Highlighting Data Science and AI Research Labs on the West Coast Highlighting Data Science and AI Research Labs on the West Coast
Data science and artificial intelligence research labs are popping up everywhere, and the West Coast in the USA is a hotspot.... Highlighting Data Science and AI Research Labs on the West Coast

Data science and artificial intelligence research labs are popping up everywhere, and the West Coast in the USA is a hotspot. Between excellent universities focusing on AI, and major tech companies having headquarters there, there’s certainly a lot of buzz around AI in California and surrounding states. Just as we highlighted AI research labs in Europe, India, and the APAC region, now we want to highlight standout artificial intelligence research labs on the West Coast.

Berkeley Artificial Intelligence Research (BAIR)

Berkeley is known as one of the best higher education institutions for technology, AI, and data science. This lab has an incredible roster of both students and professors, such as Pieter Abbeel, Dawn Song, Peter L. Bartlett, and many more.

Though Berkeley’s areas of research are far-reaching, a few of their primary endeavors include computer vision, ML, NLP, robotics, human-compatible AI, multimodal deep learning, and more. One of their most well-known open-source projects is the Caffe deep learning framework. You can follow their blog for helpful tutorials, news, and guides.


Even right off the bat, we love their mission statement, “OpenAI’s mission is to ensure that artificial general intelligence benefits all of humanity.”

What does that mean exactly? Cofounded by Elon Musk and Sam Altman, OpenAI goes beyond just creating technology and AI algorithms – they’re also working on safety, policy, research, and more. They offer many free, open-source Python-specific tools like rllab, PixelCNN, and various papers.

OpenAI made rounds in the news not long ago when it defeated world champion DOTA 2 players in real-time and in front of an audience. OpenAI also created GPT-2, an AI that can write text like articles, fake quotes, and statistics. Also, not long ago Microsoft invested a hefty sum to improve the capabilities of their Azure service with the goal of vastly improving its capabilities in building AI technologies.

University of California – San Diego

The University of California, San Diego, is one of the world’s leading research universities. Under its umbrella, there are a number of labs with their own unique focuses.

Artificial Intelligence Group

The Artificial Intelligence Group at UCSD engages in a wide range of theoretical and experimental research. Areas of particular strength include machine learning, reasoning under uncertainty, and cognitive modeling.

Berg Lab

The BergLab is Taylor Berg-Kirkpatrick’s lab in the Department of Computer Science and Engineering at the University of California, San Diego. Members of our group are also affiliated with the Language Technologies Institute at Carnegie Mellon University. They do research on natural language processing and machine learning, with a special focus on unsupervised methods for deciphering hidden structures.

Database Lab

The Database Lab at UC San Diego is one of the leading academic research groups in the field of data management, spanning the major themes of theory, systems, languages, interfaces, and applications, as well as intersections with other data-oriented fields. 


University of California – Los Angeles

Similar to its San Diego counterpart, the University of California – Los Angeles (UCLA), Samueli School of Engineering has numerous divisions devoted to AI and data science.

Automated Reasoning Group

The Automated Reasoning group focuses on research in the areas of probabilistic and logical reasoning and their applications to problems in science and engineering disciplines.

VCLA (Center for Vision, Cognition, Learning, and Autonomy)

The objective of the VCLA is to pursue a unified framework for representation, learning, inference, and reasoning, and to build intelligent computer systems for real-world applications.


The long-term research goal of UCLA NLP is to develop models, algorithms, and learning protocols for fair, accountable, and robust language processing technology.

Statistical Machine Learning Lab

The Statistical Machine Learning Lab heavily researches Non-Convex Optimization, Foundation of Deep Learning, High-Dimensional Machine Learning, Computational Genomics, Privacy-Preserving Machine Learning, Reinforcement Learning, and AI for Combating Pandemics.

Other groups at UCLA include the Big Data and Genomics Lab, ScAi (Scalable Analytics Institute), Software Evolution and Analysis Laboratory, SOLAR (Software Systems Laboratory for Data Analytics and Machine Learning), and StarAI (Statistical and Relational Artificial Intelligence Lab).

University of South California (USC)

Similar to the above locations, the University of South California (USC) has numerous AI research labs under its umbrella.

CLVR (Cognitive Learning for Vision and Robotics Lab)

The goal of CLVR is to develop intelligent systems that are capable of not only perceiving the world but also reasoning and interacting with it. They are especially interested in building a cognitive model that can learn to make plausible decisions given multi-modal data from the surroundings.

Data Science Lab

The Data Science Lab focuses on applying machine learning, data mining, and network analysis to real-world problems in society and industry, including topics like Graph Embedding, ML-driven Memory Prefetcher, System Performance Prediction, Predicting memory accesses using machine learning-based approaches, and more.

MaSCle (Machine Learning Center)

MaSCle for short is a research lab dedicated to solving some of the world’s most significant problems via machine learning. including engineering better medicines, reverse-engineering the brain, and improving advanced health informatics.

Melady Lab (Machine Learning and Data Mining Lab)

The USC Melady Lab develops machine learning and data mining algorithms for solving problems involving data with special structures, including time series, spatiotemporal data, and relational data.

Center for Artificial Intelligence in Society

The primary goal of this center is to share ideas about how AI can be used to tackle the most difficult societal problems. They believe that this agenda can best be achieved by a genuine partnership between AI and social work.

Other groups at USC include the Natural Language Processing Group, the Center on Knowledge Graphs Research Group, CSSL (Computational Social Science Lab), and the INK Lab (Intelligence and Knowledge Discovery).

The University of California – Santa Barbara (UCSB)

UCSB also has numerous AI research labs to learn from.

CRML (Center for Responsible Machine Learning)

The Center for Responsible Machine Learning is particularly interested in addressing issues of fairness, bias, privacy, transparency, explainability, and accountability in the context of AI algorithms, and in understanding the wide range of ethical, policy, legal, and even energy-efficiency issues associated with machine-learning models.

Natural Language Processing Group

The UC Santa Barbara NLP group concentrates in the areas of information extraction, computational social science, knowledge graph, learning to reason, dialogue systems, language & vision, summarization, statistical relational learning, reinforcement learning, structure learning, and deep learning.

Dynamo (Dynamic Networks: Analysis and Modeling)

Dynamo focuses on machine learning and data mining, social networks, brain networks, and bioinformatics.

Center for Machine Learning and Intelligent Systems

Examples of research activities in the Center for Machine Learning and Intelligent Systems range across areas as different as web search engines, statistical text mining, spam email filtering, information retrieval, automated reasoning, image and video data analysis, sensor networks, astronomy and planetary sciences, ocean and atmospheric sciences, systems biology, medical diagnosis, chemical informatics, and microarray genomics.

Stanford AI Lab

The Stanford AI Lab, aka SAIL, is a broad, interdisciplinary lab with many groups within it. Since its focus is broad as a whole, each group has a unique focus. Some groups include the Stanford Natural Language Processing (NLP) Group, the Stanford Vision and Learning Lab (SVL), and the Stanford Statistical Machine Learning (statsml) Group.

Leading Tech Companies with AI Research Labs

AI research labs aren’t only for universities, as many leading tech companies have their own AI research divisions. 

  • Apple
  • Facebook
  • Microsoft
  • Uber AI Labs
  • Google

Learn more about data science and AI research labs and institutions at ODSC West 2021

At ODSC West 2021 this November 16th-18th, we will have an entire track devoted to data science and AI research and AI research institutions. Some highlighted sessions include:

  • Towards More Energy-Efficient Neural Networks? Use Your Brain! Olaf de Leeuw | Data Scientist | Dataworkz
  • New Frontiers in Deep Generative Learning: Arash Vahdat | Senior Research Scientist | NVIDIA Research
  • Acquiring and Exploiting the Semantics of Data: Craig Knoblock, PhD | Keston Executive Director/Director/Research Professor | Information Sciences Institute/Center on Knowledge Graphs Research Group/Computer Science and Spatial Sciences, USC
  • Reasoning About the Probabilistic Behavior of Classifiers: Guy Van den Broeck, PhD | Director/Associate Professor  | StarAI (Statistical and Relational Artificial Intelligence Lab)/UCLA
  • Information Flow and Deep Representation Learning: Michael Tamir, PhD | Chief ML Scientist & Head of Machine Learning/AI | SIG
  • How We Got Data Prep (and Machine Learning) All Wrong?: Dr. Jennifer Prendki | Founder and CEO | Alectio
  • Personalized Machine Learning: Julian McAuley, PhD | Professor | Artificial Intelligence Group, UCSD
  • Improving Model Performance, Portability and Productivity with Apache TVM and the Octomizer: Luis Ceze, PhD | Co-founder and CEO/Director/Professor | OctoML/SAMPL Research Group/MISL/Paul G. Allen School of Computer Science and Engineering, UW
  • Logging Machine Learning Data with Whylogs: Why Statistical Profiling is the Key to Data Observability at Scale: Bernease Herman | Data Scientist | WhyLabs/University of Washington eScience Institute


ODSC gathers the attendees, presenters, and companies that are shaping the present and future of data science and AI. ODSC hosts one of the largest gatherings of professional data scientists with major conferences in USA, Europe, and Asia.