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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<title>Siril Arockiam, Ph.D. · Computational Cancer Immunogenomics</title>
<meta name="description" content="Siril Arockiam, Ph.D. builds computational systems for cancer immunogenomics, from GPU-accelerated sequence alignment to neoepitope discovery, grounded in wet-lab validation and cGMP industry experience." />
<meta name="author" content="Siril Arockiam" />
<meta property="og:title" content="Siril Arockiam, Ph.D." />
<meta property="og:description" content="Computational cancer immunogenomics: GPU-accelerated alignment, neoepitope discovery, and point-of-care diagnostics." />
<meta property="og:type" content="website" />
<meta property="og:url" content="https://siril9.github.io/" />
<meta property="og:image" content="https://siril9.github.io/assets/og-card.png" />
<meta property="og:image:width" content="1200" />
<meta property="og:image:height" content="630" />
<meta property="og:image:alt" content="Siril Arockiam, Ph.D., computational cancer immunogenomics portfolio" />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:title" content="Siril Arockiam, Ph.D." />
<meta name="twitter:description" content="Computational cancer immunogenomics: GPU-accelerated alignment, neoepitope discovery, and point-of-care diagnostics." />
<meta name="twitter:image" content="https://siril9.github.io/assets/og-card.png" />
<link rel="icon" href="data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 32 32'%3E%3Crect width='32' height='32' rx='7' fill='%230B7D6E'/%3E%3Ctext x='16' y='22' font-family='monospace' font-size='16' font-weight='700' fill='white' text-anchor='middle'%3ESA%3C/text%3E%3C/svg%3E" />
<link rel="preconnect" href="https://fonts.googleapis.com" />
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin />
<link href="https://fonts.googleapis.com/css2?family=Bricolage+Grotesque:opsz,wght@12..96,500;12..96,600;12..96,700;12..96,800&family=Hanken+Grotesk:wght@400;500;600&family=IBM+Plex+Mono:wght@400;500;600&display=swap" rel="stylesheet" />
<style>
:root {
--bg: #F6F8F7;
--surface: #FFFFFF;
--surface-2: #F0F3F1;
--ink: #10201D;
--ink-soft: #2C3B38;
--muted: #566661;
--faint: #7C8B86;
--line: #E1E7E4;
--line-strong: #CDD6D2;
--accent: #0B7D6E;
--accent-ink: #095F54;
--accent-soft: rgba(11,125,110,0.10);
--accent-line: rgba(11,125,110,0.28);
--shadow: 0 1px 2px rgba(16,32,29,0.04), 0 8px 30px rgba(16,32,29,0.05);
--maxw: 1080px;
--display: "Bricolage Grotesque", ui-sans-serif, system-ui, sans-serif;
--body: "Hanken Grotesk", ui-sans-serif, system-ui, -apple-system, sans-serif;
--mono: "IBM Plex Mono", ui-monospace, "SFMono-Regular", Menlo, monospace;
}
@media (prefers-color-scheme: dark) {
:root {
--bg: #0B110F;
--surface: #121A17;
--surface-2: #16211D;
--ink: #EAF1EE;
--ink-soft: #C9D4D0;
--muted: #93A29C;
--faint: #6E7D78;
--line: #202B27;
--line-strong: #2C3A35;
--accent: #33B8A6;
--accent-ink: #55CBBB;
--accent-soft: rgba(51,184,166,0.12);
--accent-line: rgba(51,184,166,0.30);
--shadow: 0 1px 2px rgba(0,0,0,0.30), 0 10px 34px rgba(0,0,0,0.34);
}
}
:root[data-theme="light"] {
--bg: #F6F8F7; --surface: #FFFFFF; --surface-2: #F0F3F1;
--ink: #10201D; --ink-soft: #2C3B38; --muted: #566661; --faint: #7C8B86;
--line: #E1E7E4; --line-strong: #CDD6D2;
--accent: #0B7D6E; --accent-ink: #095F54; --accent-soft: rgba(11,125,110,0.10); --accent-line: rgba(11,125,110,0.28);
--shadow: 0 1px 2px rgba(16,32,29,0.04), 0 8px 30px rgba(16,32,29,0.05);
}
:root[data-theme="dark"] {
--bg: #0B110F; --surface: #121A17; --surface-2: #16211D;
--ink: #EAF1EE; --ink-soft: #C9D4D0; --muted: #93A29C; --faint: #6E7D78;
--line: #202B27; --line-strong: #2C3A35;
--accent: #33B8A6; --accent-ink: #55CBBB; --accent-soft: rgba(51,184,166,0.12); --accent-line: rgba(51,184,166,0.30);
--shadow: 0 1px 2px rgba(0,0,0,0.30), 0 10px 34px rgba(0,0,0,0.34);
}
* { box-sizing: border-box; }
html { scroll-behavior: smooth; -webkit-text-size-adjust: 100%; }
@media (prefers-reduced-motion: reduce) { html { scroll-behavior: auto; } }
body {
margin: 0;
background: var(--bg);
color: var(--ink);
font-family: var(--body);
font-size: 17px;
line-height: 1.65;
-webkit-font-smoothing: antialiased;
text-rendering: optimizeLegibility;
overflow-x: hidden;
}
::selection { background: var(--accent-soft); color: var(--accent-ink); }
a { color: inherit; text-decoration: none; }
h1, h2, h3, h4 { font-family: var(--display); font-weight: 700; line-height: 1.08; margin: 0; letter-spacing: -0.015em; text-wrap: balance; }
p { margin: 0; }
.wrap { max-width: var(--maxw); margin: 0 auto; padding: 0 28px; }
@media (max-width: 680px) { .wrap { padding: 0 20px; } }
.eyebrow {
font-family: var(--mono); font-size: 12px; font-weight: 500;
letter-spacing: 0.18em; text-transform: uppercase; color: var(--accent-ink);
display: inline-flex; align-items: center; gap: 10px;
}
.eyebrow::before { content: ""; width: 22px; height: 1px; background: var(--accent-line); display: inline-block; }
/* ---------- top bar ---------- */
header.bar {
position: sticky; top: 0; z-index: 50;
backdrop-filter: saturate(1.4) blur(10px);
background: color-mix(in srgb, var(--bg) 82%, transparent);
border-bottom: 1px solid transparent;
transition: border-color .3s ease, background .3s ease;
}
header.bar.scrolled { border-bottom-color: var(--line); }
.bar-inner { display: flex; align-items: center; justify-content: space-between; height: 62px; }
.brand { font-family: var(--mono); font-weight: 600; font-size: 14px; letter-spacing: 0.02em; display: flex; align-items: center; gap: 10px; }
.brand .dot { width: 9px; height: 9px; border-radius: 2px; background: var(--accent); box-shadow: 0 0 0 4px var(--accent-soft); }
nav.links { display: flex; align-items: center; gap: 26px; }
nav.links a { font-family: var(--mono); font-size: 12.5px; letter-spacing: 0.04em; color: var(--muted); transition: color .18s; }
nav.links a:hover { color: var(--ink); }
@media (max-width: 780px) { nav.links a.nav-hide { display: none; } }
.theme-btn {
font-family: var(--mono); font-size: 12px; color: var(--muted);
background: transparent; border: 1px solid var(--line-strong); border-radius: 999px;
padding: 6px 12px; cursor: pointer; display: inline-flex; align-items: center; gap: 7px; transition: all .18s;
}
.theme-btn:hover { color: var(--ink); border-color: var(--accent-line); }
.theme-btn svg { width: 14px; height: 14px; }
/* ---------- hero ---------- */
.hero { position: relative; padding: 92px 0 68px; overflow: hidden; }
.hero-seq {
position: absolute; inset: 0; pointer-events: none; z-index: 0;
font-family: var(--mono); font-size: 13px; line-height: 2.1; letter-spacing: 0.32em;
color: var(--ink); opacity: 0.05; white-space: nowrap; overflow: hidden;
-webkit-user-select: none; user-select: none;
mask-image: linear-gradient(180deg, transparent, #000 22%, #000 60%, transparent);
-webkit-mask-image: linear-gradient(180deg, transparent, #000 22%, #000 60%, transparent);
}
@media (prefers-color-scheme: dark) { .hero-seq { opacity: 0.09; } }
:root[data-theme="dark"] .hero-seq { opacity: 0.09; }
:root[data-theme="light"] .hero-seq { opacity: 0.05; }
.hero-inner { position: relative; z-index: 1; }
.avail {
font-family: var(--mono); font-size: 12px; letter-spacing: 0.04em; color: var(--muted);
display: inline-flex; align-items: center; gap: 9px; margin-bottom: 26px; max-width: 100%;
border: 1px solid var(--line); background: var(--surface); border-radius: 999px; padding: 6px 14px;
}
.avail .pulse { flex: none; }
.avail .pulse { width: 8px; height: 8px; border-radius: 50%; background: var(--accent); position: relative; }
.avail .pulse::after { content: ""; position: absolute; inset: -4px; border-radius: 50%; border: 1px solid var(--accent); opacity: .5; animation: pulse 2.4s ease-out infinite; }
@keyframes pulse { 0% { transform: scale(.6); opacity: .6; } 100% { transform: scale(1.8); opacity: 0; } }
@media (prefers-reduced-motion: reduce) { .avail .pulse::after { animation: none; } }
h1.name { font-size: clamp(2.9rem, 7.4vw, 5.5rem); font-weight: 800; letter-spacing: -0.03em; line-height: 0.98; }
h1.name .last { color: var(--accent); }
.role { font-family: var(--mono); font-size: clamp(13px, 1.6vw, 15px); letter-spacing: 0.03em; color: var(--muted); margin-top: 20px; }
.thesis { font-size: clamp(1.15rem, 2.3vw, 1.5rem); line-height: 1.5; color: var(--ink-soft); max-width: 40ch; margin-top: 26px; font-weight: 400; }
.thesis strong { color: var(--ink); font-weight: 600; }
.cta-row { display: flex; flex-wrap: wrap; gap: 12px; margin-top: 34px; }
.btn {
font-family: var(--mono); font-size: 13px; font-weight: 500; letter-spacing: 0.02em;
display: inline-flex; align-items: center; gap: 9px; padding: 11px 18px; border-radius: 10px;
border: 1px solid var(--line-strong); background: var(--surface); color: var(--ink);
transition: transform .16s ease, border-color .16s ease, background .16s ease, color .16s ease;
}
.btn svg { width: 15px; height: 15px; }
.btn:hover { transform: translateY(-2px); border-color: var(--accent-line); }
.btn.primary { background: var(--accent); border-color: var(--accent); color: #fff; }
:root[data-theme="dark"] .btn.primary { color: #08120F; }
@media (prefers-color-scheme: dark) { .btn.primary { color: #08120F; } }
.btn.primary:hover { background: var(--accent-ink); border-color: var(--accent-ink); }
/* ---------- metric strip ---------- */
.metrics {
margin-top: 58px; display: grid; grid-template-columns: repeat(5, 1fr);
border: 1px solid var(--line); border-radius: 16px; overflow: hidden; background: var(--surface); box-shadow: var(--shadow);
}
.metric { padding: 22px 20px; border-right: 1px solid var(--line); min-width: 0; }
.metric .lbl, .fact .v, .card p, .pub .ptitle { overflow-wrap: anywhere; }
.metric:last-child { border-right: none; }
.metric .val { font-family: var(--display); font-weight: 700; font-size: clamp(1.5rem, 3vw, 2.05rem); letter-spacing: -0.02em; color: var(--ink); font-variant-numeric: tabular-nums; }
.metric .val .u { color: var(--accent); }
.metric .lbl { font-family: var(--mono); font-size: 11px; letter-spacing: 0.06em; text-transform: uppercase; color: var(--muted); margin-top: 8px; line-height: 1.4; }
@media (max-width: 860px) { .metrics { grid-template-columns: repeat(2, 1fr); }
.metric:nth-child(2n) { border-right: none; }
.metric { border-bottom: 1px solid var(--line); }
.metric:nth-last-child(-n+1) { border-bottom: none; }
}
@media (max-width: 520px) { .metrics { grid-template-columns: 1fr 1fr; } }
/* ---------- section scaffolding ---------- */
section { padding: 74px 0; border-top: 1px solid var(--line); }
.sec-head { margin-bottom: 42px; }
.sec-head h2 { font-size: clamp(1.7rem, 3.4vw, 2.35rem); font-weight: 700; margin-top: 16px; letter-spacing: -0.02em; }
.sec-head p.lede { color: var(--muted); max-width: 60ch; margin-top: 14px; font-size: 1.02rem; }
/* ---------- about ---------- */
.about-grid { display: grid; grid-template-columns: 1.55fr 1fr; gap: 54px; align-items: start; }
@media (max-width: 820px) { .about-grid { grid-template-columns: 1fr; gap: 36px; } }
.about-body p { color: var(--ink-soft); margin-bottom: 18px; font-size: 1.06rem; }
.about-body p:last-child { margin-bottom: 0; }
.about-body .hl { color: var(--ink); font-weight: 600; }
.facts { display: flex; flex-direction: column; gap: 0; border: 1px solid var(--line); border-radius: 14px; overflow: hidden; background: var(--surface); }
.fact { display: flex; justify-content: space-between; gap: 16px; padding: 15px 18px; border-bottom: 1px solid var(--line); }
.fact:last-child { border-bottom: none; }
.fact .k { font-family: var(--mono); font-size: 11.5px; letter-spacing: 0.05em; text-transform: uppercase; color: var(--muted); flex: none; }
.fact .v { font-size: 0.95rem; color: var(--ink); text-align: right; font-weight: 500; min-width: 0; }
@media (max-width: 520px) {
.fact { flex-direction: column; align-items: flex-start; gap: 4px; }
.fact .v { text-align: left; }
}
/* ---------- featured jump row + card hooks ---------- */
.featured { margin-top: 22px; display: flex; align-items: baseline; flex-wrap: wrap; gap: 10px 20px; }
.featured-label { font-family: var(--mono); font-size: 11px; letter-spacing: 0.16em; text-transform: uppercase; color: var(--muted); flex: none; }
.featured-links { display: flex; flex-wrap: wrap; gap: 8px 10px; }
.featured-links a {
font-family: var(--mono); font-size: 12.5px; color: var(--ink-soft);
border: 1px solid var(--line); background: var(--surface); border-radius: 999px; padding: 6px 13px;
display: inline-flex; align-items: center; gap: 7px; transition: border-color .16s ease, color .16s ease;
}
.featured-links a .ar { color: var(--accent); transition: transform .16s ease; }
.featured-links a:hover { border-color: var(--accent-line); color: var(--ink); }
.featured-links a:hover .ar { transform: translateY(2px); }
.card { scroll-margin-top: 92px; }
.card .hook { color: var(--ink); font-weight: 500; font-size: 1.05rem; line-height: 1.5; margin: -2px 0 2px; }
.card.feature .hook { font-size: 1.14rem; max-width: 48ch; }
/* ---------- toolkit chips ---------- */
.chips { display: flex; flex-wrap: wrap; gap: 8px; margin-top: 26px; }
.chip { font-family: var(--mono); font-size: 12px; color: var(--ink-soft); background: var(--surface-2); border: 1px solid var(--line); border-radius: 7px; padding: 6px 11px; }
/* ---------- projects ---------- */
.proj-grid { display: grid; grid-template-columns: 1fr 1fr; gap: 20px; }
@media (max-width: 820px) { .proj-grid { grid-template-columns: 1fr; } }
.card {
position: relative; background: var(--surface); border: 1px solid var(--line); border-radius: 16px;
padding: 26px; display: flex; flex-direction: column; gap: 14px; min-width: 0;
transition: transform .2s ease, border-color .2s ease, box-shadow .2s ease;
}
.card:hover { transform: translateY(-3px); border-color: var(--accent-line); box-shadow: var(--shadow); }
.card.feature { grid-column: span 2; }
@media (max-width: 820px) { .card.feature { grid-column: span 1; } }
.card-top { display: flex; align-items: center; justify-content: space-between; gap: 12px; }
.card-tag { font-family: var(--mono); font-size: 11px; letter-spacing: 0.08em; text-transform: uppercase; color: var(--accent-ink); }
.card-year { font-family: var(--mono); font-size: 11px; color: var(--faint); }
.card h3 { font-size: 1.32rem; font-weight: 700; letter-spacing: -0.01em; }
.card.feature h3 { font-size: 1.55rem; }
.card p.desc { color: var(--muted); font-size: 0.98rem; line-height: 1.6; }
.card .stats { display: flex; flex-wrap: wrap; gap: 18px; margin-top: 2px; }
.card .stat { display: flex; flex-direction: column; gap: 2px; }
.card .stat b { font-family: var(--display); font-weight: 700; font-size: 1.28rem; color: var(--ink); font-variant-numeric: tabular-nums; letter-spacing: -0.01em; }
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<a href="#top" class="brand"><span class="dot"></span>SIRIL AROCKIAM</a>
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<div class="avail"><span class="pulse"></span>Open to postdoctoral and industry roles · 2026</div>
<h1 class="name">Siril <span class="last">Arockiam</span><span style="color:var(--accent)">.</span></h1>
<div class="role">Ph.D. · Postdoctoral Research Scholar, Biodesign Institute, Arizona State University</div>
<p class="thesis">I build <strong>computational systems for cancer immunogenomics</strong>, from GPU-accelerated sequence alignment to neoepitope discovery, grounded in wet-lab validation and cGMP industry experience.</p>
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<div class="metrics reveal">
<div class="metric"><div class="val">95<span class="u">%</span></div><div class="lbl">Locus accuracy, GPU aligner @ 9 ms/read</div></div>
<div class="metric"><div class="val">5.98<span class="u"> nM</span></div><div class="lbl">Top neoepitope binder, HLA‑A*68:02</div></div>
<div class="metric"><div class="val"><30<span class="u"> s</span></div><div class="lbl">To call TB rifampicin resistance</div></div>
<div class="metric"><div class="val">4,324</div><div class="lbl">Saliva samples, HPV16 prevalence study</div></div>
<div class="metric"><div class="val">100<span class="u">+</span></div><div class="lbl">Molecular assays designed & validated</div></div>
</div>
<div class="featured reveal">
<span class="featured-label">Featured work</span>
<div class="featured-links">
<a href="#p-genocache">GenoCache · GPU long-read aligner <span class="ar">↓</span></a>
<a href="#p-neoepitope">HPV neoepitope pipeline <span class="ar">↓</span></a>
<a href="#p-tb">TB resistance in <30 s <span class="ar">↓</span></a>
</div>
</div>
</div>
</section>
<!-- ============ RESEARCH / ABOUT ============ -->
<section id="research">
<div class="wrap">
<div class="sec-head reveal">
<span class="eyebrow">Research</span>
<h2>Learned representations of biological sequence and structure</h2>
</div>
<div class="about-grid">
<div class="about-body reveal">
<p>My work sits at the intersection of <span class="hl">computational genomics and immunology</span>. I design methods that turn raw sequencing data into decisions: which viral integration events matter, which mutated peptides an immune system can actually see, and how to read a genome fast enough to matter in the clinic.</p>
<p>On the systems side, I built <span class="hl">GenoCache</span>, a learned-embedding alignment engine that reaches 95 percent locus accuracy at 9 ms per long read on an A100, within 0.85x of minimap2's three decades of hand-tuned heuristics. On the biology side, I built an end-to-end <span class="hl">neoepitope discovery pipeline</span> for HPV-driven cancers, and I am extending it across TCGA cohorts to ask whether integration burden and host gene expression predict survival.</p>
<p>None of it is only computational. I have run the assays, sequenced the samples, and validated in the field, and I spent two years developing vaccine potency assays under cGMP at Merck. I care about methods that survive contact with real, messy biological data.</p>
<div class="chips" aria-label="Core toolkit">
<span class="chip">PyTorch</span><span class="chip">CUDA</span><span class="chip">FAISS</span><span class="chip">HyenaDNA / DNABERT-2</span><span class="chip">scGPT</span><span class="chip">pVACtools / NetMHCpan</span><span class="chip">VIRUSBreakend / GRIDSS</span><span class="chip">Oxford Nanopore</span><span class="chip">Scanpy / Seurat</span><span class="chip">Python & R</span>
</div>
</div>
<div class="reveal">
<div class="facts">
<div class="fact"><span class="k">Focus</span><span class="v">Cancer immunogenomics & ML for genomics</span></div>
<div class="fact"><span class="k">Ph.D.</span><span class="v">Biological Design, ASU (2025)</span></div>
<div class="fact"><span class="k">Now</span><span class="v">Postdoc, Biodesign Institute</span></div>
<div class="fact"><span class="k">Industry</span><span class="v">Scientist II, Merck (cGMP)</span></div>
<div class="fact"><span class="k">Based in</span><span class="v">Tempe, Arizona</span></div>
<div class="fact"><span class="k">Patents</span><span class="v">2 filed · 2 pending</span></div>
<div class="fact"><span class="k">Publications</span><span class="v">5 peer-reviewed · 5 in review/prep</span></div>
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</section>
<!-- ============ PROJECTS ============ -->
<section id="projects">
<div class="wrap">
<div class="sec-head reveal">
<span class="eyebrow">Selected Work</span>
<h2>Projects that turn sequence into decisions</h2>
<p class="lede">Recent computational work leads off, from GPU genomics to HPV neoepitope discovery, followed by the translational diagnostics platforms behind my publications and patents. Each one shipped a working system, not just a result.</p>
</div>
<div class="proj-grid">
<!-- FEATURE: GenoCache -->
<article class="card feature reveal" id="p-genocache">
<div class="feature-inner">
<div>
<div class="card-top"><span class="card-tag">GPU Genomics · Independent</span><span class="card-year">2025–26</span></div>
<h3 style="margin-top:12px">GenoCache: learned-embedding long-read aligner</h3>
<p class="hook">A learned encoder that aligns long reads at near-minimap2 speed, no hand-tuned seeds.</p>
<p class="desc" style="margin-top:12px">A GPU-accelerated alignment engine that replaces hand-tuned seeding with a lightweight learned encoder (0.5M params, 128-D embeddings) plus FAISS vector search, DP-chaining, and edlib verification, with full SAM/CIGAR output. Built at the NVIDIA AI x Bio Hackathon and continued as independent research; awarded $15K in AWS and Modal cloud credits.</p>
<div class="stack">
<span>1D CNN encoder</span><span>FAISS / IVF-PQ</span><span>fp16 tensor-core search</span><span>numba JIT</span><span>edlib</span><span>91.8M-vector GRCh38 index</span>
</div>
</div>
<div class="stats" style="flex-direction:column;gap:16px">
<div class="stat"><b>95.0%</b><span>Locus accuracy, real ONT reads</span></div>
<div class="stat"><b>9.0 ms</b><span>Per read on A100 (0.85x minimap2)</span></div>
<div class="stat"><b>4.8x</b><span>Speedup from profiling & tuning</span></div>
</div>
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</article>
<!-- Neoepitope pipeline -->
<article class="card reveal" id="p-neoepitope">
<div class="card-top"><span class="card-tag">Immunogenomics</span><span class="card-year">2025–26</span></div>
<h3>HPV neoepitope discovery pipeline</h3>
<p class="hook">Turns HPV integration junctions into ranked, HLA-matched immunotherapy targets.</p>
<p class="desc">End-to-end pipeline from whole-genome sequencing to MHC-I binding: VIRUSBreakend/GRIDSS for integration detection, OptiType for HLA typing, pVACtools and NetMHCpan for prediction. Found 9 junction-spanning neoepitopes across HPV16/18 integration hotspots (GLI2, KLF5, MYC), plus novel E6/E7 epitopes for under-studied alleles. Now scaling to TCGA-CESC/HNSC (n>600).</p>
<div class="stats">
<div class="stat"><b>5.98 nM</b><span>Top binder, A*68:02</span></div>
<div class="stat"><b>9</b><span>Junction neoepitopes</span></div>
<div class="stat"><b>n>600</b><span>TCGA cohort scale-up</span></div>
</div>
<div class="stack"><span>WGS</span><span>pVACtools</span><span>NetMHCpan</span><span>HLA typing</span></div>
</article>
<!-- TB LAMP-Seq -->
<article class="card reveal" id="p-tb">
<div class="card-top"><span class="card-tag">Sequencing Dx</span><span class="card-year">2025–26</span></div>
<h3>Rapid TB drug-resistance detection</h3>
<p class="hook">Same-visit rifampicin-resistance calls, read straight off the sequencer.</p>
<p class="desc">LAMP amplification coupled to Oxford Nanopore MinION with an optimized rapid library prep. Detected the rifampicin-resistance mutation S450L at 66,000x depth within 30 seconds of sequencing, with sample-to-mutation in under two hours, a route to same-visit resistance profiling in low-resource settings.</p>
<div class="stats">
<div class="stat"><b><30 s</b><span>To first resistance call</span></div>
<div class="stat"><b>66,000x</b><span>Depth at S450L</span></div>
<div class="stat"><b><2 hr</b><span>Sample to answer</span></div>
</div>
<div class="stack"><span>LAMP</span><span>Nanopore MinION</span><span>rpoB / S450L</span></div>
</article>
<!-- SPRINT-HPV POC -->
<article class="card reveal">
<div class="card-top"><span class="card-tag">Point-of-Care Dx</span><span class="card-year">2020–25</span></div>
<h3>SPRINT-HPV point-of-care platform</h3>
<p class="hook">Lab-grade cervical cancer screening with no lab and no cold chain.</p>
<p class="desc">A microfluidic cartridge ($10–20/test) with a battery-powered detector ($200–300) for cervical cancer screening where cold-chain and labs are scarce. Field-validated on 150+ patient samples at AIIMS against Roche Cobas, with a multiplex LAMP assay covering 11 high-risk HPV types down to 2.5 copies/uL.</p>
<div class="stats">
<div class="stat"><b>100%</b><span>Sensitivity vs Cobas</span></div>
<div class="stat"><b>94.5%</b><span>Specificity, cervical</span></div>
<div class="stat"><b><60 min</b><span>Sample to answer</span></div>
</div>
<div class="stack"><span>Multiplex LAMP</span><span>Microfluidics</span><span>Lyophilized reagents</span><span>Field-tested</span></div>
</article>
<!-- scFM-Bench -->
<article class="card reveal">
<div class="card-top"><span class="card-tag">Single-Cell ML</span><span class="card-year">2026</span></div>
<h3>scFM-Bench: single-cell annotation benchmark</h3>
<p class="desc">A benchmark for cell-type annotation on PBMC scRNA-seq comparing reference-mapping (Seurat v5, CellTypist) against MLP baselines, with a focus on how methods behave when reference panels are small. PyTorch MLP baseline reaches 0.84 macro F1; extending to single-cell foundation models (scGPT).</p>
<div class="stats">
<div class="stat"><b>0.84</b><span>Macro F1, held-out cells</span></div>
<div class="stat"><b>scGPT</b><span>Foundation-model track</span></div>
</div>
<div class="stack"><span>Scanpy / AnnData</span><span>Seurat</span><span>CellTypist</span><span>PyTorch</span></div>
</article>
<!-- TCR-pMHC -->
<article class="card reveal">
<div class="card-top"><span class="card-tag">Structural Immunology</span><span class="card-year">2026</span></div>
<h3>TCR-pMHC structural analysis</h3>
<p class="desc">Analyzed 109 TCR-pMHC crystal structures from the PDB to map CDR-loop contact patterns at the peptide interface, confirming the P4–P8 dominant contact window. Exploring whether TCR sequence features correlate with 3D binding motifs, to push immunogenicity prediction beyond binding affinity alone.</p>
<div class="stats">
<div class="stat"><b>109</b><span>Crystal structures</span></div>
<div class="stat"><b>P4–P8</b><span>Contact window mapped</span></div>
</div>
<div class="stack"><span>PDB analysis</span><span>ChimeraX</span><span>Contact mapping</span></div>
</article>
</div>
</div>
</section>
<!-- ============ PUBLICATIONS ============ -->
<section id="publications">
<div class="wrap">
<div class="sec-head reveal">
<span class="eyebrow">Publications & IP</span>
<h2>Peer-reviewed work, patents, and preprints</h2>
</div>
<div class="pub-cols">
<div class="pub-list reveal">
<div class="pub"><span class="venue">Anal. Methods '25</span><div><span class="ptitle">Rapid On-Chip Nucleic Acid Extraction for Point-of-Care Salivary Diagnostics</span><div class="pmeta">Arockiam, S. et al. · Analytical Methods 17.21, 4321–4333</div></div></div>
<div class="pub"><span class="venue">JCO Glob. Onc '25</span><div><span class="ptitle">Portable Detection of HPV for Cervical Cancer Screening in India: Translational Considerations for Global Health</span><div class="pmeta">Nguyen, V.T., Arockiam, S., Kumar, P. et al. · JCO Global Oncology 11, e2500117</div></div></div>
<div class="pub"><span class="venue">SSRN · review</span><div><a class="ptitle" href="https://dx.doi.org/10.2139/ssrn.5456445" target="_blank" rel="noopener">Portable, Isothermal Amplification and Detection of High-Risk Human Papillomavirus</a><div class="pmeta">Arockiam, S. et al. · Preprint, in review</div></div></div>
<div class="pub"><span class="venue">Chem. Eng. R&D '21</span><div><span class="ptitle">Mixing Efficiency in Serpentine Microdevices</span><div class="pmeta">Arockiam, S. et al. · Chemical Engineering Research and Design 167, 303–317</div></div></div>
<div class="pub"><span class="venue">Biomicrofluidics '19</span><div><span class="ptitle">Effect of Electrode Configuration on Nucleic Acid Detection in Porous Interdigitated Electrodes</span><div class="pmeta">Cheng, Y.H. et al. (incl. Arockiam, S.) · Biomicrofluidics 13(6)</div></div></div>
<div class="pub"><span class="venue">IEEE HI-POCT '24</span><div><span class="ptitle">Colorimetric On-Chip Detection of HPV for Point-of-Care Settings</span><div class="pmeta">Arockiam, S. et al. · IEEE HI-POCT 2024, 1–4 (oral)</div></div></div>
</div>
<div class="reveal" style="display:flex;flex-direction:column;gap:18px">
<div class="sidebox">
<h4>Patents</h4>
<div class="item"><div class="t">Parallel LAMP assays at a single temperature using temperature-shifting agents</div><div class="s">Anderson, Knappenberger, Arockiam · US 18/694,303</div></div>
<div class="item"><div class="t">Silica-based chromatographic isolation of nucleic acid-protein complexes</div><div class="s">Anderson, Knappenberger, Arockiam · US 18/255,731</div></div>
<div class="item"><div class="t">Simple and rapid nucleic acid extraction method</div><div class="s">Arockiam et al. · Patent pending</div></div>
<div class="item"><div class="t">HR-HPV detection and genotyping by RT-LAMP</div><div class="s">Arockiam et al. · Patent pending</div></div>
</div>
<div class="sidebox">
<h4>In Preparation</h4>
<div class="item"><div class="t">HPV16 in self-collected saliva: population prevalence in Arizona</div><div class="s">n = 4,324 · manuscript in prep</div></div>
<div class="item"><div class="t">Neoepitopes from HPV-human integration junctions & novel E6/E7 epitopes</div><div class="s">Computational · in prep</div></div>
</div>
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</section>
<!-- ============ EXPERIENCE ============ -->
<section id="experience">
<div class="wrap">
<div class="sec-head reveal">
<span class="eyebrow">Trajectory</span>
<h2>Research & professional experience</h2>
</div>
<div class="timeline">
<div class="tl reveal"><div class="when">Aug 2025 – Present</div><div class="what"><h3>Postdoctoral Research Scholar</h3><div class="org">Biodesign Institute, Arizona State University</div><p>Computational genomics, translational oncology, and immunogenomics: neoepitope discovery pipelines, TB LAMP-Seq resistance detection, and high-throughput HPV screening on automated liquid handlers.</p></div></div>
<div class="tl reveal"><div class="when">Aug 2020 – Aug 2025</div><div class="what"><h3>Ph.D. · Graduate Research Assistant</h3><div class="org">Biodesign Institute, Arizona State University</div><p>Molecular diagnostics and point-of-care assay development. Dissertation on point-of-care diagnostics for early detection of HPV-driven cervical and oropharyngeal cancer. Advisors: Karen S. Anderson and Jennifer Blain Christen.</p></div></div>
<div class="tl reveal"><div class="when">Apr 2018 – Aug 2020</div><div class="what"><h3>Scientist II (Associate)</h3><div class="org">Merck & Co. · West Point, PA</div><p>Assay development and process optimization for live-attenuated VZV vaccines under cGMP. Flow cytometry potency assays, NanoString gene expression, and Quality Lead for FDA and multi-country regulatory audits.</p></div></div>
<div class="tl reveal"><div class="when">Jan 2017 – Mar 2018</div><div class="what"><h3>Research Assistant · M.S. Thesis</h3><div class="org">New Jersey Institute of Technology</div><p>Microfluidics and computational modeling: COMSOL fluid-dynamics models validated against experiment, blood-brain-barrier microdevices, and carbon-nanotube biosensors.</p></div></div>
<div class="tl reveal"><div class="when">Nov 2015 – Mar 2016</div><div class="what"><h3>Research Intern</h3><div class="org">National Institute for Research in Tuberculosis, Chennai</div><p>Developed LC-MS and RP-HPLC methods for pyrazinamide quantification in plasma for pharmacokinetic analysis (undergraduate thesis).</p></div></div>
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<span class="eyebrow">Beyond the Bench</span>
<h2>Building, funding, and translating</h2>
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<div class="bcard reveal"><div class="bt">Nucleate Arizona</div><div class="bo">Co-Founder & Director of Communications</div><p>Co-founded a student-led nonprofit accelerating biotech entrepreneurship in Arizona. Ran 10+ events for 400+ attendees, building bridges between academia and industry with AZBio and CEI.</p></div>
<div class="bcard reveal"><div class="bt">SBIR Phase I · Awarded</div><div class="bo">Grant Development · 2025</div><p>Co-led an SBIR Phase I application for point-of-care HPV detection, awarded August 2025, and contributed technical sections to multiple NIH R21 and U01 proposals.</p></div>
<div class="bcard reveal"><div class="bt">VC University · Cohort 16</div><div class="bo">Life Science Scholar · 2024</div><p>Full-tuition Life Science Scholarship for aspiring life-science investors. Venture Fellow at Laconia Capital, plus first place at the HonorHealth EHR hackathon.</p></div>
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<span class="eyebrow reveal" style="display:inline-flex;justify-content:center">Get in touch</span>
<h2 class="reveal" style="margin-top:18px">Let's build something that reads biology and acts on it.</h2>
<p class="sub reveal">I am looking for postdoctoral and industry roles in computational immuno-oncology, ML for genomics, and translational diagnostics. If your work lives at that intersection, I would love to talk.</p>
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<span class="cr">Siril Arockiam, Ph.D. · Tempe, Arizona</span>
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