Neo Mohsenvand — AI/ML Engineer and Product Designer

Experience

1. CaterpillarApr 2024 – present Chief AI Architect, Global Finance since January 2026

   Chief AI Architect, Global FinanceJanuary 2026 – present · Irving, TX

   • Tempo: Built an enterprise investigation platform and designed its meeting-like interview interface, combining stakeholder discovery, scheduling and OpenAI Realtime voice interviews with structured forms. Available to hundreds of internal users for idea intake, requirements gathering and conflict resolution.
   • Aperture: Built a new agentic image-generation harness for slide decks and visual assets, using terse prompts and hundreds of references to reduce reliance on third-party subscriptions.
   • Touchless Invoice Processing agent: Co-developed end-to-end orchestration from email ingestion and scanned-invoice OCR through exception handling and Snowflake writes, with a detailed multi-level evaluation framework. Reduced invoices needing human review from 100% to 2%.
   • Teaching: Created 10+ workshop apps, including agentic RAG, talking dashboards and a voice-only data-science interface I designed. Teach engineers and senior leaders in the workshop's fifth iteration.
   • Developing shared infrastructure for AI application prototyping and deployment across Global Finance.

   Senior Principal Data Scientist, Global FinanceMay 2025 – January 2026 · Irving, TX

   • Penman: Built and deployed an enterprise financial-analysis system using SvelteKit and Azure to analyze earnings-call transcripts and regulatory filings for finance leaders.
   • Redesigned earnings-call transcript proofreading in Penman to help finance teams identify disclosure risks.
   • Built MLflow / DeepEval evaluation infrastructure and coordinated organization-wide benchmark development.
   • Built an AI-idea prioritization agent with RICE-derived scoring, internal impact metrics and human review.
   • Designed adversarial LLM analysis of draft financial disclosures.

   Senior Engineering Fellow, Artificial IntelligenceApril 2024 – May 2025 · Illinois

   • Founding technical hire of CAT Tech AI; led four engineers delivering 12+ applications for 8,000+ technical users through engineering-analysis automation.
   • Created Magic Table for million-row spreadsheet/database workflows, combining formulas and iterative local-LLM prompts to reduce cloud compute costs; developed versions with Ollama.
   • Built a ModernBERT-based embedding model for Caterpillar products and parts; orchestrated data collection, developed a synthetic training-pair generation app, and trained on an on-premises H200 cluster.
   • Led distributed training, data curation, SFT/PEFT, PPO/DPO alignment, and automated and human evaluation.
   • Established an AI curriculum and reading group across 10+ teams, training 300+ engineers.
2. BrainCoNov 2021 – Mar 2024 Head of Research · Somerville, MA
   • Led 11 researchers developing wearable AI and brain-computer interfaces; named inventor on five provisional patent applications.
   • Led development of a conditional-GAN system reconstructing breathing patterns from 25 Hz wearable PPG. The published study reports a one-second breathing-curve feedback delay and respiratory-rate mean absolute error of 1.47 breaths/min across ten test subjects.
   • Led soft-speech interface research comparing contact and MEMS microphones. In an eleven-person study, contact microphones reduced soft-speech word error rate from 99–100% to 35% in the tested music/noise conditions.
3. MIT Media LabNov 2021 – Jun 2022 Postdoctoral Research Scientist · Cambridge, MA
   • Researched multimodal memory systems and physiological data, building on doctoral work in continuous-capture memory interfaces and self-supervised EEG representations.
4. AppleJun – Sep 2021 Machine Learning Research Intern · Cupertino, CA
   • Developed parameter-efficient transformers for biosignal event detection and continuous time-series processing.
   • Built methods to inspect attention heads and activation patterns in continuous time-series models.
5. CorticoSummer 2017 Information Design & Data Visualization Intern · Cambridge, MA
   • Built a browser-based WebGL visualization engine for dynamic social-network graphs.
6. University of British ColumbiaSep 2013 – Aug 2014 Data Scientist and Researcher · Vancouver
   • Developed a Python library for retrieving, composing, and visualizing Allen Brain Atlas connectivity data in 3D.

Education

1. MITCompleted 2021 PhD, Human–AI Interaction · Media Lab
   • Completed in 2021; listed in MIT’s February 2022 degree record. Research in self-supervised learning and human–AI interaction.
   • Thesis: Classifying and Displaying Brain-Waves through Self-Supervised Learning. Advisor: Pattie Maes. Co-advisors: Tomaso Poggio and Ed Boyden.
   • First author of SeqCLR (ML4H NeurIPS Workshop, 2020), adapting contrastive learning to EEG through channel recombination and signal augmentations; evaluated emotion recognition, sleep staging, and abnormal-EEG detection across three datasets.
   • Doctoral work also included continuous-capture memory interfaces and tools for human attention.
2. University of Oxford2013 MSc, Mathematical Modelling & Scientific Computing
   • Sparse-Signal Recovery and Compressive Sensing for Optical Functional Brain Imaging.
   • Advisor: Jared Tanner. Co-advisor: Mason Porter.
3. Tehran Polytechnic2011 BSc Biomedical Engineering · BSc Electrical EngineeringPresident, IEEE Student Branch

Honours

• NTT Data Fellowship — MIT, for Rhizome, a smart memory book2020
• First place and the Koch AI Prize — MIT Grand Hack, for Memoroom, VR for Alzheimer’s2017
• Bill Mitchell Design Award — MIT Media Lab2014
• Khwarizmi Prize — first in mathematics and physics, and third the year before2006
• Semifinalist — national mathematics and physics olympiads2004

Skills

Programming

Python, TypeScript, MATLAB, Mathematica, GLSL, WGSL

Applications & UI

SvelteKit, React, Three.js / WebGL

Design & UX

Adobe Creative Cloud, UX study design, Design Systems

Cloud & data

Azure, AWS, Docker, progressive delivery, Snowflake, multimodal data pipelines

Data science

Time-series analysis, biosignal processing, feature extraction, scientific visualization

Machine learning

PyTorch, JAX, transformers, self-supervised learning, mechanistic interpretability

Training & alignment

FSDP, DeepSpeed, Ray; SFT, PEFT, LoRA, PPO / DPO, quantization

Inference & serving

Ollama, Transformers.js, WebGPU, ONNX / WASM, vLLM

Realtime AI

OpenAI Realtime, ElevenLabs, Deepgram; low-latency multithreaded harnesses

Agentic engineering

LangGraph, agent harnesses, RAG, tool orchestration, human-in-the-loop workflows

Evaluation

MLflow, DeepEval, benchmark design, automated and human evaluation

Leading & teaching

AI system architecture · cross-functional R&D · curriculum design and workshops · mentoring · technical recruiting

Languages

English · Turkish · Persian · Mandarin