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EPISODE 01

Nikita Johnson: the RE•WORK Journey

This podcast series will bring together a cross-disciplinary mix of influential women working in AI, Deep Learning, and Machine Learning and their impact on solving challenges in business and society.

Women in AI is a biweekly podcast from RE•WORK, meeting with leading female minds in AI, Deep Learning and Machine Learning. We will speak to CEOs, CTOs, Data Scientists, Engineers, Researchers and Industry Professionals to learn about their cutting edge work and advances, as well as their impact on AI and their place in the industry.

Episode 31: Social Responsibility in Human-Robot Interaction

Our Guest: Ayanna Howard

Having worked for the likes of NASA’s Jet Propulsion Laboratory, founding Zyrobotics and chairing the Robotics PhD program at Georgia Tech, this week's discussion covers Ayanna Howard's current and upcoming work.

Episode 30: Ethics and AI: the Importance of Collaboration

Our Guest: Fiona McEvoy

Listen to this week's guest, Fiona McEvoy Tech Ethics Researcher and Founder of YouTheData discuss he importance of ethical considerations in technology.

Episode 29: Detecting Mobility Functions in Free Text

Our Guest: Ayah Zirikly

Finding out whether you’re eligible for disability allowance or to be officially registered as having a disability can be a long process, and one that many patients can’t afford to wait for. Recent progressions in NLP have made it possible to speed up this process by identifying disability mentions in text in both medical specialists’ notes and patients’. Learn from Ayah Zirikly from NIH in this week's episode.

Episode 28: Deep Learning in the Health Record: Discovering Meaning in Clinical Text

Our Guest: Tasha Nagamine

Tasha specialises in biologically inspired neural networks, and puts a special emphasis on NLP using clinical text and heads up the AI team to develop state of the art tech that actually understands a doctors thought process through natural language understanding.

Episode 27: Bringing End-To-End Machine Learning Solutions To Healthcare

Our Guest: Rachita Chandra

Despite the amount of data collected, the healthcare industry as a whole is overwhelmed by the challenges in understanding the information to transform research prototypes into real-world healthcare solutions. IBM Watson Health are working to bring together end-to-end machine learning solutions in healthcare into hospitals and general practice, learn more from Rachita.

Episode 26: How Can Industry and Academia Work Together to Create Ethical AI?

Our Guest: Cansu Canca

Cansu works on ethics of technology and population-level bioethics with an interest in policy questions. Prior to the AI Ethics Lab, she was a lecturer at the University of Hong Kong, and a researcher at the Harvard Law School. Learn more on this week's episode of the podcast.

Episode 25: Using Neural Networks For Forecast Demand At Amazon

Our Guest: Sergul Aydore

On this week's episode Sergul, ML Scientist at Amazon discusses her work in neural networks for forecast demand. Hear about how Amazon ensure they have the right quantities of each product to maximise customer experience.

Episode 24: Adversarial Learning for Text-to-Image Synthesis

Our Guest: Miriam Cha

Recent approaches in generative adversarial networks (GANs) can automatically synthesize realistic images from descriptive text. Despite the overall fair quality, the generated images often expose visible flaws that lack structural definition for an object of interest. Miriam joins us today to discuss some of her work to improve this.

Episode 23: Interpreting Machine Learning Models in Finance & Insurance

Our Guest: Soledad Galli

This week we’ll be taking another look at AI in finance, and today’s guest is Soledad Galli from LV. So what comes to mind when you think of AI in Finance? Fraud Detection? Algorithmic Trading? These areas are constantly in the news, and AI has already undoubtedly made huge contributions to the efficiency and accuracy of many financial practices, but there are also lots of new ways that AI is being implemented to alter traditional methods within retail and commercial banking, insurance and many more industries.

Episode 22: The Ethical Implications of AI

Our Guest: Yasemin J Erden

To coincide with the release of our white paper focusing on ethics and AI, Yasemin joins us to discuss her research covering topics such as bias, privacy and security, and AI for good.

Episode 21: Deep Representation Learning for Disparate Data

Our Guest: Huma Lodhi

Recently, at the Deep Learning in Finance Summit in London, Huma Lodhi from Direct Line Group joined us to present her work and explained how deep learning based AI models are showing incredible results for complex problems in both banking and insurance. When you think about all the data in these industries it makes sense that deep learning could be highly effective here, and today Huma chats with us about learning representations from disparate data, like free-from text and structured categorical and numeric data in insurance.

Episode 20: Using Deep Learning to Identify Human Behaviour with Flickr Photographs

Our Guest: Merve Alanyali

With faster internet and better connectivity, online information has taken a shift from being text-based to visual media such as photos. I’m going to be chatting with Merve Alanyali, PhD Researcher and Academic Assistant at Warwick Business School and The Turing Institute to hear how she’s using these vast amounts of data to quantify human behaviour. Merve’s research focuses on analysing large open data sources with concepts from image processing and machine learning to understand and predict human behaviour on a global scale.

Episode 19: Offline Applications of Recommender Systems in Royal Mail

Our Guest: Kat James

On this week's episode of Women in AI Podcast, we're joined by Kat James, Senior Data Scientist at Royal Mail, who explains how recommender systems help them deliver the 50 million letters across the UK 6 days a week.

Episode 18: The Ethical Implications of AI

Our Guest: Catherine Flick

How should we consider the societal impact of AI from conception to production? Catherine, Senior Lecturer in Computing and Social Responsibility at De Montfort University shares her work in social responsibilities when creating AI. Learn about bias, ethics & more.

Episode 17: Improving Online Customer Shopping Experience with Computer Vision

Our Guest: Honglei Li

Honglei joins us today to discuss how AI is transforming retail in various areas such as computer vision and pattern recognition for image detection and classification. Honglei Li is currently a senior lecturer in Enterprise Information Systems at Department of Computing & Information Sciences, Northumbria University.

Episode 16: Personalization vs. Personality in Virtual Assistants

Our Guest: Ann Thyme Gobbel

Today, we chat with Ann about her work in NLP and conversational speech recognition as well as her current role as Voice UI/UX Design Leader at Sound United. While doing a PhD in Cognitive Science and Linguistics at UCSD, Ann's interest in phonetics and NLP led to a dissertation using neural networks to model how speakers of a language form new words via paradigm patterning and token analogy.

Episode 15: How can AI assistants help patients monitor their health?

Our Guest: Cathy Pearl

AI assistants are making a huge impact in healthcare, and another really exciting company that have created a virtual assistant is Sense.ly, whose virtual nurse avatar, Molly, helps people engage with their health. Today i’m going to be chatting to their VP of user experience, Cathy Pearl to hear more about how Molly helps patients. Cathy as worked on everything from helicopter pilot simulators at NASA to a conversational iPad app in which Esquire magazine’s style columnist tells you what you should wear on a first date.

Episode 14: How can chatbots help overcome the mental health crisis?

Our Guest: Alison Darcy

Depression is the leading cause of disability globally, and the cost of mental illness to society has doubled in the last 10 years in every region of the world. Alison Darcy, CEO and Founder of Woebot Labs is joining me today to discuss her work in addressing the mental health crisis with a chatbot that delivers cognitive behaviour therapy.

Episode 13: The commercialisation of deep learning

Our Guest: Maithili Mavinkurve

Is Deep Learning just a field of technical research that won’t affect the general public? Absolutely not - we’ve not seen such a powerful and disruptive technology since the inception of the internet itself - deep learning is transforming every industry it touches from finance to healthcare, self driving cars to smart cities. Mai joins us today to discuss the importance of making the application of deep learning accessible and hassle free for businesses. Even when a business understands the importance of AI and the impact it can have in industry, it’s hard to know where to start and how to afford the relevant staff and technologies.

Episode 12: How can organisations of all shapes and sizes successfully implement AI?

Our Guest: Lisha Li

Lisha from Amplify Partners joins us today to discuss her work in funding companies who are using machine learning and data to solve problems.

Episode 11: How do we discover and synthesise new concepts with minimal supervision?

Our Guest: Zeynep Akata

On this episode, Zeynep from the University of Amsterdam and the Max Planck shares her expertise exploring zero-shot learning as a method to scale up visual category recognition as well talking about discovering and synthesizing novel concepts with minimal supervision.

Episode 10: How Do Facebook Design AI Algorithms to Power New Experiences?

Our Guest: Aparna Lakshmiratan

Aparna joins us to discuss her work in driving Facebook's program to build new algorithms for ranking and personalization, and shipping them to power products for over 2 billion people.

Episode 09: Deep Learning Models for Personalised Medicine

Our Guest: Adriana Romero

Adriana discusses her work in deep learning and how it has achieved remarkable results in fields such as: computer vision, speech recognition and natural language processing as well as transforming medicine.

Episode 08: Towards Psychologically Aware AI

Our Guest: Ann Hsu

Anne Hsu, Assistant Professor at University of London, joins us to discuss the progression and importance of creating psychologically aware AI. These models can understand users’ motivations and provide empathetic dialogues to help create more meaningful and engaging conversations.

Episode 07: Applications of Deep Learning: Anomaly Detection, Sentiment Classification, and Over-sampling

Our Guest: Noura Al-Moubayed

In this episode, Noura discusses her work in unsupervised deep learning as well as NLP and optimisation. As Yann LeCun said recently, unsupervised learning is the ‘holy grail’ of AI research as it allows machines to replicate the way humans learn, and we discuss Noura's progressions in unsupervised learning...

Episode 06: How Dialogue Systems Learn

Our Guest: Layla El Asri

However useful AI assistants are, they’re still not perfect. They’re designed to serve us through dialogue, but to be effective they must not only understand natural language, but be able to generate sentences that communicate back in a human-like manner. Layla El Asri from Maluuba, a Canadian AI company teaching machines to think, reason, and communicate with humans joins us on this episode to discuss her work leading a team to improve natural language understanding in these assistants.

Episode 05: Sci-fi to AI - Interview with Doina Precup, McGill University

Our Guest: Doina Precup

In this episode, Doina shares her journey to where she is today in AI, as well as discussing her work at McGill University, and the exciting projects she's involved in at DeepMind Montreal. The landscape of AI in Montreal is rapidly advancing, and we discuss progressions, obstacles, and current research that Doina is working on.

Episode 04: Lip Syncing From Audio

Our Guest: Ira Kemelmacher

This week Ira Kemelmacher, assistant professor at Allen School of Computer Science and Research Scientist at Facebook joins us to discuss her current work in computer vision. If you open up your internet browser and search for a singing cat or a talking baby, you’ll find edited examples that create the illusion of real speech. These videos provide immense entertainment, but is these a useful application of this?

Episode 03: Opinion Mining Using Heterogeneous Online Data

Our Guest: Elena Kochkina

Understanding public opinion is important in many applications, such as improving company's product or service, marketing research, recommendation systems, decision and policy making and even predicting results of elections. Social media is a very powerful tool to transfer information and express emotions for users and a rich source of data that enables researchers to mine public opinion, but social media is a breeding ground for rumours that get miscommunicated into fact - how can we use AI to help eliminate this?

Episode 02: Iterative Approach To Improving Sample Generation

Our Guest: Antonia Creswell

Antonia is a PhD candidate at Imperial College London, in the Bio-Inspired Computer Vision Group. Her research focuses on unsupervised learning and generative models. She received her masters in Biomedical Engineering from Imperial College London with an exchange year at the University of California, Davis. Antonia has interned at Twitter (Magic Pony), Cortexica and UNMADE. In this episode we discuss the implementation of generative modelling to synthesise new data samples, and the challenges faced in this work.

Episode 01: NIKITA JOHNSON: THE RE•WORK JOURNEY

Our Guest: Nikita Johnson

Nikita Johnson, founder and CEO of RE•WORK discusses the motivation behind the Women in AI series. The episode touches on how she came to found the AI events company, and shares some exciting insights of the upcoming Deep Learning Summit and AI Assistants Summit in London, highlighting some of the influential women who will be sharing their research at the event.

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