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Hi, my name is Abi. I am a computer scientist and machine learning engineer working extensively in A.I. to help integrate personalized machine learning systems in our day-to-day lives. As a part of that bigger goal, I founded Abide A.I. to help solve some of these challenges for enterprises and teams.

Over the past seven years, my focus has been building production-level machine learning systems for various applications including recommender systems, automated data labelling pipelines for both audio and video, audio-speech synthesis, forecasting and time-series analysis etc.

In the past, I attended Insight as a Data Science Fellow and was a Visiting Research Scholar at UCLA under Dr. Judea Pearl where I worked on Intelligent Agents focusing specifically on AutoML, MultiAgent Systems and Emotion Recognition.

Books & Courses

• ✍️ I am also currently authoring LLMOps: Managing Large Language Models in Production book for O'Reilley Publications. The best way to stay updated on the progress is either through my public talks or the newsletter.

• More - Coming Soon!

Collaboration

• If you want me to participate/speak at your event/podcast, feel free to reach out to me via email

Publications

• 🎊 Large Language Models - Sector Deep Dive with Laconia Capital, August 2023 (Updating - Coming Soon!)

• The Costly Dilemma: Are Large Language Models the Pay-Day Loans of Machine Learning, June 2023

• Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence, Accepted for poster presentation at AAAI 2020

• Problems & Challenges in AutoML, 2019

Social Calendar

Past

Past

2023

• Oct 26 - Speaker, Laconia Capital LP Event - LLMOps with Abi Aryan (Privately Hosted by Geri Kirilova and Jeffrey Silverman )
• Oct 13 - Presented a workshop on Productionizing LLMs, Packt Publication Conference
• Oct 10 - Presented a talk on Domain adaptation and fine-tuning for domain-specific LLMs, AI Engineer Summit
• Sept 20 - AMA on LLMOps at Deep Learning Daily organized by Deci.ai
• Aug 29 - Event Chair for Building AI Agents with LLMs Event - O'Reilly
• July 7 - Gave a talk on Cost Modelling for LLMs at the LLM Projects Workshop
• July 7 - Talked about Self-Learning and Growth for careers in Data and MLOps at Women in Data Podcast
• July 6 - Talked about Fune-Tuning and Evaluations for LLMs at What's the BUZZ? with Andreas Welsch
• June 15 - Moderating the panel on LLM Evaluations at LLMs in Production Conference II by MLOps.Community
• May 4 - Speaker at LLMs Demsytified Webinar with Chris Brousseau, Data Scientist at MasterCard
• April 26 - Speaker at Large Language Models in Production Twitter Spaces with Christine Yuen, Co-Founder and Head of Engineering at Shakudo.io, hosted by Sabrina Aquino
• Co-Host MLOps Community Podcast talking about
  • Why is MLOps Hard in an Enterprise with Maria Vechtomova & Basak Eskili, Machine Learning Engineers at Ahold Delhaize
  • Large Language Model at Scale with Nils Reimers, Director of Machine Learning at Cohere
  • ML Scalability Challenges with Waleed Kadous, Head of Engineering at AnyScale
  • AI and the Future of Database Optimization with Alex Debrie, Author of The DynamoDB Book
  • Challenges of Deploying ML Models on Edge Devices with Jason McCampbell, Chief Architect at Wallaroo
  • PeopleOps in MLOps with Shalabh Chaudri, Head of Customer Success, Union AI
  • ML in Production with Jean-Michel Daignan, Data Scientist at Ubisoft
  • Multilingual Programming with Rodolfo Núñez, Senior Machine Learning Engineer at Entel

2022

• Co-Host MLOps Community Podcast talking about
  • Foundational models with Alex Ratner, Founder and CEO of Snorkel
  • Managing Machine Learning Projects with Simon Thompson, Head of Data Science, GFT Technologies
  • HCI for MLOps Infra Companies with Murtuza Shergadwala, Senior Data Scientist, Fidder.ai
  • What is MLOps with Niklas Kühl, Managing Consultant for Data Science at IBM

2021

• March: Delivered a workshop on Full Stack Deep Learning at Women Who Code Los Angeles
• Hundred other Women Who Code London, LA, SF, NYC events through 2016 - 2021 that I don't remember at the moment, ha!

2020

• August: Presented a technical workshop on Natural Language Processing (NLP) Hands On! at MLNerdie Los Angeles

2018

• Delivered a workshop on A Hands-On Application of Causal Methods in Python at PyData Los Angeles
• Presented a talk on Big Problems at the Heart of Machine Learning at PyData Los Angeles

Upcoming

November 2023

• Nov 8 - Whats New in Data podcast with John Kutay

Volunteering

• October 2023 Invited Reviewer for NeurIPS Workshop: I (Still) Can't Believe It's Not Better

• March 2023 Invited Reviewer | Fifth Symposium on Advances in Approximate Bayesian Inference (AABI 2023)

• September 2022 Proposal Reviewer, PyData NYC

• September 2021 Invited Reviewer for NeurIPS Workshop: I (Still) Can't Believe It's Not Better

• August 2021 Research Mentorship | Association for Computational Linguistics

• November 2018 Area Chair - AutoML | NeurIPS 2018

• May 2018 - Sep 2018 Organising Committee Co-Chair, Pydata Los Angeles

• Mar 2016 -Aug 2021 Director, Women Who Code Los Angeles

Top Tweets & Threads

• Brief Review: Unifying Large Language Models and Knowledge Graphs Paper

• My Review of FrugalGPT Paper

• My Review from Palm 2 paper

• My fav MLOps Papers

• My fav Data Engineering Papers

While I am on Twitter, LinkedIn as well but I do not promise to post and be active there. Lately, I prefer Threads @goabiaryan for sharing ML stuff

Newsletter

Interested in hearing about Data Infrastructure, ML Systems, and new startups/research papers/tools in the ML and LLMOps space?

I send out a newsletter called ModelCraft. Feel free to sub.