Divyansh Lohia

I’m the Co-Founder & CEO of Katalyst, a New York City-based startup where we’re building AI agents for enterprise sales teams. Our mission is simple: make every account executive dramatically more effective by giving them an AI colleague that understands their pipeline, surfaces what matters and automates admin. 
With a computer science background from Cornell and experience across cloud observability and GTM at companies operating at massive scale, I’ve seen firsthand how much revenue teams lose to slow complex sales admin and manual prep. Katalyst was born to fix this.

At Katalyst, we’re obsessed with clarity, speed, and impact. We take the most painful parts of selling - prep, research, messaging, CRM scribing, meeting readiness and automate the complexity behind the scenes. Our AI agents do the work so sellers can focus on what actually moves revenue.

If you ship fast and want to build something category defining, come help us push the boundaries of AI for enterprise sales workflows.

Co-Founder & CEO

Building a Direct-to-Consumer brand that makes lifestyle products ethically & sustainably. 

If you would like to work in setting the standard on how High Achievers live and move, please reach out!

Apple

Machine Learning Engineer

Anheuser-Busch InBev

Data Scientist

Product Management Intern

Cornell University

Degree: Master of Engineering in Computer Science
Awards: Cornell Tech Merit Scholarship

Masters Student

ServiceNow

♦ Platform UX Engineering Team: Development and maintenance of platform features
♦ Developed feature to identify labels for attachments with object recognition and machine learning (Named Entity Recognition), enabling hits in search results for image and text uploads. Framework used: OpenNLP (Java)
♦ Winner, Mini Project Hackathon, ServiceNow 2018

Associate Software Engineer

Solar Energy Research Institute of Singapore

♦ Optimized parameters for solar cell manufacture using a shallow Convolutional Neural Network(CNN)
to increase module efficiency. Trained on TensorFlow, and deployed with TensorFlow Serving.
♦ Implemented transfer learning for Silicon sheets with varying wafer properties and predicted process parameters to match efficiencies across manufacturing recipes.
♦ Predicted solar cell performance across climates. Analyzed influence on performance from weather
conditions as a part of the TruePower Project with Random Forest Regression with accuracy above 0.94.
♦ Visually detected defects in solar modules with YOLO algorithm and CNNs.

Research Intern

National Centre for Biological Sciences

♦ Simulated the Stable Matching Problem in a biological population to converge on a fitness function for Pareto efficiency.
♦ Participant of Physics of Life, Monsoon School 2016

Summer Intern

Tata Consultancy Services

Intern

SENSEI Technologies

Graduated from Cornell Tech, New York - Master's in Computer Science, with experience as a data scientist and a software engineer.

Interested in industry applications of Machine Learning.
Please reach out at: aks298@cornell.edu

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Divyansh Lohia

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