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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 149: S2E11: Brigitte Gosselink, Google.org; Google AI Impact Challenge: Using AI for Social Impact

Our Guest: Brigitte Gosselink

Brigitte is Head of Product Impact at Google.org, where she leads initiatives that leverage emerging technologies and Google’s expertise to address global challenges. She is currently focused on how AI can be used for social impact through efforts like the $25M Google AI Impact Challenge. She previously lead programs focused on how technology can improve global education, innovation for people with disabilities, and crisis response.

Episode 148: S2E10: Sarah Villeneuve, The Brookfield Institute for Innovation: Policy, Society & AI

Our Guest: Sarah Villeneuve

Sarah is particularly interested in emerging technology’s impact on public policy, human well-being, and the economy. Motivated by both the potential benefits technology offers to governments and civil society, and concerns of fairness, accountability and inclusivity, she seeks to contribute to critical conversations surrounding the development and adoption of technology in public life.

Episode 147: S2E9: Myriam Côtê on Responsible AI at Mila

Our Guest: Myriam Côté

As Director of AI for Humanity, Myriam's goal is to put into actions, Mila’s humanitarian mission in collaboration with both our partners of the local ecosystem and our international allies, by promoting an ethical and socially responsible usage of AI.

Episode 146: S2E8: Katherine Stevo, AI for Translating American Sign Language (ASL)

Our Guest: Katherine Stevo

The typical translation devices for people who use ASL are gloves that aren't very accurate. The gloves tend to be inaccurate because the translation doesn't only come from peoples' hand gestures, it also comes from their body language, but the gloves don't account for that. However, the even bigger issue with these gloves is that many people can't afford them. Each glove is around $1,500. Katheriene helped create a translation device for people who use ASL. Katherine was part of the Rising Stars session at the Applied AI Summit in San Francisco, and we will be hosting similar sessions in London this September. Take a look at the event here to register and learn from the next generation of AI experts https://bit.ly/2R3Ik5L.

Episode 145: S2E7: Bistra Dilkina, USC, AI for Preventing Wildlife Poaching

Our Guest: Bistra Dilkina

Wildlife poaching is a serious threat, and one of the largest illegal industries in the world. Historic data on ranger patrolling and detecting illegal poaching incidents can be leveraged to train ML models. Bistra is working on these predictive ML models for poaching risk and explains in this episode how they have been shown to effective in Field studies in 3 different protected areas.

Episode 144: S2E6: Danielle Deibler, Winning the Misinformation Wars

Our Guest: Daneille Deibler

Marvelous.ai is developing natural language tools to analyze political discourse in news and social media . Danielle is particularly focused on how messaging spreads, both negatively (propaganda) and positively (pro-democracy campaigns). In this interview, she chats with OMGitsfirefoxx about her approach to detecting political narratives utilizing human-in-the-loop alongside other natural language processing techniques, with examples focused on the 2020 US presidential election.

Episode 143: S2E5: Kate Taylor, Using NLP in Natural Disaster Crisis Relief

Our Guest: Kate Taylor

Kate Taylor, a high school student and AI4ALL project member is joining us today to share her work in this area. Kate presented her work in the area in our rising stars session in Boston earlier this year. AI4ALL is an amazing project encouraging the next generation of experts to explore all areas of AI. Ellie, from the RE•WORK team spoke with Kate about her presentation and some of the things she’s learned throughout her time at AI4ALL. Kate also shares some of the challenges she’s working on, as well as her long term goals.

Episode 142: S2E4: Neva Durand, Learning How the Genome Folds in 3D

Our Guest: Neva Durand

Neva is the chief computational scientist at Aiden lab at Baylor College of Medicine where she creates analysis and visualisation software of assays exploring how DNA folds in three dimensions. Neva explains how although there have been some huge breakthroughs in healthcare with AI, the promised revolution in medicine is yet to come as there is still so much we don’t know about how DNA regulates cell function. Hear how Neva is working with Deep Learning to bring us closer to AI-powered medicine.

Episode 141: S2E3: Gracelyn Shi, Using Deep Learning to Unlock the Secrets of Gene Expression

Our Guest: Gracelyn Shi

Artificial intelligence has the power to unlock the secrets of gene expression. Using deep learning, the wealth of genomic information that is being created can be understood and used to improve healthcare, drug discovery, and develop new cures. Gracelyn will talk about how deep learning can be used to analyze genetic data and demo her project related to predicting transcription factor-DNA binding. She will also talk about the implications of using deep learning to extract meaningful conclusions from genetic data and what it will mean for the future of the genomics industry.

Episode 140: S2E2: Rana el Kaliouby, Building Emotional AI

Our Guest: Rana el Kaliouby

CEO and Co-Founder of Affectiva joins us on the Podcast today to discuss her work in emotionally intelligent AI where we discuss how it can be used in a variety of areas such as treating people with autism, as well as there being commercial opportunities in social robotics and other areas. Rana was interviewed by Gracelyn Shi from the knowledge society, who asked some fantastic questions about some of Rana’s goals, challenges, ethical concerns, and how she’s inspiring women in AI.

Episode 139: S2E1: Alice Xiang, Responsibility, transparency, and accountability in AI

Our Guest: Alice Xiang

Welcome to season 2 of the podcast, AI for Good.
In this episode, Gracelyn Shi from The Knowledge Society spoke with Alice Xiang from the Partnership on AI who is working as a research scientist in the areas of fairness, transparency, and accountability in AI.

Episode 138: New Series Update: AI for Good

Our Guest: Yazmin How

Find out about our upcoming series focusing on the applications of AI for social good.

Episode 137: Personalizing Your Diet With AI

Our Guest: Amice Wong

In recent years, we are becoming more conscious of our eating habits and our health, and with the help of personalised health platforms, we are able to better monitor our diet, which in turn better our wellbeing. Amice is currently working on her app, eatrite, a personalised food recommendation platform, which, through AI and machine learning algorithms, identifies the dishes on the menu and provides the user with the nutritional value that the dish would provide. This way, users are able to make a better choice when opting for their meal.

Episode 136: Reinforcement Learning in Canada: Martha White, University of Alberta

Our Guest: Martha White

Martha’s primary research goal is to develop techniques for adaptive autonomous systems that learn on streams of data with an applied focus on computational sustainability. She focuses on reinforcement learning and representation learning to achieve this goal. In particular, Martha cares about efficient, practical algorithms that enable learning from large amounts of data. Areas of expertise: algorithms & theory, artificial intelligence, machine learning, reinforcement learning.

Episode 135: Bridge to College: Leveraging AI for Equal Opportunities in Education

Our Guest: Vielka Hoy

Vielka is working on supporting underserved students towards their goal of graduation with little debt. At Bridge to College, Vielka is aiming to match students to colleges that will fund and graduate them on-time. In this episode of the podcast, we spoke about her work in education and her journey into AI.

Episode 134: Using AI to Enrich the Education Experience

Our Guest: Viola Lam

Viola works to create an enriched experience in education and has been doing this in various ways for over 12 years. Viola also won the “Entrepreneur of the Year 2015” award of the Youth Business International, which is one of the world's most honorific awards for young entrepreneurs in over 68 countries. In this episode of the podcast, we spoke about her work as a social entrepreneur and her journey into AI as well as the current landscape of AI in Hong Kong.

Episode 133: Reinforcement Learning: Meta-Learning Deep Networks

Our Guest: Chelsea Finn

Deep learning has enabled significant advances in a variety of domains; however, it relies heavily on large labeled datasets. Chelsea explains how we can use meta-learning, or learning to learn, to enable us to adapt deep models to new tasks with tiny amounts of data, by leveraging data from other tasks.

Episode 132: Assessing Data, Ethics, Regulation & DL Development in Finance

Our Guest: Jessica Lennard

Jessi has been working in lobbying, policy, communications, reputation and crisis for over a decade. During that time, she has worked for political parties, businesses (start-up to FTSE 100), consultancies, think tanks and NGOs. Her particular area of expertise is highly regulated, highly politicised, technology-driven sectors, including telecoms, energy, and Fintech. She was previously a capital markets solicitor at City firm Linklaters, after graduating from Oxford and subsequently the LSE.

Episode 131: Investing in AI in the Financial Sector

Our Guest: Maya Rodriguez

Maya has fifteen years of experience working in the asset management industry and specialises in targeted fundraising and marketing campaigns for the alternative fund industry.

Episode 130: Ethical Considerations of AI Policy, Law and Human Rights

Our Guest: Maroussia Lévesque

Maroussia works at the crossroads of law and technology. She has a background in interactive arts, having lead interdisciplinary teams at the Obx lab for experimental media within the Hexagram research-creation institute. She was called to the Bar in 2013 and clerked for the Chief Justice at the Quebec Court of Appeal, Canada. She participated in the inquiry commission on the protection of journalists’ sources, investigating law enforcement’s electronic surveillance practices. More recently, she researched AI and human rights at the Digital Inclusion Lab within Global Affairs Canada. She is a member of IEEE’s working group on algorithmic bias.

Episode 129: The Sparse Data Problem in Machine Learning

Our Guest: Giewee Hammond

Giewee has an extensive mathematics background which she uses to resolve complex problems for Upstream E&P. She is a Lead Data Scientist for her division and has strategized and filled the need for constructing a productive advanced data analytics team to meet the demands of upstream advanced data analytics projects. She lectures and participates in Houston Data Analytics, a meetup which she founded in January 2018. She highly values the importance of data preprocessing, data exploration, model validation and model interpretation. She holds the following master degrees: Actuarial Science and Analytics.

Episode 128: Conversational AI at Facebook

Our Guest: Anusha Balakrishnan

Conversational systems like Siri and Google Assistant have been around for several years now; and have recently started to play increasingly ubiquitous roles in people's daily lives, through smart home devices, phones, or social media (like Messenger). Despite this, the conversational experience that these systems provide has evolved only incrementally. At the same time, however, interest in conversational AI from the research community is growing fast, and there’s more potential than ever for using machine learning to power these systems.

Episode 126: Machine Learning at Netflix

Our Guest: Julie Pitt

Even if you’re not completely clued up on the technicalities of machine learning, you’ve most probably heard of or use Netflix. This means that you’re interacting with a whole myriad of ML every time you use the platform. Julie leads the Machine Learning Infrastructure at Netflix, with the goal of scaling Data Science while increasing innovation. She previously built streaming infrastructure behind the “play” button while Netflix was transitioning from domestic DVD-by-mail service to international streaming service.

Episode 125: Harnessing Automation for a Just World

Our Guest: Londa Schiebinger

Londa is the John L. Hinds Professor of History of Science at Stanford University and directs the EU/US Gendered Innovations in Science, Health & Medicine, Engineering, and Environment project. She is a leading international expert on gender in science and technology and has addressed the United Nations on the topic of “Gender, Science, and Technology.” She is an elected member of the American Academy of Arts and Sciences and the recipient of numerous prizes and awards, including the prestigious Alexander von Humboldt Research Prize and Guggenheim Fellowship. Her work on Gendered Innovations harnesses the creative power of sex and gender analysis to enhance excellence and reproducibility in science and technology.

Episode 124: AI for Social Good

Our Guest: Anna Bethke

Anna Bethke is the Head of AI for Social Good of Intel's Artificial Intelligence Products Group where she is establishing partnerships with social impact organizations; enabling their missions with Intel's technologies and AI expertise. She is also actively involved in the AI Ethics discussion, collaborating on research surrounding the design of fair, transparent, ethical, and accessible AI systems.

Episode 123: With Great Dialog Comes Great Responsibility

Our Guest: Deborah Harrison

Deborah, writer at Microsoft, is one of the original architects of the personality for Microsoft’s Cotrana. She crafted the core principles that define Cortana's approach to communication and now helps shepherd those principles as Cortana lights up on other devices, on other operating systems, and in other countries. Today, while the field of AI is still in adolescence, the industry stand in a brilliant position to shape not only technological innovation but also the culture of conversation between humans and machines.

Episode 122: Why aren't our AI Assistants smarter?

Our Guest: Cathy Pearl

Do our current crop of AI Assistants really use AI? If not, are they still useful? We'll look at the current state of AI Assistants, the challenges of building them, and speculate on what the future might bring. Learn from Cathy, Head of Conversation Design Outreach at Google, and the author of the O'Reilly book, "Designing Voice User Interfaces".

Episode 121: Enriching Creativity in Applied AI with Interdisciplinary Backgrounds and Diverse Perspectives

Our Guest: Himani Agrawal

Today AI is being created by a very homogeneous set of people. Not only it is homogeneous in terms of race and color but also in terms of academic backgrounds. Himani explains that she is a very unlikely researcher to become an AI engineer but it is crucial so that AI created by heterogenous set of people is more fair and inclusive.

Episode 120: Using Sensory Science & AI to Personalize Wine Recommendations

Our Guest: Amy Gross

Hear from Founder & CEO of VineSeluth, Amy Gross, how they use sensory science and apply it to wines to build artificial intelligence-powered learning algorithms for the food and beverage industry. These personal preference learning algorithms and their results can be integrated into client websites, in-store kiosks and applications to hyper-personalize the shopping experience and guide marketing initiatives, increasing sales and reducing waste for the industry.

Episode 119: Robotics and Intelligence for Human Spacecraft at NASA

Our Guest: Julia Badger

As Project Manager, Julia is responsible for the research and development of humanoid robotic (Robonaut) and autonomous system capabilities, on the Earth, the International Space Station, and for future exploration, that include dexterous manipulation, autonomous spacecraft control and caretaking, and human-robot interfaces. Julia has a BS from Purdue University, and an MS and PhD from the California Institute of Technology, all in Mechanical Engineering.

Episode 86: The Digital Apprenticeship Marketplace for the nextGen Data Professionals

Our Guest: Eunice Chendjou

Eunice is the founder at DataGig, a digital apprenticeship marketplace that helps connect aspiring data scientists with potential employers for their big data and analytics projects on-demand. Eunice strongly believes in building the next generation of women and minorities in the tech industries.

Episode 85: AI to Explore The Universe: Neural Networks & Gravitational Lenses

Our Guest: Laurence Perreault Levasseur

Laurence joined the Flatiron Institute in September 2018 as member of the CCA. Prior to this, she was a KIPAC postdoctoral fellow at Stanford University, where she conducted research in applications of machine learning methods to cosmology. Laurence completed her PhD degree at the University of Cambridge in DAMTP, where she worked on applications of open effective field theory methods to the formalism of inflation. She received her B.Sc. and M.Sc. degrees from McGill University.

Episode 84: Creating Applications That Converse, Understand and Become More Intelligent

Our Guest: Margaret Mayer

Advances in natural language processing (NLP) are increasingly eroding the barriers between frictionless human-machine interaction, creating opportunities to develop nuanced and natural communication techniques that more accurately convey person-to-person dialogue. In this episode, Margaret discussed how convolutional neural networks and long short-term memory networks are enabling more sophisticated NLP systems and building the necessary components to lay the foundation for advanced dialogue.

Episode 83: Open Data and Personal Data Ownership Platforms: social and legal implications

Our Guest: Gosia Loj

Data & Trust Working Group is part of the AI Global Governance Network of Task Forces. Gosia joins us to explain how AI can compute an enormous amount of data helping us understand our own behavioural patterns. We need data sets to train AI to be able to do it.

Episode 82: Women in AI Podcast Special - Sara Hooker & Natacha Mainville, Google Brain

Our Guest: Sara Hooker & Natacha Mainville

At the Deep Learning Summit in Toronto earlier this year, we were fortunate enough to be joined by both Sara and Natacha from Google Brain for an exclusive fireside chat. Hear about Sara’s breakthrough work, as well as her journey in AI and Deep Learning.

Episode 81: Making Deep Learning Accessible to Industry Without Data Scientists

Our Guest: Maithili Mavinkurve

As we know, deep learning is transforming every industry it touches, but it can be challenging for not only small enterprises, but companies of all shapes and sizes to know where to start and how to apply AI to help optimise their work and save money. Speaking at the Deep Learning Summit in Toronto earlier this month, it was great to chat to Mai to hear how Sightline Innovation’s work has progressed over the last year and to chat about some of the new projects they’re working on.

Episode 80: Governance & Policy for Ethical AI

Our Guest: Yolanda Lannquist

Yolanda is an AI Policy Researcher at The AI Initiative of The Future Society, a think-and-do-tank incubated at Harvard Kennedy School of Government. Her research focuses on governance and policy to shape the rise of AI to benefit society broadly while mitigating societal risks, including algorithmic bias, fairness, privacy, cybersecurity, safety, and impact on employment and inclusion.

Episode 79: How can deep learning help improve drug discovery?

Our Guest: Polina Mamoshina

Neural networks have recently been applied to many biological problems, including drug discovery. Applications of DNNs combined with domain expertise can help design de novo druglike compounds and generate large virtual chemical libraries, which can be more efficiently screened for in silico drug discovery purposes. Polina describes aspects of applications of deep adversarial networks and reinforcement learning for molecular de novo design.

Episode 78: How can AI be used in Digital Anthropology?

Our Guest: Lydia Nicholas

Learn from Lydia, who works in the intersection of data, culture and health.

Episode 77: Regulation and Global Policy in AI

Our Guest: Jade Leung

Jade is a researcher with the Governance of Artificial Intelligence Program (GovAI) at the Future of Humanity Institute (University of Oxford). Her research focuses on the governance of emerging dual-use technologies, with a specific focus on firm-government relations in the US and China with respect to advanced artificial intelligence. Jade has a background in engineering, international law, and policy design and evaluation.

Episode 76: Text Mining Techniques: FINRA & Fraud Detection

Our Guest: Yvonne Li

Mining and analyzing text helps organizations find valuable business insights in corporate data. Too often we find the common text mining techniques are not effective in many real-world corporate settings, in particular when dealing with short snippets, boilerplate text collected in forms and repeated text due to cut and paste authoring. Learn more from Yvonne Li on this week's episode of the podcast.

Episode 43: Data Governance Strategy to Support Machine Learning

Our Guest: Peggy Tsai

At the AI in Finance Summit in New York earlier this Autumn, Eunice caught up with one of our speakers, Peggy Tsai. Peggy is Vice President in the Analytics & Data department at Morgan Stanley Wealth Management and is responsible for leading the adoption of Data Governance standards and processes across Wealth Management. Hear what they had to discuss on the podcast.

Episode 42: Direct Uncertainty Prediction for Medical Second Opinions Guest: Maithra Raghu

Our Guest: Maithra Raghu

On this week’s episode, Maithra, PhD Candidate and research scientist at Google Brain discusses her work in the science of Deep Learning. Eunice from the RE•WORK team chats with Maithra about the applications of her current work and how Google Brain are using neural networks in diagnostics, as well as to predict which instances are likely to give rise to maximal expert disagreement in healthcare.

Episode 41: AI in the NHS

Our Guest: Sarah Culkin

On this week's episode of Women in AI, Sarah shares her most cutting-edge work in AI and healthcare, and delves into their 10-year plan to transform the NHS.

Episode 40: Practical Ethics for Artificial Intelligence

Our Guest: Mariarosaria Taddeo

The constant progress of AI leaves society split - some fall into the bracket of excitement, and others are more wary. Whilst these technologies have the potential to transform all industries with a positive effect, we must consider the ramifications if they are not build securely, and with ethical considerations. Mariarosaria joins us to discuss her work in philosophy and ethics at the intersection of AI to share her work in ensuring AI is created with ethics as a priority.

Episode 39: Algorithmic Underwriting for Life Insurance

Our Guest: Laura McKiernan Boylan

The life insurance industry faces a number of challenges: long-term liabilities that can span decades, outdated legacy infrastructure that limits the potential for innovation, and strict regulations that protect consumers but make quick iteration very difficult. At Haven Life and MassMutual, Laura is using algorithms and machine learning models to streamline the customer experience for policy purchases.

Episode 38: Deep Reinforcement Learning in Complex Environments

Our Guest: Raia Hadsell

Where am I, and where am I going, and where have I been before? Answering these questions requires cognitive navigation skills--fundamental skills which are employed by every intelligent biological species to find food, evade predators, and return home. On this week's episode of the Podcast, Raia Hadsell discusses her work at DeepMind.

Episode 37: Behind the Scenes at RE•WORK: Sourcing Global AI Experts

Our Guest: Ellie Lucy

On this week's episode of the podcast we catch up with Global Summit Creator, Ellie Lucy, to hear how she plans her agendas, sources global AI experts, and creates sessions focusing on the most cutting edge work in AI.

Episode 36: AI at Airbnb: Are We Solving The Right Problem?

Our Guest: Negin Nejati

We are living in an exciting time where Machine Learning theory for common applications is maturing, open source tools are plenty, and computation is cheap. While this enables us to move faster than ever, it also makes it easy to throw latest technology at any given problem with little preparation. This can lead to overly complex solutions, suboptimal processes, and waste time. In this talk I’ll draw examples from real applications to show the necessity of spending time on defining the problem accurately before diving for solutions.

Episode 35: Using AI To Understand How Food is Impacting Your Body

Our Guest: Laura Douglas

You only need to open a magazine to be faced with dieting tips and tricks to get in shape, and we’re bombarded with so much contradictory information on how to get the ‘perfect body’ that there’s no wonder it can be overwhelming. Hear from Laura Douglas, Co-Founder at MyLevels is working with her team to overcome this with AI.

Episode 34: Leveraging ML & Emotion AI to Build Algorithms that Match People to Products According to Their Perceptions

Our Guest: Sowmiya Chocka Narayanan

Clothes shopping is some people’s idea of a relaxing afternoon well spend, whilst for others it’s a bit of a nightmare. On this episode I'm joined by Sowmiya Chocka Naraynan, Co-Founder and CTO of Lily AI, the first product to use deep emotional intelligence and AI in the commerce market to decode a woman’s emotional and perceptive needs to highlight or draw away from certain parts of the body to help you find the perfect outfit.

Episode 33: Embodied Vision

Our Guest: Georgia Gkioxari

Georgia Gkioxari is a research scientist at Facebook AI Research (FAIR). She received a PhD in computer science and electrical engineering from the University of California at Berkeley under the supervision of Jitendra Malik in 2016. Learn about her career in AI as well as her current work.

Episode 32: Semantic Understanding for Robot Perception

Our Guest: Jana Kosecka

Advances in robot navigation and fetch and delivery tasks rest to a large extent on robust, efficient and scalable semantic understanding of the surrounding environment. I’m joined today by Jana Kosecka from George Mason University and Google where she’s working on exactly this. Jana is using deep learning to fuel rapid progress in this area to help label data and analyse images, so I’m really excited to learn more about her work in robotics.

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.


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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