semibold tracking-tight mb-3 group-hover:text-amber-400 transition-colors">
<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC9734683/pdf/11192_2022_Article_4574.pdf" target="_blank" class="text-white/90 hover:text-white underline-offset-4 hover:underline">YouTube and Science: Models for Research Impact</a>
</h3>
<p class="text-sm text-white/40 mb-4"><span class="text-white/70">Abdul Rahman Shaikh</span>, Hamed Alhoori, M. Sun</p>
<p class="text-sm text-white/50 leading-relaxed mb-6">
Can YouTube videos predict a paper's real-world influence? This work introduces new datasets linking video content to scholarly articles and trains ML models that forecast citation counts and public engagement using altmetrics signals, measuring scientific impact beyond academia.
</p>
<div class="flex items-center justify-end gap-2">
<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC9734683/pdf/11192_2022_Article_4574.pdf" class="paper-link"><i data-lucide="file-text" class="w-3.5 h-3.5"></i> Paper</a>
<a href="https://github.com/sabdulrahman/YouTube" class="paper-link"><i data-lucide="github" class="w-3.5 h-3.5"></i> Code</a>
</div>
</div>
</div>
<!-- Paper 2: iTrace, SELECTED + PUBLISHED -->
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<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-amber-500/20 text-amber-400 border border-amber-500/30">Published</span>
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-white/5 text-white/50">Graphics Interface 2025</span>
</div>
<h3 class="text-xl md:text-2xl font-semibold tracking-tight mb-3 group-hover:text-amber-400 transition-colors">
<a href="https://arxiv.org/pdf/2505.23079" target="_blank" class="text-white/90 hover:text-white underline-offset-4 hover:underline">iTrace: Interactive Tracing of Cross-View Data Relationships</a>
</h3>
<p class="text-sm text-white/40 mb-4"><span class="text-white/70">Abdul Rahman Shaikh</span>, Maoyuan Sun, Xingchen Liu, Hamed Alhoori, David Koop</p>
<p class="text-sm text-white/50 leading-relaxed mb-6">
When dashboards have many linked views, finding connections between distant data points is hard. iTrace introduces smooth focus transitions that guide attention across views, making cross-view relationship tracing faster and less error-prone.
</p>
<div class="flex items-center justify-end gap-2">
<a href="https://arxiv.org/pdf/2505.23079" class="paper-link"><i data-lucide="file-text" class="w-3.5 h-3.5"></i> Paper</a>
<a href="https://github.com/sabdulrahman/iTrace" class="paper-link"><i data-lucide="github" class="w-3.5 h-3.5"></i> Code</a>
</div>
</div>
</div>
<!-- Paper 3: Systematic Design, SELECTED + PUBLISHED -->
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<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-amber-500/20 text-amber-400 border border-amber-500/30">Published</span>
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-white/5 text-white/50">IEEE VIS 2022</span>
</div>
<h3 class="text-xl md:text-2xl font-semibold tracking-tight mb-3 group-hover:text-amber-400 transition-colors">
<a href="https://arxiv.org/pdf/2207.07558" target="_blank" class="text-white/90 hover:text-white underline-offset-4 hover:underline">Toward systematic design considerations of organizing multiple views</a>
</h3>
<p class="text-sm text-white/40 mb-4"><span class="text-white/70">Abdul Rahman Shaikh</span>, David Koop, Hamed Alhoori, Maoyuan Sun</p>
<p class="text-sm text-white/50 leading-relaxed mb-6">
How should multiple visualization panels be arranged? This paper reviews dozens of multi-view systems and distills layout principles grounded in perception and content, providing a framework for designing dashboards that help users connect information across views.
</p>
<div class="flex items-center justify-end gap-2">
<a href="https://arxiv.org/pdf/2207.07558" class="paper-link"><i data-lucide="file-text" class="w-3.5 h-3.5"></i> Paper</a>
</div>
</div>
</div>
<!-- Paper 4: SightBi, SELECTED + PUBLISHED (Best Paper) -->
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<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-amber-500/20 text-amber-400 border border-amber-500/30">Published</span>
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-white/5 text-white/50">TVCG 2021</span>
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-yellow-500/20 text-yellow-400 border border-yellow-500/30">Best Paper</span>
</div>
<h3 class="text-xl md:text-2xl font-semibold tracking-tight mb-3 group-hover:text-amber-400 transition-colors">
<a href="https://arxiv.org/pdf/2108.01044" target="_blank" class="text-white/90 hover:text-white underline-offset-4 hover:underline">SightBi: Exploring Cross-View Data Relationships with Biclusters</a>
</h3>
<p class="text-sm text-white/40 mb-4">Maoyuan Sun, <span class="text-white/70">Abdul Rahman Shaikh</span>, Hamed Alhoori, Jian Zhao</p>
<p class="text-sm text-white/50 leading-relaxed mb-6">
Exploring linked data across views usually involves tedious trial-and-error. SightBi formalizes cross-view relationships as biclusters and creates dedicated relationship-views that surface hidden connections, turning guesswork into guided exploration. Awarded Best Paper Honorable Mention at IEEE VIS 2021.
</p>
<div class="flex items-center justify-end gap-2">
<a href="https://arxiv.org/pdf/2108.01044" class="paper-link"><i data-lucide="file-text" class="w-3.5 h-3.5"></i> Paper</a>
<a href="https://github.com/sabdulrahman/SightBi" class="paper-link"><i data-lucide="github" class="w-3.5 h-3.5"></i> Code</a>
</div>
</div>
</div>
<!-- Paper 5: Novelists' Styles, SELECTED + PUBLISHED -->
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<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-amber-500/20 text-amber-400 border border-amber-500/30">Published</span>
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-white/5 text-white/50">JCDL 2025</span>
</div>
<h3 class="text-xl md:text-2xl font-semibold tracking-tight mb-3 group-hover:text-amber-400 transition-colors">
<a href="https://arxiv.org/pdf/2511.20459" target="_blank" class="text-white/90 hover:text-white underline-offset-4 hover:underline">Generation, Evaluation, and Explanation of Novelists' Styles with Single-Token Prompts</a>
</h3>
<p class="text-sm text-white/40 mb-4">Mosab Rezaei, Mina Rajaei Moghadam, <span class="text-white/70">Abdul Rahman Shaikh</span>, Hamed Alhoori, Reva Freedman</p>
<p class="text-sm text-white/50 leading-relaxed mb-6">
Can you teach an LLM a novelist's writing style with a single token? This work fine-tunes language models to generate 19th-century literary styles using minimal prompts, then evaluates the output with a transformer-based detector and explainable AI analyses.
</p>
<div class="flex items-center justify-end gap-2">
<a href="https://arxiv.org/pdf/2511.20459" class="paper-link"><i data-lucide="file-text" class="w-3.5 h-3.5"></i> Paper</a>
<a href="https://github.com/mosabrezaei/Text-Generation-XAI" class="paper-link"><i data-lucide="github" class="w-3.5 h-3.5"></i> Code</a>
</div>
</div>
</div>
<!-- Paper 6: Long-term interest, PUBLISHED only -->
<div class="paper-card published reveal-item fade-scale group relative bg-white/[0.02] border border-white/10 rounded-2xl overflow-hidden hover:border-white/20 transition-all duration-500 hidden">
<div class="absolute inset-0 bg-gradient-to-br from-emerald-500/5 via-transparent to-transparent opacity-0 group-hover:opacity-100 transition-opacity duration-500"></div>
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<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-amber-500/20 text-amber-400 border border-amber-500/30">Published</span>
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-white/5 text-white/50">Journal of Informetrics 2022</span>
</div>
<h3 class="text-xl md:text-2xl font-semibold tracking-tight mb-3 group-hover:text-amber-400 transition-colors">
<a href="https://www.sciencedirect.com/science/article/abs/pii/S1751157722000402" target="_blank" class="text-white/90 hover:text-white underline-offset-4 hover:underline">Quantifying the online long-term interest in research</a>
</h3>
<p class="text-sm text-white/40 mb-4">Murtuza Shahzad, Hamed Alhoori, Reva Freedman, <span class="text-white/70">Abdul Rahman Shaikh</span></p>
<p class="text-sm text-white/50 leading-relaxed mb-6">Do some papers stay relevant for decades online while others fade? This study analyzes years of online mentions across platforms and builds ML models that predict which research will sustain public interest over time.</p>
<div class="flex items-center justify-end gap-2">
<a href="https://www.sciencedirect.com/science/article/abs/pii/S1751157722000402" target="_blank" class="paper-link"><i data-lucide="file-text" class="w-3.5 h-3.5"></i> Paper</a>
</div>
</div>
</div>
<!-- Paper 7: Youth in Policy, PUBLISHED only -->
<div class="paper-card published reveal-item fade-scale group relative bg-white/[0.02] border border-white/10 rounded-2xl overflow-hidden hover:border-white/20 transition-all duration-500 hidden">
<div class="absolute inset-0 bg-gradient-to-br from-blue-500/5 via-transparent to-transparent opacity-0 group-hover:opacity-100 transition-opacity duration-500"></div>
<div class="relative p-8">
<div class="flex items-center gap-3 mb-4 flex-wrap">
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-amber-500/20 text-amber-400 border border-amber-500/30">Published</span>
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-white/5 text-white/50">IEEE BigData 2024</span>
</div>
<h3 class="text-xl md:text-2xl font-semibold tracking-tight mb-3 group-hover:text-amber-400 transition-colors">
<a href="https://arxiv.org/abs/2501.07858" target="_blank" class="text-white/90 hover:text-white underline-offset-4 hover:underline">Examining the Representation of Youth in the US Policy Documents through the Lens of Research</a>
</h3>
<p class="text-sm text-white/40 mb-4">Miftahul Jannat Mokarrama, <span class="text-white/70">Abdul Rahman Shaikh</span>, Hamed Alhoori</p>
<p class="text-sm text-white/50 leading-relaxed mb-6">Are policymakers listening to youth-focused research? This NLP study examines how academic work about young people is cited in U.S. policy documents, revealing gaps between what researchers study and what policies prioritize.</p>
<div class="flex items-center justify-end gap-2">
<a href="https://arxiv.org/abs/2501.07858" target="_blank" class="paper-link"><i data-lucide="file-text" class="w-3.5 h-3.5"></i> Paper</a>
</div>
</div>
</div>
<!-- Paper 8: Patent Citations, PUBLISHED only -->
<div class="paper-card published reveal-item fade-scale group relative bg-white/[0.02] border border-white/10 rounded-2xl overflow-hidden hover:border-white/20 transition-all duration-500 hidden">
<div class="absolute inset-0 bg-gradient-to-br from-amber-500/5 via-transparent to-transparent opacity-0 group-hover:opacity-100 transition-opacity duration-500"></div>
<div class="relative p-8">
<div class="flex items-center gap-3 mb-4 flex-wrap">
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-amber-500/20 text-amber-400 border border-amber-500/30">Published</span>
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-white/5 text-white/50">JCDL 2019</span>
</div>
<h3 class="text-xl md:text-2xl font-semibold tracking-tight mb-3 group-hover:text-amber-400 transition-colors">
<a href="https://ieeexplore.ieee.org/abstract/document/8791120/" target="_blank" class="text-white/90 hover:text-white underline-offset-4 hover:underline">Predicting patent citations to measure economic impact of scholarly research</a>
</h3>
<p class="text-sm text-white/40 mb-4"><span class="text-white/70">Abdul Rahman Shaikh</span>, Hamed Alhoori</p>
<p class="text-sm text-white/50 leading-relaxed mb-6">How do you measure if a paper matters to industry? This work uses social media and altmetrics features to predict which academic papers will be cited by patents, providing an ML-based proxy for economic impact.</p>
<div class="flex items-center justify-end gap-2">
<a href="https://ieeexplore.ieee.org/abstract/document/8791120/" target="_blank" class="paper-link"><i data-lucide="file-text" class="w-3.5 h-3.5"></i> Paper</a>
</div>
</div>
</div>
<!-- Paper 9: Master's Thesis, PUBLISHED only -->
<div class="paper-card published reveal-item fade-scale group relative bg-white/[0.02] border border-white/10 rounded-2xl overflow-hidden hover:border-white/20 transition-all duration-500 hidden">
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<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-yellow-600/20 text-yellow-500 border border-yellow-600/30">Thesis</span>
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-white/5 text-white/50">NIU 2022</span>
</div>
<h3 class="text-xl md:text-2xl font-semibold tracking-tight mb-3 group-hover:text-amber-400 transition-colors">
<a href="https://search.proquest.com/openview/d2f17782f4f4135c177d5656fe062e3e/1" target="_blank" class="text-white/90 hover:text-white underline-offset-4 hover:underline">Modeling the Broader Impact of Science and Health Using Social Media</a>
</h3>
<p class="text-sm text-white/40 mb-4"><span class="text-white/70">Abdul Rahman Shaikh</span></p>
<p class="text-sm text-white/50 leading-relaxed mb-6">Master's thesis exploring how ML, computer vision, patent data, and social media can measure the societal, economic, and health-related impact of scientific research.</p>
<div class="flex items-center justify-end gap-2">
<a href="https://search.proquest.com/openview/d2f17782f4f4135c177d5656fe062e3e/1" target="_blank" class="paper-link"><i data-lucide="file-text" class="w-3.5 h-3.5"></i> Thesis</a>
</div>
</div>
</div>
<!-- Preprint: Boundary Blending -->
<div class="paper-card preprint reveal-item fade-scale group relative bg-white/[0.02] border border-white/10 rounded-2xl overflow-hidden hover:border-white/20 transition-all duration-500 hidden">
<div class="absolute inset-0 bg-gradient-to-br from-amber-500/5 via-transparent to-transparent opacity-0 group-hover:opacity-100 transition-opacity duration-500"></div>
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<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-green-500/20 text-green-400 border border-green-500/30">Preprint</span>
<span class="px-2.5 py-1 text-[10px] font-medium rounded-full bg-white/5 text-white/50">arXiv 2023</span>
</div>
<h3 class="text-xl md:text-2xl font-semibold tracking-tight mb-3 group-hover:text-amber-400 transition-colors">
<a href="https://arxiv.org/abs/2306.09812" target="_blank" class="text-white/90 hover:text-white underline-offset-4 hover:underline">Boundary Blending: Reconsidering the Design of Multi-View Visualizations</a>
</h3>
<p class="text-sm text-white/40 mb-4">Maoyuan Sun, <span class="text-white/70">Abdul Rahman Shaikh</span>, Yue Ma, David Koop, Hamed Alhoori</p>
<p class="text-sm text-white/50 leading-relaxed mb-6">Should visualization panels have hard edges? This work identifies three types of view boundaries (data, representation, and semantic) and analyzes four design strategies for blending them to create more fluid multi-view experiences.</p>
<div class="flex items-center justify-end gap-2">
<a href="https://arxiv.org/abs/2306.09812" target="_blank" class="paper-link"><i data-lucide="file-text" class="w-3.5 h-3.5"></i> Preprint</a>
</div>
</div>
</div>
<!-- View All -->
<div class="text-center pt-8">
<a href="https://scholar.google.com/citations?user=3nfm1N8AAAAJ&hl=en" target="_blank" rel="noopener noreferrer" class="inline-flex items-center gap-2 text-sm text-white/50 hover:text-white transition-colors group/link">
View all on Google Scholar
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</a>
</div>
</div>
</div>
</section>
<!-- ============================================
5. PROJECTS
============================================ -->
<section id="projects" class="max-w-7xl sm:px-6 sm:mt-20 border-t border-white/10 mt-16 mx-auto pt-10 px-4 pb-10 scroll-mt-24">
<div class="flex flex-col sm:flex-row sm:items-end sm:justify-between gap-4 mb-8 reveal-item fade-scale">
<div>
<h2 class="text-2xl sm:text-3xl tracking-tight">Projects</h2>
<p class="text-white/50 text-sm mt-2">Open-source tools, systems, and experiments.</p>
</div>
<a href="https://github.com/sabdulrahman" target="_blank" rel="noopener noreferrer"
class="inline-flex items-center gap-2 px-4 py-2 rounded-full bg-white/10 hover:bg-white/20 transition-colors text-sm w-fit">
<i data-lucide="github" class="w-4 h-4"></i>
<span>@sabdulrahman</span>
</a>
</div>
<!-- Project Grid (2-col on desktop, text-only cards) -->
<div class="grid grid-cols-1 md:grid-cols-2 gap-5">
<!-- Project: LLMFlow -->
<div class="project-card-text group reveal-item fade-scale" data-accent="llm" style="transition-delay: 0ms">
<div class="project-card-text__inner">
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<div class="flex items-center gap-2">
<i data-lucide="file-search" class="w-4 h-4 text-white/30 group-hover:text-[var(--card-accent)] transition-colors"></i>
<div class="flex gap-1.5">
<span class="project-tag">LLM</span>
<span class="project-tag">RAG</span>
</div>
</div>
<a href="https://github.com/sabdulrahman/LLMFlow" target="_blank" rel="noopener noreferrer" class="project-card-text__github" aria-label="View LLMFlow on GitHub">
<i data-lucide="github" class="w-4 h-4"></i>
</a>
</div>
<a href="https://github.com/sabdulrahman/LLMFlow" target="_blank" rel="noopener noreferrer">
<h3 class="text-base font-semibold tracking-tight mb-2 group-hover:text-[var(--card-accent)] transition-colors">LLMFlow: Scholarly Document Summarization & QA</h3>
</a>
<p class="text-sm text-white/50 leading-relaxed mb-4">
End-to-end pipeline that chunks scholarly PDFs, generates hierarchical summaries via Llama/Ollama and GPT, and supports multi-turn Q&A with source attribution. Evaluated retrieval quality using MRR and NDCG on annotated query sets; reduced reading time for 30+ page papers by ~60%.
</p>
<div class="flex items-center justify-between mt-auto">
<div class="flex items-center gap-2 text-[11px] text-white/35">
<span class="w-2 h-2 rounded-full bg-[#3572A5]"></span>Python · LangChain · FastAPI · React
</div>
<a href="https://github.com/sabdulrahman/LLMFlow" target="_blank" rel="noopener noreferrer" class="text-[11px] text-white/40 hover:text-white transition-colors flex items-center gap-1">
Code <i data-lucide="arrow-up-right" class="w-3 h-3"></i>
</a>
</div>
</div>
</div>
<!-- Project: Rufus -->
<div class="project-card-text group reveal-item fade-scale" data-accent="llm" style="transition-delay: 80ms">
<div class="project-card-text__inner">
<div class="flex items-center justify-between mb-3">
<div class="flex items-center gap-2">
<i data-lucide="globe" class="w-4 h-4 text-white/30 group-hover:text-[var(--card-accent)] transition-colors"></i>
<div class="flex gap-1.5">
<span class="project-tag">RAG</span>
<span class="project-tag">Crawl</span>
</div>
</div>
<a href="https://github.com/sabdulrahman/rufus" target="_blank" rel="noopener noreferrer" class="project-card-text__github" aria-label="View Rufus on GitHub">
<i data-lucide="github" class="w-4 h-4"></i>
</a>
</div>
<a href="https://github.com/sabdulrahman/rufus" target="_blank" rel="noopener noreferrer">
<h3 class="text-base font-semibold tracking-tight mb-2 group-hover:text-[var(--card-accent)] transition-colors">Rufus: Intelligent Web Data Extraction for LLMs</h3>
</a>
<p class="text-sm text-white/50 leading-relaxed mb-4">
AI-powered web crawler that navigates sites, extracts relevant content, and synthesizes it into structured documents optimized for RAG ingestion. Handles JS-rendered pages via async Selenium, cutting knowledge-base creation time by 30%.
</p>
<div class="flex items-center justify-between mt-auto">
<div class="flex items-center gap-2 text-[11px] text-white/35">
<span class="w-2 h-2 rounded-full bg-[#3572A5]"></span>Python · Asyncio · Selenium · RAG
</div>
<a href="https://github.com/sabdulrahman/rufus" target="_blank" rel="noopener noreferrer" class="text-[11px] text-white/40 hover:text-white transition-colors flex items-center gap-1">
Code <i data-lucide="arrow-up-right" class="w-3 h-3"></i>
</a>
</div>
</div>
</div>
<!-- Project: GenHealth -->
<div class="project-card-text group reveal-item fade-scale" data-accent="health" style="transition-delay: 120ms">
<div class="project-card-text__inner">
<div class="flex items-center justify-between mb-3">
<div class="flex items-center gap-2">
<i data-lucide="heart-pulse" class="w-4 h-4 text-white/30 group-hover:text-[var(--card-accent)] transition-colors"></i>
<div class="flex gap-1.5">
<span class="project-tag">Health AI</span>
<span class="project-tag">Multimodal</span>
</div>
</div>
<a href="https://github.com/sabdulrahman/GenHealth" target="_blank" rel="noopener noreferrer" class="project-card-text__github" aria-label="View GenHealth on GitHub">
<i data-lucide="github" class="w-4 h-4"></i>
</a>
</div>
<a href="https://github.com/sabdulrahman/GenHealth" target="_blank" rel="noopener noreferrer">
<h3 class="text-base font-semibold tracking-tight mb-2 group-hover:text-[var(--card-accent)] transition-colors">GenHealth: Multimodal Medical Report Analysis</h3>
</a>
<p class="text-sm text-white/50 leading-relaxed mb-4">
Multimodal AI system fusing clinical text, medical imaging (BLIP-2/CLIP), and structured EHR signals via transformer encoders and domain-specific preprocessing. Improved diagnostic-information extraction F1 by 30% in experimental evaluation.
</p>
<div class="flex items-center justify-between mt-auto">
<div class="flex items-center gap-2 text-[11px] text-white/35">
<span class="w-2 h-2 rounded-full bg-[#3572A5]"></span>Python · PyTorch · Transformers · FastAPI
</div>
<a href="https://github.com/sabdulrahman/GenHealth" target="_blank" rel="noopener noreferrer" class="text-[11px] text-white/40 hover:text-white transition-colors flex items-center gap-1">
Code <i data-lucide="arrow-up-right" class="w-3 h-3"></i>
</a>
</div>
</div>
</div>
<!-- Project: Pexos -->
<div class="project-card-text group reveal-item fade-scale" data-accent="infra" style="transition-delay: 200ms">
<div class="project-card-text__inner">
<div class="flex items-center justify-between mb-3">
<div class="flex items-center gap-2">
<i data-lucide="shield" class="w-4 h-4 text-white/30 group-hover:text-[var(--card-accent)] transition-colors"></i>
<div class="flex gap-1.5">
<span class="project-tag">Sandbox</span>
<span class="project-tag">Docker</span>
</div>
</div>
<a href="https://github.com/sabdulrahman/pexos" target="_blank" rel="noopener noreferrer" class="project-card-text__github" aria-label="View Pexos on GitHub">
<i data-lucide="github" class="w-4 h-4"></i>
</a>
</div>
<a href="https://github.com/sabdulrahman/pexos" target="_blank" rel="noopener noreferrer">
<h3 class="text-base font-semibold tracking-tight mb-2 group-hover:text-[var(--card-accent)] transition-colors">Pexos: Safe Python Execution Sandbox</h3>
</a>
<p class="text-sm text-white/50 leading-relaxed mb-4">
Secure code execution service for running untrusted Python with syscall restrictions, resource limits, and network isolation. Built for safe LLM code generation evaluation.
</p>
<div class="flex items-center justify-between mt-auto">
<div class="flex items-center gap-2 text-[11px] text-white/35">
<span class="w-2 h-2 rounded-full bg-[#3572A5]"></span>Python · Flask · nsjail · Docker
</div>
<a href="https://github.com/sabdulrahman/pexos" target="_blank" rel="noopener noreferrer" class="text-[11px] text-white/40 hover:text-white transition-colors flex items-center gap-1">
Code <i data-lucide="arrow-up-right" class="w-3 h-3"></i>
</a>
</div>
</div>
</div>
<!-- Project: ChatFit -->
<div class="project-card-text group reveal-item fade-scale" data-accent="llm" style="transition-delay: 240ms">
<div class="project-card-text__inner">
<div class="flex items-center justify-between mb-3">
<div class="flex items-center gap-2">
<i data-lucide="message-square" class="w-4 h-4 text-white/30 group-hover:text-[var(--card-accent)] transition-colors"></i>
<div class="flex gap-1.5">
<span class="project-tag">Chatbot</span>
<span class="project-tag">GPT</span>
</div>
</div>
<a href="https://github.com/sabdulrahman/ChatFit" target="_blank" rel="noopener noreferrer" class="project-card-text__github" aria-label="View ChatFit on GitHub">
<i data-lucide="github" class="w-4 h-4"></i>
</a>
</div>
<a href="https://github.com/sabdulrahman/ChatFit" target="_blank" rel="noopener noreferrer">
<h3 class="text-base font-semibold tracking-tight mb-2 group-hover:text-[var(--card-accent)] transition-colors">ChatFit: Personalized Fitness Chatbot</h3>
</a>
<p class="text-sm text-white/50 leading-relaxed mb-4">
Conversational fitness assistant that collects user goals through dialogue and generates personalized workout and diet plans using GPT with structured output parsing.
</p>
<div class="flex items-center justify-between mt-auto">
<div class="flex items-center gap-2 text-[11px] text-white/35">
<span class="w-2 h-2 rounded-full bg-[#3572A5]"></span>Python · OpenAI GPT · Streamlit · Flask
</div>
<a href="https://github.com/sabdulrahman/ChatFit" target="_blank" rel="noopener noreferrer" class="text-[11px] text-white/40 hover:text-white transition-colors flex items-center gap-1">
Code <i data-lucide="arrow-up-right" class="w-3 h-3"></i>
</a>
</div>
</div>
</div>
<!-- Project: VoxCore -->
<div class="project-card-text group reveal-item fade-scale" data-accent="cv" style="transition-delay: 320ms">
<div class="project-card-text__inner">
<div class="flex items-center justify-between mb-3">
<div class="flex items-center gap-2">
<i data-lucide="mic" class="w-4 h-4 text-white/30 group-hover:text-[var(--card-accent)] transition-colors"></i>
<div class="flex gap-1.5">
<span class="project-tag">Audio</span>
<span class="project-tag">Auth</span>
</div>
</div>
<a href="https://github.com/sabdulrahman" target="_blank" rel="noopener noreferrer" class="project-card-text__github" aria-label="View VoxCore on GitHub">
<i data-lucide="github" class="w-4 h-4"></i>
</a>