ROHAN DEOGAONKAR · ENGINEER
Open to internships & collaborations
I build
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One engineer across software, silicon, and markets. TY B.Tech ENTC (AI & ML) at MIT World Peace University · SIH 2025 National Finalist.
17
Projects & repos
1
Preprint
3
Certifications
4
Domains
NOW
Building CandleKit v0.2·
Researching ETF arbitrage & passive flowspress ~ for terminal
Activity
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Everything I've built.
Resume projects + every public repo, in one explorable index.
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Journey
PINNED
ALL PROJECTS
PROJECT ACTIVITY · AUG 2024 – JUL 2026
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Experience
Data Management & Voice AI Automation
Nov 2022 – Present
MTXL, Pune
Configured and trained a voice-to-text application — audio bit-rate conversion, voice-recognition training, and automated text-processing pipelines.
Sensor Research Collaborations
2025 – 2026
NICMAR University
Embedded DS18B20 sensors inside concrete to study road thermal behavior; deployed piezoelectric sensors for micro-crack detection in structural health monitoring.
Achievements & Certifications
SIH 2025
National Finalist
AI-driven precision pesticide system. Research lead; only second-year student on the team.
2020 – 2021
Published a Unity game
Independently developed and released at age 15.
ANTHROPIC · 2026
AI Fluency certifications ×2
Framework & Foundations · AI Fluency for Small Businesses. Plus AI & ML certification (2024).
Publication
PREPRINT · ZENODO · MAY 15, 2025
WILDFLOW: A Multimodal Retrieval-Augmented Academic Intelligence System
Verification-driven RAG architecture enforcing strict knowledge boundaries at the system level — replacing prompt-based hallucination control with architectural constraints.
Read the project story →
Research
ONGOING
ONGOING
MARKETS
ETF Arbitrage and Passive Flows in the Indian Stock Market
A research project studying whether the rapid growth of passive investing has begun to distort the structure of India's flagship equity index, the Nifty 50, and whether ETF mispricing carries a short-horizon predictive signal for the underlying market.
ONGOING
COGNITIVE SCIENCE
Current Self-Models in the Reconstruction of Past Episodic Detail
A conceptual review and gap analysis.
Asks whether the behavioural content of a specific remembered episode is generated from the self-model held at retrieval when that model has changed since encoding — and whether the result is experienced as recollection rather than estimation. The review separates three levels of remembered content and locates where existing theory already answers the question and where it does not.
AttributesSettled — implicit-theory and consistency-bias models (Ross, 1989).
EventsLargely covered by survey question-answering and dual-trace accounts; open only where the rememberer's own capabilities changed between encoding and retrieval.
ProcedureThe gap — no evidence, no model, and no obvious source of ground truth.
Six candidate accounts are stated at equal weight; existing evidence does not discriminate between them. No new cognitive bias is proposed.
COMPLETED
RBI × Nifty 50
Event study of 26 RBI monetary-policy events on Nifty 50 returns, 2015–2025.
IPO Price Analysis
ML regression over subscription data, RHP signals and listing performance.
GET IN TOUCH
rohandeogaonkar.9@gmail.com ↗
© 2026 Rohan Deogaonkar · Pune, India
Hand-coded as a single page · Space Grotesk · warm greys, no frameworks · Last updated July 2026