Curriculum vitae

Kanishk Paul. Kolkata.

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Research interests

Rigorous evaluation of AI systems; world models and causal induction in interactive agents; multilingual and low-resource NLP; efficient inference under tight compute.

Education

B.Tech, Computer Science and Engineering (Internet of Things and Cyber Security including Block Chain Technology), Heritage Institute of Technology, Kolkata.

National Gems Higher Secondary School, Kolkata.

Research experience

Jadavpur University, Kolkata. Research collaborator, multilingual NLP. Co-authoring a manuscript (in preparation) with Prof. Sudip Naskar and a TU Munich collaborator.

  • Built a reproducible round-trip evaluation (14 Indic languages, two translation-model families, 56,000 translations) measuring whether honorific register survives a pivot through English, on 4-bit local models and free-tier GPUs.
  • Identified a systematic deference floor: IndicTrans2 kept 99% of deferential source register (1,659/1,677) but 6% of less-deferential register (71/1,188) among classified outputs; native-speaker validation of cue tables for 12 of 14 languages is pending.
  • Showed that dedicated MT's near-zero pivot penalty is a floor artefact, since its direct path already drops almost all less-deferential register, while LLM translators lose 20–22 points through their own English pivot.
  • Wrote LLM-free, rule-based register extractors (one cue table per language) and a Unicode normalization policy that fixed four silent under-counting bugs; froze datasets behind hash checks and made every pipeline resumable and seeded.
  • Preregistered predictions before each phase and reported two that failed: the original contextual-fraction predictor did not survive robustness checks, and the target-decoder-prior test failed with a flawed metric; a corrected confirmatory re-test is preregistered.

Manuscripts in preparation

Register obstruction, with S. Naskar and a TU Munich collaborator. In preparation.

Mechanic Composition Worlds. In preparation.

Research projects

World models for ARC-AGI-3: Virgil and its predecessors, with every score and its rules.

ButterflyGate: an O(n log n) token mixer in a pretrained model's early layers.

ResonatorLM audit: an independent replication.

Earlier: NeuroSymbolic Chain of Thought, Synthesis of Thought, Debate of Thought, a photonic Shor's algorithm design, an MCMC sampler, a fee-less AI-miner blockchain, federated learning with proof-of-work. See History.

Industry and other

Unify (YC W23). Design partner. Tested a pre-release agent platform and reported reproducible gaps in OAuth permission visibility, learned-memory review, action audit trails and per-action cost attribution.

Heritage Institute of Technology. Undergraduate researcher, humanoid robotics. Wrote and defended a proposal for a low-budget assistive humanoid robot through several faculty review rounds; informal funding commitment of ₹20,000 from the department.

buildspace, Season 5. Built an offline LLM for Android that acts (messages, calls, music) solo in about three weeks.

Selected projects

Blindfold. A browser agent that redacts pages on device and sends only stand-in values through one audited exit. Co-led a six-person SIH 2026 team.

maiku. One runtime for Python functions, local LLMs, PyTorch modules, MCP servers, A2A agents, CLIs and people, through one streaming event contract.

ChromeClaw. A browser agent with one schema-validated action per step, a policy layer and a JSONL trace of every step.

ReasonTrace. A visual debugger that turns agent logs into a seven-event graph.

Sefai. Offline GGUF inference in about 150 lines of Rust.

Also: Casca, a desktop agent runner. Stockfih, Stockfish 18 in the browser. ParaReport, Kolkata civic reports. CuteTuner, a local vocal tuning studio. lifesim, a Monte Carlo life simulator. Horizon, a local decision workstation.

Earlier builds, 2020 to 2025: an answer engine, English to SQL, no-code fine-tuning, an AI music critic, a map you talk to, a speaking coach, flood and drought mapping, a deepfake detector, a university advisor, a disaster-response map, a lunar game, a multimodal assistant, trading systems. See Work.

Ventures

OpenMind. CEO.

faculza.

NashBase, with a potential co-founder.

A research collective. Wound down.

A college AI research group.

Hackathons

8 hackathon wins.

YearEventFieldResultBuilt
2023SIH 2023, college roundRunner-up, cash prizeDisaster-response platform; led the AI layer
2023NASA Space AppsUnity lunar exploration module
2024SIH 2024, college roundTop of the pitch roundDeepfake image detector
2024NSHM Innovathon100+ teams3rd, behind IIT Kharagpur and IIT KanpurUniversity advisor; owned the AI
2024MLX (GDG On Campus, inter-college, Kaggle)~908th; led both tracks for long stretchesClassification and regression
2025MLX 2.0 (GDG On Campus, Kaggle)~501stClassification and regression
2025National hackathon with investor scouting (up to ₹1 crore)Cleared the pitch round; 23rd, top 21 advancedAI music critic, built solo
2025Smart Bengal Hackathon~1,100 teamsFinalist (top ~80); about top 20Speaking coach; led the AI
2025ISRO Bharatiya Antariksh HackathonDid not reach the finalFlood and drought spread
2025SIH 2025, college qualifierWon the pitch round; qualified for nationalsCity traffic platform; led the team
2025Hack Heritage 2025~300 teamsWon the pitch round; selected for SIH nationalsEcology map platform, built solo in ~12 h
2026SIH 2026Blindfold; co-led, most commits
2026Build with Gemma Hackathon (virtual, 4 Jul)ParaReport
2026Amazon ML Challenge 2026, Business Entity Resolutiontop team 0.991483; 10th 0.9902820.988216 macro F0.5Entity matching across 2.2M businesses
2026ARC Prize 2026 (Kaggle)Account best 0.23Blackstar

Honors and selections

Google × Hugging Face Gemma meetup, 1 of 50.

DisCo Cohort 001.

PrettiFlow Cohort 2, selected 1 of 6, declined.

Thinking About Thinking Ambassador Programme.

F Inc Blueprint 2, interviewed.

Entrepreneurs First Fall 2026, interviewed.

Invited as a design partner by a startup from DeepMind founders.

Open source

unifyai/unify-agent#171, merged.

nossa-y/activity-frames#47, open.

Skills

Languages: Python, TypeScript, JavaScript, Rust, C++, SQL, Java.

ML and AI: PyTorch, TensorFlow, Hugging Face Transformers and Hub, scikit-learn, LLMs (inference, fine-tuning, evaluation), RAG, prompt engineering, machine translation (IndicTrans2, NLLB-200, FLORES-200), 4-bit quantization, state-space and post-transformer models (Mamba, RWKV, HRMs), neurosymbolic and symbolic AI, reinforcement learning, computer vision, multi-agent systems, multilingual and low-resource NLP, MLX, llama.cpp, ONNX Runtime.

Data: NumPy, pandas, SciPy, NetworkX, linear programming, benchmarking, data pipelines.

Engineering: React, Next.js, Tailwind CSS, shadcn/ui, FastAPI, Flask, Django, Node.js, Supabase and PostgreSQL, Tauri, Playwright, Streamlit, Docker, REST APIs, CI/CD, MLOps, AWS and GCP, Git, Linux, pytest, Vitest.

Practice: experimental design, preregistration, benchmark construction, paper reproduction.

Contact

kanishkpaul1729@gmail.com, GitHub, LinkedIn.