Decades later, her scientific interests range across many disciplines, yet Bell's focus is singular: She wants to save millions of lives around the world by providing better tools for early detection of diseases. The Waterman Award recognized Bell for pioneering innovations in ultrasound and photoacoustic imaging that have led to new techniques and improved the quality of medical images, especially for people with darker skin or larger bodies. She is working to ensure that those innovations eventually become accessible to everyone. Bell, who goes by "Bisi," is the John C. Malone Associate Professor of Electrical and Computer Engineering at Johns Hopkins University, where she founded and directs the Photoacoustic & Ultrasonic Systems Engineering (PULSE) Lab and has appointments in the departments of biomedical engineering, computer science, and oncology. On a warm day this past June she sat in her office, meeting with one of her dozen or so graduate and postdoctoral students and checking in on the student's ongoing work.

It's difficult to keep track of the many publicity disasters that have been touched off in recent months by Elon Musk's pronouncements and accusations on Twitter. He berated Wall Street analysts who questioned his company's finances on a conference call. He announced on Twitter that he was considering taking Tesla private, only to do an about-face. And then there was the recent podcast where he appeared to be smoking marijuana in a far-flung philosophical interview touching on everything from improving the safety of self-driving cars to the dangers of artificial intelligence, sending Tesla stock to its lowest point in months.

Security software designed to prevent bank fraud has been fooled by a BBC reporter and his twin. BBC Click reporter Dan Simmons set up an HSBC account and signed up to the bank's voice ID authentication service. HSBC says the system is secure because each person's voice is "unique". But the bank let Dan Simmons' non-identical twin, Joe, access the account via the telephone after he mimicked his brother's voice. HSBC introduced the voice-based security in 2016, saying it measured 100 different characteristics of the human voice to verify a user's identity.

Facebook has unveiled DeepText, a deep learning-based text comprehension engine that uses neural networks to understand the context of posts in over 20 languages. DeepText uses several deep learning neural network architectures, as well as its artificial intelligence (AI) backbone FBLearner Flow and the Torch open source machine learning library, to perform word-level and character-based learning. The system can understand slang and make sense of potentially ambiguous phrases. For example, if a Facebook user posts the phrase'I like apple' DeepText can work out whether it refers to the fruit or Apple. Facebook had to go beyond normal neuro-linguistic programming (NLP) techniques with DeepText, as the extensive pre-processing logic built on top of intricate software engineering and language knowledge is ineffective at picking up variations in languages and spelling when people post on the same topic.