Advai: DataScience@work seminar

Title: Introducing Advai: Advancing AI Safety and Security

Speaker: Damian Ruck, Chief Researcher, Advai 

 

Schedule:

  • 2.00 – 3.00pm Introducing Advai: Advancing AI Safety and Security (Rm 2.04, Fry Building)
  • 3.00 – 4.00pm Networking session (Common Room, Fry Building)

Location: Room 2.04, Fry Building 

 

Abstract: 

Introducing Advai: Advancing AI Safety and Security

Advai, a leading company in the field of Safe and Secure AI, specializes in testing, evaluation, and assistance of AI systems. Advai conducts research for  range of organizations with the sole purpose of identifying AI failure modes and ensuring robust performance. The company now collaborates with prominent AI companies, financial services, insurance providers, the National Cyber Security Centre (NCSC), the AI Task Force, and venture capitalists.

Advai’s research team plays a crucial role in the company’s success by providing expertise and original research to support consultancy work. The team develops tools and metrics for Advai’s products and undertakes research contracts for the MoD and other organizations. Their work revolves around three broad areas: adversarial red teaming, tools for testing, evaluation, and assurance, and tools for building more robust AI systems. We will discuss some of this work in this talk.

Looking ahead, Advai’s research team is exploring innovative solutions such as assurance agents, which involve the use of AI agents to semi-automate testing and evaluation processes. They are also investigating the adaptation of traditional system safety processes to Ai systems, moving towards formal verification of AI systems, ensuring their reliability and security.

By addressing the critical challenges in AI safety and robustness, Advai is paving the way for the development and deployment of trustworthy AI systems across various industries. Their ongoing research and collaborations with key stakeholders position Advai at the forefront of shaping the future of Safe and Secure AI.

Advai provides a suite of tools to test, evaluate and help you trust AI systems, based on next-gen research.

 

Damian Ruck, Chief Researcher, Advai 

After attaining a PhD at the University of Bristol, Damian spent several years in U.S universities publishing Computational Social Science research in top academic journals. He has since taken up the role of Chief Researcher at Advai, an Adversarial Machine Learning startup, applying Data Science skills to building Robust and Secure AI.

 

 

Microsoft Research: DataScience@work seminar

Title: TBA

Speaker: James Hensman, Principal Machine Learning Researcher, Microsoft Research

 

Schedule:

  • 2.00 – 3.00pm Seminar + Q&A (Rm. 2.04, Fry Building)
  • 3.00 – 4.00pm Networking session (Common Room, Fry Building)

Location: Room 2.04, Fry Building 

 

Abstract: TBA

 

 

Kew Gardens: DataScience@work seminar

Title: Harnessing Botanical and Mycological Knowledge: Data-Driven Solutions for Global Challenges 

Speakers: Adam Richard-Bollans, Research Fellow, and Eren Karabey,  Kew Gardens

Schedule:

  • 2.00 – 3.00pm Seminar + Q&A (Rm. 2.04, Fry Building)
  • 3.00 – 4.00pm Networking session (Common Room, Fry Building)

Location: Room 2.04, Fry Building 

Abstract: 

Harnessing Botanical and Mycological Knowledge: Data-Driven Solutions for Global Challenges 

A vast amount of botanical and mycological knowledge exists within Kew as well as in global datasets and published scientific literature. In this talk Adam and Eren will discuss their work on turning knowledge into data and the ways they are using data to tackle a variety of global challenges; including extracting structured data from scientific papers, analysing phytochemical diversity across the plant tree of life, searching for new medicinal plant-derived compounds, analysing the chemical composition of coffee species and predicting germination rates of orchid seeds. 

Speakers:  

Dr. Adam Richard-Bollans is a Future Leader Fellow at RBG, Kew. With a background in mathematics and computing, his main work is focused on machine learning methods to efficiently search the estimated 343,000 known vascular plant species for new compounds of pharmaceutical interest. 

Eren Karabey is a student on placement at Kew as an undergraduate intern. Eren is studying Computer Science and Artificial Intelligence at the University of Bath. His main project is to automatically build machine learning-ready datasets from open access research papers.

About Kew Science 

Scientists at Kew work collaboratively and globally to understand and protect biodiversity and to discover sustainable solutions to some of our biggest global challenges. Kew Science encompasses a wide range of disciplines and activities, from analysing evolutionary processes and ecological interactions, to exploring bioactive molecules to unlock useful properties in plants and fungi.  Kew also holds a globally unique, substantial and growing collection of fungal and plant specimens, illustrations, databases, scientific literature, and archives of unpublished material. Ongoing digitisation of these collections is beginning to unleash new opportunities for large-scale data mining and analysis for scientific discovery and innovation. 

David Greenwood: DataScience@work seminar

Title: TBA

Speaker: David Greenwood, Founder,

 

Schedule:

  • 2.00 – 3.00pm Seminar + Q&A (Rm. G.07, Fry Building)
  • 3.00 – 4.00pm Networking session (Common Room, Fry Building)

Location: Room G.07, Fry Building 

Abstract: TBA

 

 

ONS: DataScience@work seminar

Title: TBA

Speaker: Dr Timothy Green, Data Scientist, Data Science Campus, Office for National Statistics

www.ons.gov.uk | datasciencecampus.ons.gov.uk 

 

Schedule:

  • 2.00 – 3.00pm Seminar + Q&A (Rm. G.07, Fry Building)
  • 3.00 – 4.00pm Networking session (Common Room, Fry Building)

Location: Room G.07, Fry Building 

Abstract: TBA

 

 

EDF: DataScience@work seminar

Title: Adaptive probabilistic forecasting of temporal data for electricity markets

Speaker: Yannig Goude – Senior Researcher: Machine Learning & Forecasting

Schedule:

  • 2 – 3.30pm Seminar + Q&A in Room 2.41, Fry Building
  • 3.30 – 4pm networking with students and colleagues in Common Room, Fry Building.

Location: Room 2.41, Fry Building

Abstract: 

Optimising production and making decisions on the electricity markets requires the modelling of various hazards (electricity consumption, temperature, solar radiation, wind, hydraulic contributions, unavailability of power plants, market prices, and renewable production) based on historical data.  For them to work and be of practical interest, in most cases these models have to meet a number of requirements: they have to be interpretable (understandable by the end users, generally engineers in the business departments), adaptive (in the sense of automatically adapting to changes in the data) and efficient. Against a backdrop of increasing production from renewable sources and major tensions in the markets (rising electricity prices, unavailability of production facilities, gas supplies), the teams at EDF R&D (Osiris department) are developing forecasting models that combine these different characteristics.

Yannig Goude is a senior researcher working at EDF R&D, in the department Optimisation Simulation RIsk and Statistics (Osiris), since 2008 and an associate professor at the Laboratoire de Mathématiques d’Orsay, Université Paris-Saclay. He obtained a Ph.D. in statistics and probability in 2007 at the Université Paris-Sud 11, Orsay. His research interests are forecasting, time series, machine learning, semi-parametric models, and online aggregation of experts. 

 

 

The Smith Institute: DataScience@work seminar

When: Friday 7 July, 2-3pm with networking in the Common room thereafter

Location: Room 2.04, Fry Building

Abstract:

The Digital Revolution, Radio Waves and Data Science

Over the past three decades, a whole new sector has grown up around the creation and delivery of mobile data services, which is still growing.  A major challenge has been to provide the capacity in the electromagnetic spectrum to keep pace with demand, and this task has fallen largely on the desks on government regulators.  In addressing it, they have drawn upon the experience of physicists, economists, computer scientists and mathematicians, leading to at least one Nobel Prize along the way and many underpinning scientific advances.  The driver for this progress has been the downstream economic benefits, which are hard to estimate accurately, but amount in financial terms to multiple tens of billions annually.  In this talk, I will survey some of the scientific highlights that have enabled this ‘digital revolution’, concentrating on those that have a strong intersection with data science.

Dr Robert Leese is Chief Technical Officer at the Smith Institute and also Fellow in Mathematics at St Catherine’s College, Oxford.  Beginning in the UK, about 15 years ago, he has worked on many of the auction mechanisms that different governments around the world have used to make spectrum available for new services.

About the Smith Institute

Mathematical approaches coupled with data exploration are key to tackling real-world challenges, to finding the solutions that transform industries and enable societies, businesses and governments to thrive.

From improving the performance of railways to meeting Carbon Zero targetsforecasting crop growth to verifying radio spectrum auctions, the Smith Institute has been tackling their clients’ most critical and complex problems with bespoke solutions for over twenty years.

The possibilities of harnessing mathematical tools are infinite; they enable transformation for their clients across a variety of sectors, applying specialist domain knowledge paired with fresh thinking in transportenergydefencesecurityFMCG and radio spectrum.

For further information about The Smith Institute, see their website.

OVO Energy: DataScience@work seminar

Speakers:

Dave Eagon, Lead Data Scientist

Dr Angharad Stell, OVO Energy

Schedule: 

  • 2 – 3.30pm Seminar + Q&A in Room G.13, Fry Building
  • 3.30 – 4pm networking with students and colleagues in Common Room, Fry Building. 
Abstract: OVO is a major UK Energy supplier, headquartered in Bristol, providing gas and power to domestic consumers. The Portfolio Management team is responsible for forecasting, valuing and hedging billions of pounds of commodity each year. In this talk we will discuss the challenges faced by our team in recent years (COVID, Cost of Living, Ukraine), the challenges that are still to come and how we use machine learning, statistics and computer science to manage our risks. We will explore what a typical day in our data science team might look like, the decisions we are responsible for and how we make them.
Dave Eagon has a degree in Mathematics and Statistics from Oxford University and was an investment banker before qualifying as an actuary specialising in finance and investments. He joined OVO in 2021 and now leads the OVO trading data science team. Dr Angharad Stell has a degree in Natural Sciences from Cambridge University and a PhD in Atmospheric Chemistry from Bristol University. She spent two years as a Research Associate in the Atmospheric Chemistry Research Group at Bristol University before joining the trading data science team in 2022.

About OVO Energy

OVO Energy was founded in 2009 and redesigned the energy experience to be fair, effortless, green and simple for all customers. OVO is on a mission through its sustainability strategy Plan Zero to tackle the most important issue of our time; the climate crisis, by bringing our customers with us on the journey towards zero carbon living. OVO Energy has committed to being a net zero carbon business and achieve bold science-based carbon reduction targets by 2030, while helping members reduce their household emissions at the same time.

For further information about OVO Energy, see their website and their LinkedIn page.

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