Engineering, financial tech, and data analytics, inculcated at Penn State, applied across three U.S. internships, defended in code that ships.
credits at Penn State across AI, Computer Engineering, Data Sciences, IST
U.S. internships across enterprise analytics, fintech infrastructure, and university research
in leadership roles. Sustained interests in mathematics, economics, geopolitics, data analytics.
credits at Penn State across AI, Computer Engineering, Data Sciences, IST
U.S. internships across enterprise analytics, fintech infrastructure, and university research
in leadership roles. Sustained interests in mathematics, economics, geopolitics, data analytics.
Pennsylvania State University (Penn State)
B.S. Information Sciences and Technology
with special focus in Data Sciences, minor in Computer Engineering
Domains studied:
Machine LearningDistributed SystemsCalculus & Linear AlgebraProbability TheoryMicroeconomics & MacroeconomicsComputational StatisticsData StructuresDatabase SystemsComputer VisionNetwork SecurityCloud ArchitectureOperating SystemsComputer ArchitecturePrivacy, Security and Ethics in Data Science
Sustained personal study:
GeopoliticsInternational Fiscal Policy and EconomicsNLP and Financial Market AnalyticsCalculus and Probability TheoryWriting and Rhetoric
SECTION 02 / Developing;)
Architecture committed; coding my way to accomplishments. The status badges are accurate at the moment they're read and stale by the time they're acted upon. That's the nature of work.
Where the world's attention concentrates, mapped in real time.
The Arc
Target metrics ──────
Money-laundering detection that earns its complexity over the tabular baseline.
The Arc
Target metrics ──────
Cryptographic provenance for every LLM call your organisation makes.
The Arc
Target metrics ──────
An AI-native Compliance Control Room — file Reg-M, surveil trades, and stay audit-ready in one loop.
The Arc
Target metrics ──────
SECTION 03 / The Slate
Three coordinated agents — searcher, critic, writer — that produce a defensible literature review.
Synthesises ≥10-paper review in <5 min
GH ↗A 7B model that matches GPT-4 on regulatory-filing question answering.
89% F1 on 500-query held-out set
GH ↗Honest tokens-per-second-per-watt numbers for sub-7B models on consumer hardware.
≥5 models on the public leaderboard
GH ↗Six published trading strategies, replicated. Most are paper tigers.
documented survivor count after frictions
GH ↗What S&P 500 firms say about climate vs. what they spend on it.
quantified talk-walk gap, sectoral cut
GH ↗Lok Sabha debates, indexed and searchable for journalists.
Aiming 1000+ hours of speech indexed
GH ↗When two newspapers cite each other, who sources whom?
Looking 50+ outlets in the citation graph
GH ↗Supervised ML flagging early cardiovascular risk from vitals/labs — Flask REST service with automated Python+SQL ingestion, validation, and feature pipelines.
~85% classification accuracy · cross-validation + HP tuning for generalisation
GH ↗CNN for object/trace detection hardened with error-level analysis, augmentation, and noise-robust preprocessing. Led a 10-person build to a notebook → report workflow analysts could re-run.
~87% detection accuracy · packaged for repeatable analyst handoff
GH · TBDSECTION 04 / The Foundation
What the credit hours actually built.
Enumerous courses. Filling this list deliberately, only the ones whose work outlived the semester.
SECTION 05 / Journey Onward
The leadership tracks, and the recognitions that came with showing up.
A measured pause here. The roles I've held and the recognitions worth listing are deliberately unmentioned until I've had a chance to write them in my own voice.
SECTION 06 / Mind & Margin
I read, I write, I observe - I thrive
My mind reasons, My heart expresses, I put it in letter. Few live; more wait. On McCandless and Rousseau. On India's fiscal architecture.
Read them at Mind & Margin →Coffee, then code. In that order.
Reach out, let's talk. The work is the part I'm here for; everything else is logistics.
Looking for opportunities in applied AI engineering, financial-data infrastructure, and analytical journalism. Joining immediately is fine; remote, hybrid, or relocated all work. The point is to learn fast, ship things that defend themselves, and find the rooms where the next problems get framed.
Siddharth Shah · © 2026
