Work with thought leaders and academic experts in data science

Christos A. Makridis holds academic appointments at Columbia Business School, Stanford University, Baylor University, University of Nicosia, and Arizona State University. He is also an adjunct scholar at the Manhattan Institute, senior adviser at Gallup, and senior adviser at the National AI Institute in the Department of Veterans Affairs. Christos is the CEO/co-founder of [Dainamic](https://www.dainamic.ai/), a technology startup working to democratize the use and application of data science and AI techniques for small and mid sized organizations, and CTO/co-founder of [Living Opera](https://www.livingopera.org/), a web3 startup working to bridge classical music and blockchain technologies. Christos previously served on the White House Council of Economic Advisers managing the cybersecurity, technology, and space activities, as a Non-resident Fellow at the Cyber Security Project in the Harvard Kennedy School of Government, as a Digital Fellow at the Initiative at the Digital Economy in the MIT Sloan School of Management, a a Non-resident Research Scientist at Datacamp, and as a Visiting Fellow at the Foundation for Defense of Democracies. Christos’ primary academic research focuses on labor economics, the digital economy, and personal finance and well-being. He has published over 70 peer-reviewed research papers in academic journals and over 170 news articles in the press. Christos earned a Bachelor’s in Economics and Minor in Mathematics at Arizona State University, as well a dual Masters and PhDs in Economics and Management Science & Engineering at Stanford University.

Team lead in machine learning, neuroscience. <br> I have captured and executed projects for DARPA, NASA, and several international clients (GM, Toyota, Fujitsu). \* 12 projects transitioned--$10M revenue captured (31+ publications, 32+ patents) \* 9 awards including those from NASA, GM, and HRL Laboratories \* I also have startup, contracting and consulting experience \* US citizen (authorized to work) <br> Last updated: Aug 30, 2023

Dr Jo Boaler is a Professor of Mathematics Education at Stanford University, and the co-founder of youcubed. Her PhD won the national award for educational research in the UK and her book: Experiencing School Mathematics won the ‘Outstanding Book of the Year’ award for education in Britain. She is an elected fellow of the Royal Society of Arts (Great Britain), and a former president of the International Organization for Women and Mathematics Education (IOWME). She is the recipient of a National Science Foundation ‘Early Career Award’ and the NCSM Kay Gilliland Equity Award (2014). She is the author of nine books and numerous research articles. Her latest book is Mathematical Mindsets: Unleashing Students’ Potential through Creative Math, Inspiring Messages and Innovative Teaching (2016), and is published by Wiley. She serves as an advisor to several Silicon Valley companies.

Dr. Justin P. Whalley was educated in the UK (M.Sci. Mathematics, University of Bristol) and France (Ph.D. Bioinformatics, University of Évry). He moved to Spain to work as a postdoc at the National Center for Genomic Analysis (CNAG). During his time there, he ran the Quality Control working group for the Pan-Cancer Analysis of Whole Genomes project to assess the data coming in and reduce batch effects. This involved collaboration with researchers from the Broad Institute of MIT and Harvard, the German Cancer Research Center and the Wellcome Sanger Institute in the UK. He returned to the UK to work as a [Senior Bioinformatician at the University of Oxford](https://www.well.ox.ac.uk/people/jpw/). His time there coincided with the global pandemic and he was deeply involved in the COvid-19 Multi-omics Blood ATlas (COMBAT) consortium as the lead for the Integration (Tensor) working group. Dr. Whalley became a member of the [faculty of the Chicago Medical School at Rosalind Franklin University of Medicine and Science](https://www.rosalindfranklin.edu/academics/faculty/justin-p-whalley/) in January 2023.

As a Postdoctoral Researcher at UC Irvine, I apply my PhD in Cognitive Neuroscience to investigate the neural mechanisms of learning and memory. I use advanced data management, analytics, techniques to process and analyze large-scale brain imaging data sets. I have over seven years of research experience, including as a Graduate Research Assistant at Florida International University, where I contributed to multiple publications and projects on cognitive and affective neuroscience. I am passionate about advancing the scientific understanding of the brain and its functions, and collaborating with other researchers and experts in the field. I am also committed to sharing my knowledge and skills with the next generation of neuroscience students and professionals.

**Results-driven AI leader with 20+ years of success spearheading model development and optimization initiatives in the energy industry and academia. Proven track record in leveraging computational data science, scientific machine learning, and AI to drive breakthrough physics-data solutions and deliver tangible business value. Adept at translating complex scientific concepts into robust AI models. Skilled in numerical simulation, scientific machine learning, and bilingual communication to optimize project outcomes.**

I am a lecturer at the University of California, Davis, teaching undergraduate students in physics and engineering basic and advanced physics. I also collaborate with several experimental and theory groups in condensed matter physics all over the globe focussing on critical phenomena, quantum magnetism, topological materials, transport properties, and driven quantum systems. My current interests lie in Hilbert Space fragmentation and associated critical phenomena for systems with subsystem symmetries. Additionally, I use the numerical linked cluster expansion to study heavy fermion compounds of interests to groups in John's Hopkins and Princeton Universities.

Over the past decade, I have gained extensive expertise in experimental design, data analysis, and scientific writing while working across a range of academic, pharmaceutical, and research institutions—both in the United States and Uruguay. Throughout my career, I have worked with multiple multidisciplinary teams, which has significantly enhanced my ability to conduct research in complex environments while encouraging teamwork to develop cutting-edge biotechnologies.

Experienced academic and researcher specializing in data science and computer vision, with a proven track record in academia and industry. Proficient in Computer Vision, Machine Learning, and Image Processing, with published many works recognized by over 1000 citations in peer-reviewed publications. Proven ability to collaborate effectively within multidisciplinary teams to tackle complex problems and deliver innovative solutions.  Advocate for teamwork, effective communication, and mentorship.

Dr. Anindya Ghose is the Heinz Riehl Chair Professor of Business at New York University Stern School of Business. His research interests are in the areas of IT-enabled platforms, services and products, including mobile apps, social media, digital marketplaces, and big data analytics. He has also done work on understanding consumer behavior in digital environments. He has published over 130 papers in academic journals and has been honored with several best paper awards. He has also served on the editorial boards of several journals, including Management Science, Information Systems Research, and MIS Quarterly. He is a Fellow of the Institute for Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM).

Dr. Giuliana Noratto is a senior associate research scientist at Texas A&M AgriLife. She received her Ph.D. in food science and technology from Texas A&M University System, and her M.Sc. in food science and technology from Universidad Nacional Agraria La Molina. She also holds a B.S. in food science and technology from Universidad Nacional Agraria La Molina. Dr. Noratto’s research interests include food safety and quality, sensory science, and food processing.

Mengying Li is an Assistant Professor at The Hong Kong Polytechnic University. She received her Ph.D. in Mechanical Engineering from University of California, San Diego in 2018. Her research interests include predictive modeling, design optimization, and machine learning. She is also an expert in passive cooling devices.