Top 10 Big Data Analytics experts to follow
Top 10 DNA Data Storage experts to follow
George Church: A professor at Harvard and MIT, Church is a pioneer in the field of genetics and synthetic biology. His work has explored the potential of DNA as a storage medium, aiming to harness its incredible data density for real-world applications.
Sriram Kosuri: A professor at UCLA, Kosuri’s research has been at the forefront of DNA data storage. He has demonstrated practical applications of encoding digital information in DNA sequences.
Nick Goldman: As a computational biologist at the European Bioinformatics Institute, Goldman introduced a seminal method for reliable storage and retrieval of digital information in DNA, sparking renewed interest in the field.
Yaniv Erlich: Known for multiple groundbreaking works in genetics, Erlich’s research also delves into the intricacies of DNA storage, emphasizing encoding strategies and error-correction methods.
Luis Ceze: A professor at the University of Washington, Ceze’s work has revolved around computer architecture and systems, and he’s been instrumental in pushing DNA data storage as a promising avenue for future digital archives.
Karin Strauss: Affiliated with Microsoft Research and the University of Washington, Strauss has co-led efforts to design DNA storage systems, exploring techniques to make the reading and writing of DNA data both reliable and practical.
Olgica Milenkovic: A professor at the University of Illinois Urbana-Champaign, Milenkovic has made significant contributions to the coding theory behind DNA data storage, optimizing data density and retrieval accuracy.
Emily Leproust: As the CEO of Twist Bioscience, Leproust oversees the production of synthetic DNA for diverse applications, including DNA data storage, which the company is actively exploring in collaboration with academic researchers.
Robert Grass: Based at ETH Zurich, Grass’s research has extensively covered the stability and preservation of DNA data storage, including encapsulation methods to ensure long-term data integrity.
Dina Zielinski: Previously at the New York Genome Center and now working in the biotech industry, Zielinski co-authored a study with Yaniv Erlich that set a record for DNA data storage density, demonstrating its feasibility for large-scale applications.
Top 10 Data Analytics experts to follow
Nate Silver: Founder of FiveThirtyEight, Silver uses statistical analysis to make predictions in everything from politics to sports. His approach to data-driven journalism has reshaped how data analytics is perceived by the general public.
Avinash Kaushik: The Digital Marketing Evangelist for Google, Kaushik is a recognized authority in web analytics and digital strategies. His books and blog, “Occam’s Razor,” provide deep insights into actionable analytics.
Hans Rosling: Though he passed away in 2017, Rosling’s legacy continues through his groundbreaking work in visualizing complex datasets. His venture, Gapminder, revolutionized storytelling with analytics, making global health and economics data comprehensible to the masses.
Hadley Wickham: Chief Scientist at RStudio, Wickham’s contributions to the R community, including packages like ggplot2 and dplyr, have been instrumental in advancing data visualization and analysis.
Tamara Dull: As the Director of Emerging Technologies for SAS, Dull breaks down the complexities of big data, the Internet of Things, and open source. Her insights bridge the technical and the practical, making data analytics accessible.
Monica Rogati: Having engineered pivotal data products at LinkedIn and Jawbone, Rogati’s expertise lies in turning data into actionable, user-facing products. Her perspective on data-driven product development is invaluable.
Ben Wellington: A data scientist and policy analyst, Wellington’s blog “I Quant NY” uses New York City’s public data to tell compelling stories. His approach showcases the power of analytics in influencing public policy and urban planning.
Cassie Kozyrkov: As Google Cloud’s Chief Decision Scientist, Kozyrkov specializes in bringing statistical rigor to decision-making processes. Her articles and talks demystify complex topics, making data science and analytics more approachable.
Andrew Gelman: A professor at Columbia University, Gelman’s work in statistical modeling and research on the limitations of traditional statistics in the face of complex datasets is groundbreaking.
D.J. Patil: Having served as the first Chief Data Scientist of the U.S., Patil’s experience spans public policy and private sector innovation. His emphasis on “data-driven” decision-making has become a mantra for many in the analytics sphere.
Top 10 Big Data experts to follow
Bernard Marr: An internationally best-selling author, Marr writes extensively about big data, analytics, and enterprise performance. His insights span from how big data impacts businesses to its role in the future of tech.
Doug Cutting: Known as the co-founder of Apache Hadoop, the open-source big data framework, Cutting’s contributions are foundational to the big data landscape. His commentary on evolving data architectures is indispensable.
Hilary Mason: Former Chief Scientist at Bitly and founder of Fast Forward Labs, Mason is a voice of authority on data analytics and its applications. Her focus on innovation in data science makes her insights particularly valuable.
D.J. Patil: Coined the term “Data Scientist” and served as the Chief Data Scientist of the U.S. Office of Science and Technology Policy. Patil’s expertise lies in using big data for social good, among other practical applications.
Monica Rogati: With a background as the VP of Data at Jawbone and a data expert at LinkedIn, Rogati has deep expertise in building data products and leveraging big data for tangible growth.
Kenneth Cukier: Senior Editor of Digital Products at The Economist, Cukier frequently writes about data’s impact on businesses and societies. His book, “Big Data,” co-authored with Viktor Mayer-Schönberger, is a must-read.
Dr. Kirk Borne: A Principal Data Scientist at Booz Allen Hamilton, Borne’s insights into data mining and astrophysics make his take on big data both unique and extensive. He’s particularly vocal about big data’s role in scientific advancements.
Merv Adrian: As a Gartner Analyst, Adrian’s research covers database management, infrastructure, big data, and NoSQL. His analyses of market trends and future trajectories in big data are keenly insightful.
Jure Leskovec: An associate professor at Stanford and Chief Scientist at Pinterest, Leskovec’s work revolves around data mining and network analysis. His research provides a deeper understanding of large-scale data structures and behaviors.
Fern Halper: As the VP and Senior Director of TDWI Research for advanced analytics, Halper’s work provides a rich overview of the tools, strategies, and practices pivotal to the big data industry.