Gautam Jajoo

Hey folks! I am Gautam Jajoo, currently building a startup where we are tackling one of the hardest problems in AI i.e. making time align with context so machines can reason, forecast, and predict the world better. I am quite fascinated by building systems that truly grasp the underlying concepts of how the world works. I love building things at the intersection of tech, finance, and research.

Education: B.E. Computer Science & M.Sc. Economics, BITS Pilani (2025)

Research Interests: These days, I am mostly working on Time Series Foundational Models, causal reasoning, and multi-agent systems. My journey has evolved quite a bit: I started with Federated Learning, Privacy-Preserving ML, and Causal Reasoning (heavily influenced by economics). From there, I moved into LLM reasoning, agentic reasoning and retrieval, and now deeper into temporal intelligence.

Hobbies: I love traveling, quizzing, playing chess (always up for a match — lichess: gautamjajoo), watching movies (I am a full-on movie buff), and writing jokes (I have even tried stand-up comedy!).

Over the years, I have enjoyed taking part in competitions across product development, business case studies, finance, programming contests, data science, and analytics. I like exploring different problem spaces.

I enjoy talking to people (not a full extrovert, but more of an ambivert). I bring energy and optimism wherever I go, and even on tough days I try to stay upbeat. I also live by the word backhodi: a Hindi term for light-hearted banter and silly jokes.

I generally don’t find time to write a blog, but I do try to share my thoughts on X. Feel free to reach out to me if you have any questions or just want to say hi! Here’s my Calendly.

news

Dec 01, 2025	Attending NeurIPS in San Diego from Dec 1st to 7th. Will be in the Bay Area for a couple of months forward. Looking to meet exciting people!
Oct 08, 2025	Attending Global Fintech Fest in Mumbai from October 8th to 10th.
Sep 14, 2025	Attending the 12th HLF. Proud to be a part of it, in Europe for a couple of days.
Aug 15, 2025	Going for Mission Control Builders in Residence Program by Mission Street Capital. Will be in the Bay Area for a couple of days.
Jul 13, 2025	Convocation happened today, finally graduated!
Jun 16, 2025	Attending YC AI Startup School and will be in the Bay Area for a couple of weeks post that.
Jun 11, 2025	Attending CVPR in Nashville and presenting the paper VLLMs-4-all at the VLLMs-4-all workshop.
Apr 14, 2025	Joining Lossfunk Residency in BLR building something in AI x Finance.
Feb 25, 2025	In Philadelphia and New York City for AAAI from Feb 26th to March 5th.
Nov 02, 2024	Paper “Federated Learning with Heterogeneous LLMs: Integrating Small Student Client Models with a Large Hungry Model” has been selected in the 2025 AAAI Undergraduate Consortium. Will be there at AAAI in Philadelphia!
Oct 02, 2024	In the Bay Area till 12th October, attending the GSOC Summit, SFTechWeek, and the BayLearn Symposium.
Sep 21, 2024	Attended Pycon India 2024 as an invited speaker. Slides and recording available soon
Aug 24, 2024	Attended Pycon MY 2024 as an invited speaker to talk on “Unveiling the Private: Federated Learning and Model Compression for Secure AI at the Edge”
Aug 19, 2024	Started working as a Research Intern at Microsoft Research, BLR
Jun 03, 2024	Started working as a Data Science Intern at Atlassian
May 01, 2024	Paper “METALS: Semi-Supervised Federated Active Learning for Intrusion Detection Systems” has been accepted at the IEEE ISCC 2024
Feb 21, 2024	Mentoring GSOC students with CloudCV. Prospective students, do checkout GSOC CloudCV
Feb 05, 2024	Started working as a collaborator at the MIT Media Lab!!

experiences

Kairosity

Co-Founder, CEO

(July 2025 - Present)

◦ Building Temporal World Model for forecasting and event prediction.

LossFunk

Resident

(April 2025 - May 2025)

Supervised by: Paras Chopra

◦ Worked on multi agent systems for credit assessment and how can forecasting be used in underwriting.

Microsoft Research Lab

Research Intern

(Aug 2024 - June 2025)

Supervised by: Amit Sharma and Nagarajan Natarajan

◦ Working on prompt optimization or "textual gradient" on a broader persepctive.
◦ Working on causal discovery benchmarking and LLM memorization and reasoning.

MIT Media Lab

Research Collaborator and Open Source Developer

(Feb 2024 - Jan 2025)

Supervised by: Abhishek Singh and Ramesh Raskar

1. Camera Culture Group ◦ Working on SONAR, a collaborative project where users self-organize to improve their ML models by sharing representations of data or model.
◦ Benchmarked decentralized learning algorithms and network topologies, ensuring fault tolerance and mitigating rogue client issues.
2. Fluid Interfaces Group:
◦ Worked on nudging agents on the web [Could not complete it due to time constraints]

Atlassian

Data Science Intern

(June 2024 - July 2024)

◦ Created a performance scorecard dashboard on Tableau with relevant metrics used by 50+ stakeholders to get a comprehensive understanding of business, customer and product health and highlight the areas of success and pinpoint the issues
◦ Authored 150+ complex SQL queries to build the scorecard to gain an extensive understanding of business, customer, and product health.
◦ Developed forecasting & anomaly detection models to detect outliers & predict the metric values to benchmark against the truth values.

CloudCV

Developer, Mentor, Contributor

(2018 - Present)

◦ I am helping to actively maintain CloudCV Project which aims to make AI research more reproducible.
◦ GSOC Organization Administrator 2025 - Working on EvalAI on two awesome ideas, "Enhanced Test Suite and Improved User Experience" and "RAG-Based Chat Bot for Enhanced Challenge Support".
◦ GSOC Organization Administrator 2024 - Leading a team of 5+ mentors and students working on EvalAI on two awesome ideas, "Admin Tools Enhancement and Cost Optimization" and "Enhanced Exception Handling & Leaderboard Porting".
◦ GSOC Mentor 2023 - Mentored 2 students for Google Summer of Code 2023 who are working on improving the usre interface and infrastructure of EvalAI

Nantes Universite, France, LS2N (STACK team)

Research Intern

(May 2023 - Jan 2024)

Supervised by: Prof. Kandaraj Piamrat and Dr. Ons Aeoudi

◦ Developed a new Active Learning (AL)-based Federated Learning (FL) framework (METALS : seMi-supervised fEderaTed Active Learning for intrusion detection Systems) of the Intrusion Detection Systems (IDS) in IoT networks to combine semi-supervised learning and FL to take advantage of the strengths of both approaches
◦ Conducted testing, benchmarking our model against state-of-the-art methodologies, including Classical Machine Learning models (Random Forest, SVM, Decision Tree, KNN etc.), classical FL, and introducing new Active-based FL

ADAPT Lab, BITS Pilani

Undergraduate Student Researcher

(Jan 2023 - May 2024)

Supervised by: Prof. Poonam Goyal

◦ Developed an FL-based tiny model to estimate the Remaining Useful Life (RUL) of electric vehicle batteries
◦ Exploring techniques for model compression such as Binarization, Quantization, Pruning, and Knowledge Distillation to reduce memory constraints for deploying on edge devices and enhance the Machine learning(ML) model’s performance

Summer of Bitcoin

Student Developer

(May 2022 - July 2022)

Supervised by: Vincenzo Palazzo

◦ Collaborated on developing and redesigning ln-dashboard, a seamless payment system on Bitcoin’s Lightning Network
◦ Worked on integrating components like QR codes, enhancing APIs and implementing new APIs using GraphQL for metric display

North Eastern Space Application Centre

Student Intern

(May 2022 - Aug 2022)

Supervised by: Dr. Avinash Chouhan

◦ Created and hosted Deep Learning(DL) - based model, services, and workflow pipelines for a disaster risk reduction project
◦ Successfully deployed ML model based on Sat2Graph Paper to production environment at scale using KServe and BentoML

Indian Angel Network Pvt Ltd

Investment and Portfolio Management Intern

(Feb 2022 - April 2022)

Supervised by: Prafful Garg

◦ Worked in the funding processes for startups by performing due diligence, attending pitches, and other venture screening processes
◦ Worked on formulating an investment thesis on potential investment niches in the BioTech and Web3 industry

Google Summer of Code

Student Developer

(May 2021 - Aug 2021)

Supervised by: Rishabh Jain and Dhruv Batra

◦ Worked on EvalAI where we replaced the existing UI with a new UI version and implemented new REST APIs
◦ Worked on adding new features, improving UI, fixing bugs, and optimizing data loading by reducing loading time by 66%
◦ Improved the infrastructure by reducing API requests by 40% and implementing unit tests using Jasmine and Mocha