With the 2026 Council elections on the horizon, we’re thrilled to introduce a dynamic and diverse slate of candidates who bring passion, expertise and a shared commitment to the power of statistics in public life.
From AI ethics to climate finance, from mentoring early-career statisticians to championing global data literacy, these candidates represent the breadth and depth of our community. Each one brings a unique voice to the table – and they’re ready to make a difference by joining the RSS Council, one of our key governing bodies.
Elections will take place from Monday 1 September until midnight on Sunday 12 October.
Omar Rivasplata
“I am excited to stand for election to the RSS Council as a representative of Computational Statistics and Machine Learning. As this field continues to transform science, industry, and society, I am committed to strengthening the connections between statistical foundations and machine learning practice.
Omar Rivasplata is currently based at The University of Manchester where he is academic staff at the Centre for AI Fundamentals and Associate Professor (Senior Lecturer) in Machine Learning in the Department of Computer Science. Before joining The University of Manchester in July 2024, he held academic positions at University College London and the University of Alberta, as well as an industry position at DeepMind.
Omar is an RSS fellow, also serving on the committee of the Computational Statistics and Machine Learning Section and the AI Task Force. He is also a member of the
European Laboratory for Learning and Intelligent Systems (ELLIS) and the
ELLIS Unit Manchester, a member of the
London Mathematical Society (LMS) and LMS Regional Representative for the North, and a fellow of the
Institute of Mathematics and its Applications (IMA).
Omar is particularly interested in the mathematical and statistical principles that underpin machine learning models, studying and researching both Statistical Learning Theory and Artificial Intelligence (AI) Fundamentals. That said, he tends to have a broad interest in various aspects of statistical machine learning and AI in general. Omar is keen to work on designing strategies to train and certify machine learning models to meet target standards of predictive accuracy and robustness. Previously, Omar has led or been a contributor to projects on statistical learning bounds, deep learning models and kernel models, probabilistic models including generative models and offline reinforcement learning, among others.
Before moving to the UK in 2017, Omar previously lived in both Canada and Peru.
Chris Nemeth
"I have had the pleasure of volunteering for the Society in leadership roles for over five years. I strongly believe in the value of statistical thinking and am committed to strengthening the Society’s role in promoting the importance, relevance and visibility of statistics in public life.
If elected, I will support cross-disciplinary collaboration, improve training and mentoring for early-career statisticians and promote the rigorous use of statistics in industry, policy and academia. Together, I believe we can expand the Society’s impact and ensure statistics remains integral to the fast-developing AI revolution."
Chris Nemeth is a Professor in Probabilistic Machine Learning at Lancaster University and Co-Director of Lancaster’s Data Science Institute, where he provides strategic leadership for interdisciplinary data science research.
Since completing his PhD in Statistics and Operational Research at the STOR-i CDT in 2014, he has been awarded two EPSRC fellowships—including a UKRI Turing AI Acceleration Fellowship (PASCAL)—and has collaborated with industrial partners such as Tesco, Shell and Microsoft Research. He is also a co-investigator on the EPSRC-funded ProbAI hub, which focuses on the mathematical and computational foundations of probabilistic AI.
His research focuses on computational statistics and probabilistic machine learning, with applications to environmental data science, such as ice sheet melt prediction and air quality modelling. He has supervised 14 PhD students and 10 postdoctoral research associates and is deeply committed to mentoring early-career researchers and promoting interdisciplinary collaboration and the importance of statistics across the sciences.
Chris previously served as vice-chair of the Royal Statistical Society’s Statistical Computing Section, where he led its transformation into the Computational Statistics and Machine Learning Section. He became chair of the newly formed section in 2021 and served until 2023, organising workshops and training events to foster community engagement and collaboration for RSS fellows.
He also currently serves as an Associate Editor for the
Journal of Probabilistic Machine Learning, and as a Scientific Advisory Board member for Integreat—a Norwegian Centre of Excellence in Machine Learning.
Ryan Defina
“I’m passionate about statistics and the crucial role it plays in evidence-based decision making. If afforded the honour of joining the RSS Council, I would seek to prioritise opportunities to widen engagement with supranational organisations and the private sector to leverage their unique perspectives. My record demonstrates a commitment to showcasing the importance of statistical professions and in delivering outcomes for key stakeholders.”
Ryan is currently Principal Consultant at Defina Advisory, a boutique consulting firm advising executives on high-level data strategy, best practice in official statistics and the calibration of financial sector safety nets. He has experience in methodology development within official statistics, data management in central banking, in regulating financial institutions within a supranational context, and private sector management consulting. His broad experience living and working in multiple continents, offering tailed statistical advice to CEOs from a variety of industries, ensures he is well-versed in articulating key statistical priorities. He has proudly worked on global initiatives with representatives from the International Monetary Fund, World Bank, numerous national statistical organisations and central banks in recent years.
Ryan has been Chair of the RSS Finance and Economics Section and previously served as New South Wales Branch Secretary of the Statistical Society of Australia.
Edith Milanzi
“As a medical statistician and founder of a data-for-good initiative, I am passionate about making statistics more inclusive, socially responsive and globally relevant. If elected, I will advocate for greater representation of a range of different voices and champion data literacy across diverse communities. I will also use my platform and network to bring greater visibility to the RSS among those who may not otherwise engage with it, helping extend its reach and impact.”
Dr. Edith B. Milanzi is a Malawian medical statistician and data scientist. She has extensive experience applying advanced statistical methods to global health challenges, particularly in HIV, maternal and child health and infectious disease surveillance. Her work has supported data harmonisation and policy-relevant research for organisations such as the World Health Organization, UNFPA and UNESCO.
Dr Milanzi is the founder of Femanalytica, a Malawian data science initiative dedicated to the social sector. The lab provides analytical solutions to non-profit organizations and promotes data literacy, with a particular emphasis on training women in data and technology in Malawi. Femanalytica aims to become Malawi’s first data science hub focused on advancing the Sustainable Development Goals using evidence and innovation.
With a PhD in Statistical Epidemiology, her academic contributions include peer-reviewed publications utilising birth cohort data, electronic health records and leading capacity-strengthening efforts. She has been recognised through fellowships such as the Royal Statistical Society’s Future Leaders Programme, CIPHER Leaders of Tomorrow Programme, and continues to mentor emerging statisticians and data scientists.
Currently based in the UK, Dr. Milanzi remains committed to advancing statistical practice for social good, particularly in under-resourced settings.
David Smallbone
“With AI dominating headlines, the RSS provides the common sense, technical rigour, support and guidance our practitioners need to do the right thing across academia and industry. Many challenges remain to ensure we keep getting these messages across. As a Council, we must make sure our collective voice is heard.
With over 20 years of experience helping organisations to improve performance and deliver better outcomes for customers and stakeholders, I will help the RSS shape the services and support its offers to our members. It’s an exciting time for us; let’s make sure our activities have a positive impact on society!”
David is a Partner in KPMG's Customer, Operations and Infrastructure team, helping organisations get better outcomes from their physical infrastructure and assets through digital technologies, data and analysis. His interests lie in statistical tools and techniques for modelling assets and infrastructure and how these impact on customer experience and economic and social outcomes. He has a passion for using the power of data visualisation to tell better stories with data.
David followed up Mathematical Sciences at The Queen’s College, Oxford with a MSc in Statistics at University of Kent. This provided the foundation for a career helping people make better decisions based on the available data, with an understanding of the risks and limitations. It has seen him work with planes (National Air Traffic Services), trains (Network Rail) and automobiles (Babcock) as well as clients across transport, utilities, retail and defence in his roles at KPMG and AMCL.
David has been a fellow of RSS for nearly 25 years. Having picked up his GradStat as a Young Statistician, David has been an active member of the RSS focusing on the Business & Industrial Section (BIS), including as Chair from 2020 to 2024. He has also been BIS’s representative on the Discussion Meetings Committee. He hopes to continue this support to practitioners in industry and academia as part of Council.
Simon Asplen-Taylor
“If I were elected as a trustee, I’d want to help empower the RSS to act as a voice of influence in the current uncertain times. In addition, I’d like to help engage data scientists and AI specialists, who continually leverage statistics, sometimes unwittingly, but don’t consider themselves statisticians. I’d like to help this group of practitioners find a home in the RSS; most don’t naturally feel technology is their home. Finally, I’d like to help support the role of the RSS as a valuable voice for reviewing government policy in areas of data, analytics and AI.”
Simon is the CEO of VALSTR, one of Europe’s most experienced and successful data leaders. He was the first Chief Data Officer in the UK and has served as CDO for a number of FTSE firms, including IBM, Bupa, Tesco, UBS, and Rackspace. Simon has previously led the biggest business case made for data in Europe, which succeeded in generating £1bn of incremental revenue per annum for a large retail bank. He was responsible for implementing the data and analytics capabilities for the UK’s Financial Regulator that resulted in the UK’s first prosecution of insider trading. In 2022, Simon wrote the data strategy for the Lloyd’s of London insurance market across 2000 firms.
Simon is a bestselling author, having written the Amazon #1 selling
Data and Analytics Strategy for Business (2022). The book has sold out and he has now written the second edition which is being released in August 2025. This new edition includes more content on AI and on practically integrating AI capabilities into a firm’s existing data and analytics strategy.
Simon is featured on this year’s UK Top 100 Influential People list. He has also been awarded the titles of ‘Europe’s Most Influential Data Leader’ and ‘Most Influential London CEO in Data’.
Simon has an MBA from Durham University and has studied Artificial Intelligence at MIT. He is an appointed member of the Royal Statistical Society’s AI Task Force and has been selected to act as an expert judge for the Society’s 2025/26 William Guy lectureship appointments.
Dr. B. M. Golam Kibria
“With a strong background in statistics and a deep commitment to the advancement of our discipline, I am passionate about supporting the Society’s mission to promote the importance of evidence-based decision-making and statistical literacy. With my diverse research background, I have published over 290 research articles and co-authored two books. I have mentored numerous students, serving as the primary or co-primary advisor for five PhD and 24 master's students.
I have received multiple awards, including the FIU Top Scholar Award (2016, 2024). I am an RSS fellow, have a PhD in statistics from The University of Western Ontario (as well as an honorary doctorate from Jönköping University) and I have been named on Stanford University and Elsvier’s “Top 2% Scientist List” every year since 2020. I have also held leadership roles in the South Florida chapter of the American Statistical Association (ASA), including Secretary, Treasurer, Vice President and President."
Dr. B. M. Golam Kibria is a professor and the graduate director (statistics) in the Department of Mathematics and Statistics at Florida International University and has taught at the University of British Columbia, the University of Western Ontario, and Jahangirnagar University in Bangladesh. Dr. Kibria’s research interests are diverse, and since 1993, he has published over 285 full research articles in renowned statistical journals, numerous statistical proceedings and co-authored two books.
Dr. Kibria has served as the primary or co-primary advisor for five PhD students and 24 master’s students at FIU, along with mentoring many undergraduate students. He has also contributed to various PhD, M. Phil, and MSc thesis committees at FIU and internationally, in Australia, Canada, India, Pakistan, South Africa and Sweden.
He has received several prestigious awards, including the FIU Top Scholar Award and the FIU Faculty Award for Excellence in Research & Creative Activities. Dr. Kibria served as the Editor-in-Chief of the
Journal of Probability and Statistical Science for nearly five years and is currently a member of the editorial boards of several international statistical journals.
Dr. Kibria was awarded an Honorary Doctorate from Jönköping University in Sweden on October 8, 2022. He has been ranked in the Top 2% of the World's Scientists for five consecutive years (2020–2024) by Stanford University. He has also previously served the South Florida chapter of the ASA as elected secretary, treasurer, vice president and president – a valuable addition to his candidacy.
Kate Land
“My admiration for the RSS grows with every interaction. I had a small window into the cogs of the organisation when on the conference board and was impressed by the professional hard-working team involved. I also greatly respect the RSS for championing matters of public interest, such as effective measures of inflation.
As non-technical people increasingly use AI tools for data analysis and research, we need the RSS more than ever. As part of the council, I would work with the RSS on its strategic goal to support public understanding and engagement with statistics, in the context of new technologies.”
Dr Kate Land has an MA Cantab in Maths and Astrophysics from Cambridge, and a PhD in Astrophysics from Imperial College. She is currently Lead Data Scientist at Inalytics, a company that analyses the behaviour and decisions of fund managers.
Dr Land has experience in both academia and industry. She was a Junior Research Fellow at Christ Church, Oxford, holding a Glasstone Research Fellowship in Cosmology. Following her postdoctoral experience, she moved into finance and became a research director at the quantitative hedge fund Winton Capital, developing their systematic trading algorithms and risk models. Subsequently, she’s worked in a number of fintech start-ups, co-founded Havelock London, a successful investment management business and served on the advisory board for the Investment Association’s fintech accelerator.
She’s been involved with the RSS most recently as part of the 2024 conference board and as a committee member for the Data Science Section 2019-20, which saw her host debates about the accreditation of data scientists. She has been a volunteer for the RSS’s Statisticians in Society scheme and regularly tackles the Significance puzzle page!
Throughout her career, Kate has been actively engaged in STEM outreach. During her post-doc, she co-founded Galaxy Zoo; a long-running pioneering citizen science project. Currently, she is a registered STEM Ambassador, providing regular talks and workshops for local groups and co-organising her local STEM festival. She is also the vice chair of her popular local astronomical society and a charity trustee of her children’s PTA.
Amanda Penistone
“I’m proud to be a fellow of the RSS and would love the opportunity to further contribute to delivering the RSS objectives, enhancing cross-sector collaboration and championing the public interest. I’ve been delighted to contribute to the Climate Change and Net Zero Taskforce and would like to continue the RSS’s focus on these sorts of urgent global challenges.”
Amanda has been a government statistician in the UK for 15 years. She’s currently Head of International Climate Finance Analysis at the UK Department for Energy Security and Net Zero (DESNZ). She leads a large multidisciplinary analytical team providing analytical support throughout the lifecycle of UK International Climate Finance programmes, from assessing value for money of options, through monitoring results, to evaluating impacts. She’s a member of the RSS Climate Change and Net Zero Taskforce, and she champions compliance with the Code of Practice for Statistics. She also represents the UK internationally, sharing the UK’s expertise and best practice on climate change statistics. Before working on International Climate Finance, she headed up the team producing the UK’s greenhouse gas inventory and a collection of Accredited Official Statistics publications on the UK’s greenhouse gas emissions statistics. She previously worked in the Department for Education, providing a wide range of statistical analysis and modelling to support evidence-based policymaking.