We are delighted to introduce our Advisory Board for Digital Discovery!

The Digital Discovery Advisory Board is made up of outstanding researchers from chemistry, materials science, and biotechnology who contribute to the journal as reviewers and writers, provide strategic feedback, and act as community advocates. Learn more about our entire Editorial and Advisory Boards on our website and get to know our newest Advisory Board members and some of their research samples below

Meet our new Advisory Board members:

Abigail Doyle

University of California, Los Angeles, USA

The Doyle lab conducts research at the interface of organic, organometallic, physical organic, and computational chemistry.

Alexandre Tkatchenko, University of Luxembourg, Luxemburg

Dr Tkatchenko develops first-principles computational models to study a wide range of complex materials.

Berend Smit , EPFL, Switzerland

Professor Smit’s focuses on the application and development of novel molecular simulation techniques.

Cecilia Clementi, Freie Universität Berlin, Germany

Dr Clementi’s research focuses on the development and application of methods for the modelling of complex biophysical processes.

Conor Coley, MIT, USA

Professor Coley develops new methods at the intersection of data science, chemistry, and laboratory automation.

Koji Tsuda, The University of Tokyo, Japan

Dr Tsuda’s research background and current interests involve machine learning, computational biology, and computational materials science.

Marwin Segler, Microsoft, Germany

Dr Segler pioneered modern machine learning for molecular design, and chemical synthesis planning.

Heather Kulik, MIT, USA

Professor Kulik completed postdoctoral training at Lawrence Livermore and Stanford, prior to joining MIT as a faculty member.

Jan Jensen, University of Copenhagen, Denmark

Dr Jensen works in molecular discovery and reactivity prediction in the University of Copenhagen.

Isao Tanaka, Kyoto University, Japan

Professor Isao Tanaka is working on first principles calculations and data-centric science with special interests on issues in materials science and engineering.

Ola Engkvist, AstraZeneca and Chalmers University of Technology, Sweden

Professor Engkvist main research interests are deep learning based molecular de novo design, synthetic route prediction and large scale molecular property predictions.

Silvana Botti, Friedrich Schiller University Jena, Germany

Dr Botti’s research focuses on computational materials design, as well as on the development and application of many-body treatments for theoretical spectroscopy.

Shuye Ping Ong, University of California San Diego, USA

Professor Shuye leads the Materials Virtual Lab at UCSD, focusing on the interdisciplinary application of materials science, computer science, and data science to accelerate materials design.

Pablo Carbonell, University of Valencia, Spain

Dr Carbonell’s research interests are in automated design for metabolic engineering and synthetic biology.

Please join us in welcoming all of our new Advisory Board members to Digital Discovery!

Digital Discovery is open for submissions. Find out more on the journal webpage, sign up for email alerts or submit your manuscript now.

We are pleased to announce free desktop seminar to introduce Digital Discovery and share interesting new work in the journal’s scope. In this 100-minute seminar, meet the authors and editors of Digital Discovery and learn about the exciting experimental and computational work being performed to accelerate scientific progress.

If you’re interested in either seminar but can’t make the date, register your interest and we’ll send you a link to the recording afterwards.

(Update 20 October 2022 – The recording of this webinar is now available to view at this link.)

Wednesday 12 October, 1700 JST / 1600 CST / 1330 IST / 1000 CEST / 0900 BST

Professor Yuya Oaki   Keio University, Japan Title: “Sparse modeling for small data toward digital discovery.”
Professor Xi Zhu   The Chinese University of Hong Kong, China Title: “Towards the digitalization of chemical experiments.”
Dr Sukriti Singh   University of Cambridge, United Kingdom Title: “Transfer learning for reaction outcome prediction with limited data.”
Prof. Emma Schymanski   University of Luxembourg, Luxembourg Title: “Extraction of chemical structures from literature and patent documents using open access chemistry toolkits: a case study with PFAS.”

Further information

Register