Machine Learning Websites

Alex Strick van Linschoten is an ML Engineer at ZenML. He is a historian turned software developer. He built Ekko, an open-source framework for adding realtime infrastructure and in-transit message processing to web applications. He has experience in the Python, Ruby and JavaScript ecosystems and is comfortable working with Go, PostgreSQL, AWS cloud infrastructure and Docker. He has a PhD in History and authored several books based on his research work in Afghanistan. He also built Gemini by Example as a reference resource for the Gemini API / SDK.

Daniel Bourke is a writer who creates YouTube videos about the intersection of health, technology, and art. He is the author of the novel *Charlie Walks*. Daniel teaches machine learning and deep learning at the Zero to Mastery Academy. His mission involves using AI to help people move more and eat better. He is currently developing Nutrify, an app to learn about food using AI, and KeepTrack, an app for keeping track of belongings. He also creates educational resources on learnhuggingface.com and learnml.io. He aims to grow his own food and his ikigai is learning to create and creating to learn.

Herbert Bay is a visionary entrepreneur and globally recognized expert in Computer Vision and Machine Learning. He is the lead-inventor of the SURF algorithm and co-founder of seven Swiss/US AI ventures. He has received the ECCV Koenderink Prize and the CVIU Most Cited Paper Award. Beyond his work in technology, Herbert is an adventurer who has crossed both the Atlantic and Pacific oceans on a sailboat with his family.

Dan MacKinlay is a statistician and musician based in Melbourne, Australia. He specializes in the application of statistical inference to AI Safety and the process of scientific discovery, especially in geospatial settings. He is currently employed at CSIRO researching topics in AI Safety and hybrid machine learning methods for physical sciences. His methods of interest include Bayesian neural nets, sparse coding, Gaussian processes, and sequential Monte Carlo methods.

Ronny Calderón has worked in the tech industry for over 9 years as a remote worker. His background includes Big Data, Cybersecurity, and Machine Learning. He enjoys creating products that help people live happier and more successful lives. Ronny is interested in entrepreneurship, marketing, mental models, indie making, and productivity. He shares thought-provoking ideas and value through his blog, focusing on critical thinking, SaaS building, and marketing for developers.

Utkarsh Kanwat is an AI Engineer and Machine Learning Expert focused on building intelligent systems. He develops LLM optimization frameworks, RAG systems, and scalable ML platforms. Utkarsh has an academic research background in computer vision and medical imaging from IIT Bombay. He has experience fine-tuning Gemini models and building production RAG systems. He also built an enterprise data mediation platform and architected an automated deployment pipeline. Utkarsh led a team to victory in a Global Generative AI Hackathon. His research includes developing deep learning models for automated histopathology classification and he has published research at an international conference on medical image analysis.

Nihal Puram is an aerospace engineering major at the Indian Institute of Technology, Madras. He is a self-taught programmer and deep learning enthusiast. This blog is a showcase for his projects and endeavours.

Roman Glushko is a software engineer and product developer. He is a lifelong learner who dissects real-world tech such as open-source platforms, microservices, system programming, distributed systems, and multi-agent AI workflows. He simplifies these topics for engineers and curious minds. Roman also explores the world, unpacks its systems, and captures his reflections on leadership, personal development, team dynamics, and mindset.

Benjamin Anderson is a computer scientist interested in machine learning and artificial intelligence. He is currently building an AI startup in San Francisco. Before that, he was a research fellow at Stanford's Regulation, Evaluation, and Governance Lab, where he focused on data-driven policy interventions in partnership with government agencies. He worked with the Internal Revenue Service to explore the benefits of using self-supervised tabular pretraining for audit selection and with Santa Clara County to evaluate the COVID-19 disease surveillance program using molecular phylogenomics. In his free time, he enjoys listening to comedy podcasts, doing yoga, and baking sourdough. He can be found on Twitter or reached by email at benjamin.anderson [at] hey.com.

Sean MacAvaney is a Senior Lecturer (Associate Professor) at the University of Glasgow and a member of the Terrier Team. He earned his PhD at Georgetown University under Nazli Goharian and Ophir Frieder, where he was a member of the IR Lab. His research focuses on applying machine learning to problems in IR and NLP. He received the ACM SIGIR Early Career Researcher Award, the AI2 Intern of the Year Award, the ARCS Endowment Fellowship, and paper awards at SIGIR, ECIR, and COLING. Prior to graduate school, he worked as a software developer at IIT/SourceTech. He is currently looking for PhD students.

Dave Ramsey is a data scientist based in Philadelphia (PHL). He explores various data science projects, including using the BERN API with the BioBert NLP model to auto-label biomedical terms. He has also worked on movie recommenders and OpenAI GPT-3 examples. His projects are often published on GitHub pages, and the code is available on his GitHub. He also has a YouTube recommendation project using Random Forest ML and has done analysis on Decent Espresso Machine YouTube competition.

Bobby W. Lindsey is a principal machine learning specialist at AWS. He holds an M.S. in mathematics with an emphasis in data science from Tarleton State University. Previously, he worked as a senior data scientist and solutions architect at TechnipFMC. He writes about data science, software engineering, mathematics, cloud architecture, security, and other topics he finds interesting. He has also contributed to several open source projects.

Lennart Heim is a researcher at RAND, leading compute research in the Technology and Security Policy Center within RAND Global and Emerging Risks. He is also a Professor of Policy Analysis at the Pardee RAND Graduate School, teaching AI Governance. His research focuses on the role of compute for advanced AI systems and how it can be leveraged for AI governance, with an emphasis on policy development and security implications. He provides policy and technical advice to tech companies and governments, primarily in the US. He is also affiliated with the Centre for the Governance of AI (GovAI) as an Adjunct Fellow, a member of the OECD.AI Expert Group on AI Compute and Climate, a Pro Forecaster at INFER Pub, and a strategy specialist at Epoch on AI governance strategy. He has a background in computer engineering and studied at ETH Zürich and RWTH Aachen.

Justin Andersun builds tech products and writes fiction. He focuses on machine learning and data-heavy systems, with an interest in tools that encourage care and accountability. He is conscientious, neurotic, agreeable, and open to new experiences. Justin is from Michigan, a practicing Catholic, and a regular blood donor. He enjoys mountaineering and once could ride a unicycle.

Joanita Dsouza is a Senior Software Engineer. She has experience building Distributed Systems and a growing interest in Machine Learning. Joanita holds a Masters in Computing from the University Of Utah (2011-2013) and a Bachelor of Engineering in Computer Engineering from Mumbai University (2005-2009).

Simon Andersen is a software engineer and game creator originally from Paris. He has lived in multiple locations including Seoul, Bergen, St Barthélemy island, Austin, and Tenerife island, and currently resides in Mainz, Germany, while frequently returning to Paris. He has worked at NVIDIA as a contributor to RAPIDS cuML, writing the TF-IDF implementation on GPU. Simon is also an independent game developer, having released the platformer game Pale Night on Steam and with an action roguelike game, Cosmos Survivors, coming soon. In his spare time, he enjoys dancing, gaming, and inline skating.

Ch'ng Zhu Lin is a data scientist with a background in internal audit and chartered accountancy. Driven by a passion for investigating data anomalies and process efficiency, Zhu Lin transitioned into data science and AI. Zhu Lin's experience includes roles at TAO Digital Taiwan, the Institute of Statistical Science, Academia Sinica, and Micron Technology. Zhu Lin holds an MSc in Data Science and AI from the University of Liverpool. Zhu Lin is also a member of the Institute of Chartered Accountants England and Wales, the Malaysian Institute of Accountants, and is an ASEAN Chartered Professional Accountant.

Martina Pugliese is a physicist who works in data science, machine learning, and AI. Based in Edinburgh, Scotland, she writes about a variety of topics, including tech, data, and other areas of knowledge that fascinate her. She creates hand-drawn data visualisations and is involved in projects such as Askademic, an AI tool for scientific research, and CityBreaking, data analyses on overtourism. She also maintains a GitBook with notes on German grammar.

Vincent Cheng is a sophomore studying math at Cornell. He was previously a freshman at UCSD. He is interested in math, ML, AI safety, and Brazilian Jiu-Jitsu. He enjoys learning new things and meeting new people. He worked part-time at Veritasium for six months and was a part of Ross, WARP, and Atlas.

David is a dad of three girls, living in the suburbs of Toronto with his family. He enjoys sailing, wood turning, playing Texas Hold'em, and reading. Professionally, he works for a growth stage equity investor, focusing on portfolio support. He collaborates with Machine Learning engineers and researchers to build AI/ML products with portfolio companies. He also teaches a data visualization course at Google. He uses his website to post photos, quotes, and occasional commentary based on his reading, as well as some analysis or data visualization.

Samuel Wade Wang is an aspiring data professional with a Master's of Science in Analytics from Georgia Tech. He is passionate about leveraging data to uncover insights, drive innovation, and optimize solutions for real-world challenges. His specializations include data wrangling, data visualization, statistical modeling, machine learning, and optimization. He is currently looking for Data Analyst/Data Scientist jobs.

Nathaniel Budijono studied computer science, math, computational biology, and computational chemistry at the University of Minnesota. His professional experience includes building ETL pipelines, researching genetic interaction networks, productionalizing explainable machine learning models, and using language models to study the linguistics of incels. He supports Nucleate Dojo, Socratica, and NAVA.

JJ Balisanyuka-Smith is originally from London, England, and graduated with Honors in Cognitive Science and Math from Swarthmore College, PA. Currently, JJ is an independent AGI Alignment Researcher. Their research interests include NLP, Multi Agent Safety, Machine Learning Theory, AI Safety, and Neural Net Compression. JJ was an early employee at Cohere on the Generative Models and Fine-tuning Teams and co-founded Swarthmore Effective Altruism. In their free time, JJ makes and listens to music under the name JJ Balisan, plays multiple instruments, and is an active marathon runner and Coach with Vegan Runners UK. JJ is an Alumni of the Sutton Trust/ Fullbright US program and volunteers with the program. They also believe in Effective Altruism and have pledged to give 10% of their lifetime earnings to charity.

Bogdan Buduroiu is a platform engineer currently building at Oolong Technologies. He resides in Taiwan. He studied Deep Learning and now focuses on creating performant Engineering Platforms for the ML & GPU-bound age. He is exploring information retrieval algorithms, especially inference at the edge, and working with small LLMs. He writes about Android, Automation, Data, Deep Learning, DevOps, Engineering, GAN, Geopolitics, Life, LLM, Machine Learning, Military, Misinformation, Networking, Nvidia, Obsidian, Privacy, Research, Self-Hosting, Semantic Router, Society, Taiwan, and Tech.