Machine Learning Websites

Nathan Barry is a CS graduate student at UT Austin interested in systems and machine learning. He enjoys working on hard problems with great people and occasionally writes about things that interest him. Nathan is currently finishing his Master’s of Science in CS at UT Austin (Aug 2024 - Present). He will be a Graduate Researcher at UT Austin starting in August 2025, working on diffusion language models and previously distributed low-communication training. Previously, he worked at Apple as a Machine Learning Intern (May 2025 - Aug 2025) and as an Undergraduate Researcher at UT Austin (Feb 2024 - Sep 2024). He also worked at multiple startups as a Software Engineer (Nov 2021 - Jan 2025). Nathan finished his Bachelor’s of Science in CS and Math at UT Austin (Aug 2021 - May 2025).

Alex is a Senior Research Scientist on the AGI Safety and Alignment team at Google DeepMind. His research interests include deep reinforcement learning and agents. Previously, he conducted research in robotics. He graduated from the UC Berkeley Computer Science program in 2016, where he did undergraduate research in the Berkeley Artificial Intelligence Research (BAIR) Lab. He was an Honorable Mention for the NSF Graduate Research Fellowship Program. Outside of machine learning, he enjoys complexity theory, theoretical cryptography, and mathematical logic. In his free time, he plays card games and video games, including Magic: the Gathering and Dominion. He is a puzzlehunt enthusiast and has helped write multiple hunts, including MIT Mystery Hunt 2023.

Wilson is a software engineer. He is interested in distributed systems, backend development, and infrastructure. He enjoys building scalable and reliable systems. He also likes learning about new technologies and contributing to open source projects.

Phil is a Staff AI Engineer at Hugging Face, where he helps companies adopt and implement Machine Learning and Open Source. He is passionate about democratizing artificial intelligence through education and open-source. Phil is a frequent speaker, teacher, and writer about Machine Learning, MLOps and Transformers. Before joining Hugging Face, he was a Lead Data Scientist at a leading AI company, where he helped build and deploy large-scale machine learning systems.

Owain Evans is an AI Alignment researcher and Director at Truthful AI, a research group in Berkeley. He is also an Affiliate Researcher at CHAI, UC Berkeley. His research focuses on emergent misalignment, out-of-context reasoning, and introspection in LLMs. Previously, he worked at FHI (Oxford) and earned a PhD from MIT. He serves on the Board of Directors at Ought and Constellation. He gave the Hinton Lectures in 2025 in Toronto.

Nathan Jeffery is a person who shares musings, stories, and the occasional rant. He has experience in business, particularly regarding the importance of contracts, accounting, focus, ownership, and doing what one loves. He believes in avoiding cheap work and clients, and in hiring slowly and firing slower. He emphasizes the importance of clear documentation and deposits when engaging with clients. Nathan believes in solving problems and hustling harder, rather than stressing. He also believes that clients pay for solved problems and that internal drive is important. He also believes in choosing partners carefully and disrupting an industry to make money.

Shashank is an engineer who used to work on large-scale intelligence systems, crafting Machine Learning Engineering and MLOps solutions, primarily Recommender Systems for online learning. He is now studying High Performance Computing at Georgia Tech and intends to combine ML and HPC to work on super large scale intelligence systems. He enjoys discussing games, maximizing fun, cult-building, machine learning, computers, or how to build companies. He can be contacted via email or LinkedIn. Mindy the cat supervises all operations.

Facundo Quiroga is a researcher working on Machine Learning and Computer Vision at the Instituto de Investigación en Informática LIDI, Facultad de Informática, UNLP. He lives in La Plata, Argentina and has worked as a researcher at the III-LIDI, UNLP since 2013. He is also a Researcher at the Comisión de Investigaciones Científicas of the Buenos Aires province. Facundo teaches Intro to Computer Architecture and Data Mining. He has also taught several posgraduate courses. His research areas include Interpretability for Neural Networks, Sign Language Processing, and Astronomical data. He holds a PhD in Computer Science from Facultad de Informática, UNLP. He also holds a “Licenciature” degree from Facultad de Informática, UNLP. He is currently supervising several PhD and MSc students.

Ryan Marcus is an assistant professor of computer science at the University of Pennsylvania. He uses machine learning to build the next generation of data management tools that automatically adapt to new hardware and user workloads, invent novel processing strategies, and understand user intention. He is especially interested in query optimization, index structures, intelligent clouds, programming language runtimes, program synthesis for data processing, and applications of reinforcement learning to systems problems. He can be reached at rcmarcus@seas.upenn.edu and his office is located at AGH 407.

Slashgeek writes about things that interest them, focusing on geeky topics such as programming, HowTos, and their personal take on emerging technologies. Their background is primarily in Linux system administration, specifically web service optimization for high traffic. They have taught themselves web-stack technologies (HTML, CSS, JavaScript, PHP, MySQL) and general-purpose languages like JAVA, Android development, and Python. They also have experience with large-scale data storage solutions, high throughput, and networking infrastructure. Their recent interests include machine learning and cryptocurrency. Currently, they are on sabbatical.

Petr Lorenc is a student and programmer with an interest in machine learning. He enjoys going to the gym, running, travelling, and trying new foods. Petr is interested in exploring new technologies and applying ideas in the real world. He has worked at DHL Anywhere, Seznam, and Ackee Dateio. Petr studied at CTU in Prague (Faculty of Electrical Engineering and Faculty of Information Technology) and NTUT in Taipei. He is also a member of eClub at CTU.

Kunal Bhalla is a Principal Software Engineer at Meta in New York, working on developer tools for data and ML engineers. He is currently focused on building infrastructure and tools for large models. Previously, he worked on tools for ML developers, aiming to make debugging ML models faster and simpler. Earlier roles at Facebook included leading a team working on infrastructure for Bento, Facebook's in-house Jupyter Notebook solution, and working on Android battery consumption. He has presented tech talks at conferences such as PyTorch Conference and JupyterCon.

Arun Palaniappan is a software engineer at Zerodha. He previously worked at Deep Forest Science as a machine learning engineer, building machine learning pipelines for drug discovery and handling backend and DevOps tasks with AWS. Before that, he was a project assistant at IIT-Madras, focusing on network security. Arun holds a Masters degree in Data Science from PSG College of Technology, Coimbatore, graduating in May 2021. In his spare time, he enjoys reading and practicing doing nothing.

Elias Albisser is currently studying Artificial Intelligence & Machine Learning at HSLU. He works part-time alongside his studies to apply what he learns. In July of 2025, he finished the “Berufsmatura Fachrichtung Technik, Architektur, Life Sciences” with a grade of 5.6. He completed his apprenticeship as “Informatiker Fachrichtung Applikationsentwicklung” in August 2022. Elias is a Linux enthusiast, using NeoVim and Arch Linux. He enjoys mathematics, nature, and sports.

Yonatan is an AI Researcher at Tavily, focusing on web infrastructure for agents. He holds a Master's degree in Statistics and Data Science from Tel Aviv University. His research there, supervised by Roded Sharan and Jonathan Ben-Dov, involved applying NLP and Graph Neural Network methods to identify the authors of the Dead Sea Scrolls. Prior to Tavily, Yonatan worked as a researcher at Forter, where he applied machine learning for fraud detection.

Cole Wyeth is a third year PhD student at the University of Waterloo studying computer science with a focus on algorithmic information theory and sequential decision theory. His research interests include theoretical AI safety, particularly agent foundations, for which AIXI is a foundational concept. He is supervised by Professor Ming Li and advised by Professor Marcus Hutter. He holds an M.S. in mathematics from the University of Minnesota, Twin Cities. He is focused on preventing the rapid progress in AI from going badly and supports a pause on development of autonomous agents until the alignment problem is solved. He is an advisor to the AI safety research fund. In the past, he worked in robotics, including a machine learning internship at Dexai robotics. His hobbies include bouldering, reading, and mixed martial arts.

Alessandro De Simone is a software engineer based in the UK, specializing in Ruby development for government and growth-stage companies. With over 15 years of experience, he has worked with public sector teams, fintech companies, and startups, delivering reliable and maintainable software in complex environments. Alessandro focuses on Agile delivery, object-oriented design, testing, and refactoring. He aims to keep codebases clean, understandable, and easy to work with, whether it's legacy code or greenfield projects. Alessandro collaborates with recruiters, delivery managers, and project managers who need experienced Ruby support. He currently works as a contractor for various projects through his company, Acrobyte Ltd.

Paolo Gabriel is an engineer and scientist specializing in AI, machine learning, and brain-machine interfaces. He holds a PhD in Electrical & Computer Engineering from UC San Diego, where he worked in the Translational Neuroengineering Lab. He also holds a BS in Engineering Physics from Stanford University. Currently, Paolo is a Senior Computer Vision Engineer on the AI team at LookDeep Health, where he designs computer vision pipelines, analyzes patient activity, and curates multi-modal datasets. He is interested in connecting people with their data.

Nishan Pantha is a Computer Scientist at NASA-IMPACT, leading the LLM team. He works on ML research & engineering for open science, particularly NLP/LLMs for scientific knowledge discovery. He is interested in applied Machine Learning, NLP, Large Language Models, and designing modular, extensible, and maintainable systems. He explores philosophical domains: life, culture, art, progress, and the nature of existence. He is influenced by Feynman. He has 9+ years at the intersection of ML research and engineering, bridging the gap between research and practical solutions.

Michael Albada is a computer scientist and writer based in Sonoma County, California. He currently works at Microsoft, applying AI to cybersecurity. Previously, he worked on large-scale machine learning and deep learning models for geospatial intelligence at Uber, and in natural language processing at ServiceNow. His book, Building Applications with AI Agents, is scheduled for be released in 2025. He enjoys learning about new technical challenges and is open to collaboration opportunities.

Ran Ding is a software engineer, former physicist, and lifelong learner. He currently works at OpenAI on its multimodal effort. Previously, he led machine learning and product efforts at Instagram, Threads, Meta GenAI, AWS AI, and startups. He received his PhD from UW and commercialized his research through a semiconductor chip design startup Elenion. He holds 9 US patents and published more than 80 papers. Outside of work, he enjoys reading, taking photos, playing cello, practicing BJJ, and tinkering with mechanical keyboards.