Innovators under 35

This list was extracted from MIT Technology Review that has been presenting this list for the past 20 years. This contest generates more than 500 nominations each and the editors then face the task of picking 100 semifinalists to put in front of our 25 judges, who have expertise in artificial intelligence, biotechnology, software, energy, materials, and so on.

This is the Female Innovators under 35 MIT.

Christina Boville

CEO at Aralez Bio

Christina Boville helped design a process that improves biology’s way of controlling chemical reactions. She starts with natural enzymes—proteins that enable chemical reactions in living cells—and engineers them to produce useful chemicals that don’t exist in nature. The approach can reduce manufacturing times for compounds used in the pharmaceutical industry from months to days, shrink waste by up to 99%, and cut energy consumption in half.

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Nadya Peek

Assistant Professor at the University of Washington

Nadya Peek began tinkering with machines out of stubbornness. As an undergraduate, when she collaborated with artists on their installations, she often ran into limitations with the tools and equipment they were using. Rather than accept her fate, she hacked the machines until they finally did what she wanted. It got her thinking: why couldn’t machines be more flexible? What if instead of changing your idea to fit the tools, you could change the tools to fit your idea? Thus began her quest to create application-specific machines that could help anyone do almost anything. Read More

Leila Pirhaji

Founder & CEO at ReviveMed

Leila Pirhaji built an AI-based tool for measuring tiny molecules in the body called metabolites, and her work could help us better detect and treat diseases. “There are 100,000 metabolites in the body,” she says. “They are involved in our metabolism and are downstream from DNA, so they show the effects of both our genes and lifestyle.” Such metabolites include everything from blood sugars and cholesterol to obscure molecules that appear in significant numbers only when someone is sick.

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Rebecca Saive

Assistant Professor Applied Physics & Co-founder ETC Solar

The silver lines that crisscross the face of solar panels are essentially metal wires. They’re necessary to channel the electric current flowing out of the cells, but they reflect about 5% of the sunlight that reaches them, creating the single biggest drain on their efficiency.

Rebecca Saive, an assistant professor in applied physics at the University of Twente in the Netherlands, has invented a novel type of “front contact” that addresses this problem, reducing the wasted sunlight and improving the performance of solar photovoltaics. Read More

Anastasia Volkova

CEO and Co-founder at Regrow and Flurosat

If there’s one thing that frustrates Anastasia Volkova, it’s inefficiency. So when she realized she could combine remote sensing data with scientific modelling to improve crop yields, reduce the use of agricultural chemicals, and make better use of water, she knew she’d found her life’s work. It didn’t matter that she was still pursuing her doctorate in aerospace at Sydney University or that she would need to single-handedly raise more than $5 million in startup money: Volkova, the daughter of a self-taught botanist and the goddaughter of a successful farmer, wanted to fix what she thought was wrong with large-scale farming. Read More

This is the Female Entrepreneurs under 35 MIT.

Atima Lui

Lui is now deploying an AI-based app called Nudemeter to try to fix that problem. Through photos and a short quiz, it determines a user’s skin colour, accounts for how the skin is illuminated, predicts changes in skin tone through the year, and helps consumers of any complexion choose makeup colours that work with their skin.

Lui has managed to build a business around Nudemeter, but her goals go beyond the technology itself. Growing up, she says, she was shaped and hurt by society’s assumptions about “who gets to be an entrepreneur, or who gets to be a technologist.” That’s something else she’s trying to fix. Read More

This is the Female Visionaries under 35 MIT.

Leilani Battle

Postdoctoral Researcher at University of Washington, Paul G. Allen School of Computer Science & Engineering

When Leilani Battle was working on her PhD, she helped develop ForeCache, a tool designed to help researchers browse large arrays of data—for instance, scanning high-resolution satellite images to look for areas covered with snow. The goal is to reduce latency, so that a user can pan and zoom across the data set without perceptible delay. A common way to do this is to predict which parts of the data a user is likely to need and then “prefetch” them. But how to predict what to prefetch? That depends on understanding the user’s behavior. read More

Morgan Beller

General Partner @ NFX | Co-creator of Diem≋ (fka Libra)

In the summer of 2017, Morgan Beller approached her supervisor on Facebook’s corporate development team with a proposal: what if she began spending the bulk of her job researching how the social-media giant could enter the digital currency market? Beller was so new at Facebook that she was still completing her orientation, but she’d cut her teeth at a venture capital firm, where she’d worked on early cryptocurrency investments. She could see that a seismic shift in the global financial community was coming. Read More

Eimear Dolan

SFI Royal Society University Research Fellow and Lecturer Biomedical Engineering

Medical implants are often thwarted as the body grows tissue to defend itself. She may have found a drug-free fix for the problem. When Eimear Dolan first worked to develop implantable medical devices to treat type 1 diabetes, she and her colleagues had to overcome a common roadblock. Their problem was one that’s long dogged makers of devices like pacemakers, insulin delivery systems, and breast implants: when the body senses an implanted foreign object, it constructs a protective wall of fibrous tissue. This reaction, known as the foreign body response, is one of the main reasons medical implants fail. Read More

Bo Li

Assistant Professor at University of Illinois at Urbana-Champaign

By devising new ways to fool AI, she is making it safer. A few years ago, Bo Li and her colleagues placed small black-and-white stickers on a stop sign in a graffiti-like pattern that looked random to human eyes and did not obscure the sign’s clear lettering. Yet the arrangement was deliberately designed so that if an autonomous vehicle approached, the neural networks powering its vision system would misread the stop sign as one posting a speed limit of 45 mph. Read More

Rose Faghih

Assistant Professor of Electrical Engineering |& Director of University of Houston's Computational Medicine Lab

Her sensor-laden wristwatch would monitor your brain states. If Rose Faghih’s project pans out, a seemingly simple smartwatch could determine what’s happening deep inside your brain. Faghih has developed an algorithm to analyze otherwise imperceptible changes in sweat activity—a key indicator of stress and stimulation. Using two small electrodes attached to the back of a smartwatch, she can monitor changes in skin conductance caused by sweat. Signal-processing algorithms then allow Faghih to correlate those changes with specific events, such as a PTSD-related flashback or even just wandering attention, in order to pinpoint the person’s brain state. Read More

Inioluwa Deborah Raji

Founder Project Included

Her research on racial bias in data used to train facial recognition systems is forcing companies to change their ways. The spark that sent Inioluwa Deborah Raji down a path of artificial-intelligence research came from a firsthand realization that she remembers as “horrible.” Raji was interning at the machine--learning startup Clarifai after her third year of college, working on a computer vision model that would help clients flag inappropriate images as “not safe for work.” The trouble was, it flagged photos of people of colour at a much higher rate than those of white people. The imbalance, she discovered, was a consequence of the training data: the model was learning to recognize NSFW imagery from porn and safe imagery from stock photos—but porn, it turns out, is much more diverse. That diversity was causing the model to automatically associate dark skin with salacious content. Read More

Adriana Schulz

Assistant Professor at Paul G. Allen School of Computer Science & Engineering

Her tools let anyone design products without having to understand materials science or engineering. Adriana Schulz’s computer-based design tools let average users and engineers alike use graphical drag-and-drop interfaces to create functional, complex objects as diverse as robots and birdhouses without having to understand their underlying mechanics, geometries, or materials. “What excites me is that we’re about to enter the next phase in manufacturing—a new manufacturing revolution,” says Schulz. One of her creations is Interactive Robogami, a tool she built to let anyone design rudimentary robots. A user designs the shape and trajectory of a ground-based robot on the screen. Schulz’s system automatically translates the raw design into a schematic that can be built from standard or 3D-printed parts. Read More

This is the Female Humanitarians under 35 MIT.

Katharina Sophia Volz, PHD

CEO & Founder at OccamzRazor

A loved one’s diagnosis led her to employ machine learning in the search for a Parkinson’s cure. In 2016, Katharina Volz received news that someone close to her had Parkinson’s. At the time Volz had just finished her PhD at Stanford and was locked into a well-earned career in academic research, working on stem cells. But the news changed all that. “I just knew I could actually make a difference,” she says. “Sometimes you feel helpless. But actually I felt deeply responsible for finding a way to get curative treatments for this disease, because I knew I could do something about it.” Volz now leads a company, OccamzRazor, that has successfully married machine learning with biomedical research and is pushing the search for a Parkinson’s cure. Read More

This is the Female Pioneers under 35 MIT.

Ghena Alhanaee

PhD Candidate at University of Southern California

Early on in her days as a doctoral student at the University of Southern California, Ghena Alhanaee stumbled upon a disturbing set of facts. The countries of the Persian Gulf, including her native United Arab Emirates, were far more vulnerable to disaster than she’d realized. Not only was the Gulf itself one of the world’s largest oil and gas production zones, with more than 800 offshore platforms and thousands of tankers passing through its shallow waters every year, but the UAE was also building the Arab Peninsula’s first nuclear power plant. Meanwhile, several Gulf countries relied almost exclusively on desalinated Gulf water for drinking, with emergency supplies for just two or three days. “If something were to happen, and desalination plants weren’t able to operate, right now there really is no backup plan,” Alhanaee says. Read More

Lili Cai

Postdoctoral Researcher at Stanford University

She created energy-efficient textiles to break our air-conditioning habit. Lili Cai has created nanomaterial-based textiles the thickness of a normal T-shirt that can keep you warm or cool you off. Cai’s work takes advantage of the fact that human skin strongly emits infrared radiation in a specific range of wavelengths. By manipulating the ways in which her fabrics block or transmit radiation in this band, she has produced multiple textiles that can have different effects on temperature. To heat the body, Cai created a metallized polyethene textile that can minimize heat radiation loss but is still breathable. Compared with normal textiles, it keeps people about 7 °C warmer. Under direct sunlight, her cooling fabric, a novel nanocomposite material, can cool the body by more than 10 °C. Read More

Jennifer Glick

Quantum Computing at IBM

If quantum computers work, what can we use them for? She’s working to figure that out. The world’s biggest machine, the Large Hadron Collider, was built to help answer some of the most important questions in physics. To do that, the scientists behind the particle collider have to be able to process and understand the massive amounts of data from the machine. They want to be able to tell whether certain particles are produced in high--energy collisions taking place at nearly the speed of light. The LHC can produce over a petabyte of data per second from one billion particle collisions, requiring about one million processor cores spread out around the world to analyze and understand what would otherwise be chaos. What does all that data mean?

Source: MIT Tech Review

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