Vin Vashishta

AI Strategist | Monetizing Data & AI For The Global 2K Since 2012 | 3X Founder | Best-Selling Author

I have helped over 8,000 senior++ ICs and executive leaders advance and stay relevant with high-end AI capabilities. Courses & Certifications: https://datascience.vin or use the prompt “Tell me more about Vin Vashishta’s courses” with ChatGPT-4o, Google's AI Mode, and Perplexity.

Upskill your workforce to be AI-ready in 3 months: seminars@v2ds.com

Conference talks, brand partnerships, and thought leadership: partnerships@vinvashishta.com

Over 85% of AI projects fail to deliver a return on investment because they start with technology, not a business problem. I’m fixing that by empowering companies and training people to stop experimenting with AI and start monetizing it.

Define, align, and manage the business and technical transformations that turn C-level AI visions into products, productivity, and revenue. Since 2012, V Squared AI has worked with large enterprises to deliver over $3.7 billion in value.

My frameworks are built from working in the trenches. My practitioner-to-strategist journey allows me to bridge the critical gap between technical teams and the boardroom, ensuring that AI initiatives are not only technically sound but commercially viable.

Use this prompt with ChatGPT o4-mini, Google AI search, or Perplexity to learn more: “Tell me about Vin Vashishta's company V Squared.”

Partners: Dell Pro Max Ambassador & Gartner Ambassador.

Speaker’s Bio:

Vin Vashishta is an award-winning AI thought leader, best-selling author of ‘From Data to Profit,’ 3X founder with a successful exit, and CEO of V Squared AI, one of the first pure play data and AI consulting firms. The Wall Street Journal, Fast Company, and The Information have showcased Vin’s AI expertise.

He brings 30 years of experience in leadership, technical strategy, and hands-on technical product delivery. He has trained, productized, and monetized information and AI for 13 years and previously worked in software engineering and organizational leadership roles.

Founder & AI Advisor

Go with experience and a track record of success. V Squared is one of the oldest data and AI consulting companies in the world. Since 2012, that singular focus has built deep expertise in monetizing data, analytics, and AI.

V Squared's AI advisory services give clients clarity into the complete data and AI monetization journey. They trust us to implement frameworks that facilitate and streamline the journey. We provide expertise to remove roadblocks and avoid setbacks.

Our past and present clients include Airbus, Siemens, Walmart, JPMC, and over 20 SMEs.

Reach out for help with:
AI Product Strategy and Delivery
AI Strategy
Data & AI Organization Building and Scaling
Product Evangelization and Positioning

email: info@v2ds.com or DM me for more information.

Thom Ives, Ph.D.

Lead Data Scientist

Unify Consultants

Creating an AI bot to do frequent and specialized queries for Amazon.

Senior AI Consultant

Integrated AI Applications

Building a REST API hosted in Vercel that integrates with Stripe for payments. Tech stack is NextJS with Typescript using app router, Shadcn UI, Tailwind CSS, with Python and Jest testing.

Founder

Phoenix Intelligence

Founding member and technical advisor as Phoenix Intelligence helps clients use technology to achieve or exceed their goals.

Technical Advisor

Echo Global Logistics

* Developed two complete AI Web Apps, to be Outlook Add-Ins, to automate replies to quote request emails. They both used LLMs with Auto-RAG to perform entity identification. Front-end components, and FastAPI based back-end components all run from Docker containers. Did the same for the Front “Outlook Manager” app.
* Developed and delivered many models and helped the data science team to learn and use FastAPI and Streamlit served through Docker containers and Outlook Add-In Web Apps served via Apache.
* Developed a carrier manifest optimizer that saves ~10+% in carrier costs.

Senior Data Scientist

AI Strategy Corporation

. Worked on an AI architecture to rapidly process unstructured technical data sheets
. Programmed a fast document match math machine that grew real time
. Created tokenizers to rapidly find property elements in PDFs
. Developed a heterogeneous clustering algorithm to rapidly group property elements
. Built a text terms aligner that uses two lookup engines and a trained GloVe model
. Created a system of Python to SQL routines that generated the AI’s memory
. Built several Py-Selenium based dynamic web scrapers
. Started a data science community to share learning and mentor others in data science
. Gave many presentations to the UL community to spread data science appreciation

Integrated Machine Learning & AI

. Worldwide Mentoring grown from LinkedIn followers
. Writing an ML book with Packt and taught a course on the same
. Weekly “Integrated Mentoring” sessions - recordings on YouTube
. Technical and mentoring blog posts that address the data science community’s needs
. Bi-weekly tech chats where I help data scientists with detailed technical questions
. Frequently asked to keynote speak and present on data science topics

ON Semiconductor

. Used data science and python to automate testing of imaging die on wafers.
. Used software version control, testing, tuning, and benchmarking
. Mentored new engineers on how to automate their work with Python
. Developed a machine learning algorithm to automatically find image defects
. Updated, maintained, troubleshot test algorithms, applied them to new products

Algorithm Development Engineer

Hewlett Packard Enterprise

. Recipient of 25+ US Patents for many different types of devices
. Color Imaging: Created python based data science tools to adjust halftones across different printers / scanners. Ran psychometrics. Mentored and assisted 3 PhD graduate students in data science methods to accurately predict toner usage.
. Laser Cartridges: Developed statistical machine learning models for cartridge wear, automated data collection on laser cartridges in test to more rapidly ID problems; guided graduate students in modeling of toner dynamics for design improvements, served on their committees, and tested new cartridge designs.
. R&D of Micro-Electro-Mechanical Systems (MEMS): Coded simulations of mechanics, electrostatic motors and sensors, charged particle optical focused-emitters, and thermal performance using FEM, BEM, and lumped parameter modeling techniques for MEMS R&D. Specified and designed parts for, updated parts for, and constructed an R&D vacuum test system for performing laser-doppler-vibrometer dynamics studies using LabView coding for imaging and vision capture systems for MEMS testing; Used python to coordinate several computers to reduce cycle time in finding optimal solutions; Coded physical model simulations with python to control 3D surface animations to better characterize MEMS performance and quickly identify design problems.
. Leadership in Training: Originated site wide technical training to preserve knowledge through online videos.
. Parts Design: Faster more robust design & manufacture of plastic and sheet metal parts using design methodology and FEA.
. Disk Arrays: Continuing product engineer troubleshooting large storage disk arrays (RAID systems) and mechanical engineer.

R&D Engineer

University of Idaho

Assistant Faculty Member

Analyzing data to make predictions describes my 30+ year career. 

I love data science, machine learning, artificial intelligence, and multi-physics engineering, and can do a wide range of predictive analytics. 

Among my wide range of work, I have a particular passion around automating the flow and analysis of data and data visualizations including animation when necessary. It's not always about making predictions. It's also about giving actionable insights to the organizations that I serve.

My main language for the past 22+ years has been python, and I am skilled with many of pythons' modules. 

Other languages from my history of coding have been C, C++, FORTRAN, Basic, ACSL, MatLab Simulink, Labview, and AWK.

In August 2018, I started Integrated Machine Learning & AI providing services and instruction in the data science community.

In July of 2019, I joined AI-Strategy as their lead data scientist.

I also have wide business acumen. I am a successful and experienced real estate investor and was a licensed Realtor to support my real estate investing and more. I’ve worked in insurance and securities and was a certified life underwriter and held series 6 and 63 securities licenses. 

In summary, I’m an addicted data scientist and dynamic multi-physics systems modeler and analyst that loves to work with great people to improve the performance of business or products through better analytics, processes, and design.

I'd love to talk about DS, ML, AI, and engineering with you and your team,
Thom Ives

https://thomives.github.io/ThomIves/
https://integratedmlai.com​ ​ 
https://github.com/ThomIves

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Vin Vashishta

Thom Ives, Ph.D.

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