IBM Research-Tokyo

Emerging Leaders: Female scientists driving our global research agenda

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As March 8, 2018 marks International Women’s Day, this year’s campaign is a #PressforProgress – focusing on gender parity in the community and in the workplace. Since early days at IBM, we have always been led by Thomas J. Watson Jr.’s famous 1953 memo: “It is the policy of this organization to hire people who have the personality, talent and background necessary to fill a given job, regardless of race, color or creed.”

All around the world, female scientists at IBM are pioneering, inventing, designing and creating the technology that will bring us into the next generation of computing. This year, help us celebrate the advancements of some of the female scientists from our emerging lab markets who are helping to transform industries, invent new technologies, and reshape our world through science.


Fatemeh Jalali – Research Scientist, IoT & Cognitive Computing.

Fatemeh holds a BS in Computer Engineering, MSc in IT and PhD in Telecom Engineering. She joined the IBM Research – Australia lab in 2015. Her main research focuses are IoT, Edge computing and cognitive computing and has received multiple awards for her research, the most recent one being selected as one of the 200 Most Qualified Young Researchers in Computer and Mathematics by the Scientific Committee of the Heidelberg Laureate Forum Foundation in 2017. As the Chair of the IEEE Women in Engineering Victorian Section she regularly runs hands-on IoT workshops and hackathons for students, teachers and IT passionate people. Fatemeh also serves on the technical committee (IoT and wearable track) at the Grace Hopper Celebration of Women in Computing 2017-2018, and as the Networking Chair of IEEE ISGT Asia Conference in 2016.

If you could solve one difficult problem using science and technology, what would it be? I would like to use it as a tool to bring people with diverse backgrounds together to solve important problems facing society and improve the quality of life for all. I try to do my part by encouraging the use of science and technology in the educational system to attract and inspire a broad range of young people, especially females since the shortage of women in STEM is a serious issue in Australia.

Mahtab Mirmomeni– Software Engineer, Brain Inspired Computing

Mahtab is currently leading the epilepsy deep learning challenge project with the aim to design deep learning models & algorithms for epileptic seizure detection that enable remote patient monitoring using wearable sensors. She holds a Master of Computer Science from The University of Melbourne and is currently working towards her PhD at the same university. Mahtab is a strong advocate for Women in STEM and is the founder of the Women in Tech society at the University of Melbourne. She is the winner of the 2017 Women Tech Makers scholarship and winner of the 2017 Graduate Women Victoria scholarship and has been invited to talk about her career path in science and technology to high school and university students.

Since the birth of her son in late 2015, Mahtab has focused on supporting mothers in technology and discussing their issues through her personal blog. She loves traveling, hiking and spending time with her young family.

If you could solve one difficult problem using science and technology, what would it be? Australia is a large country with many remote areas that don’t have immediate access to clinicians and physical treatment. I’d like to use science and technology to design methods and systems that facilitate remote patient monitoring. My research specifically focuses on using wearable sensors, which are non-invasive, to track patients and which could inform clinicians at the right time to intervene.


Ana Paula Appel – Research Scientist, Social Data Analytics

Ana Paula is a Research Staff Member and Master Inventor in the Social Data Analytics Group.  Ana Paula has a B.S. in Computer Science from the Federal University of Sao Carlos (UFSCar), a M. Sc. and Ph.D. degree also in Computer Science from the State University of Sao Paulo (USP) under the guidance of Prof. Dr. Caetano Traina Jr. She has also studied at Carnegie Mellon University (CMU) and  Federal University of Sao Carlos (UFSCar). Ana Paula’s research interests are in the field of graph and data mining work, specially applied to social data.

If you could solve one difficult problem using science and technology, what would it be? I would like to make difference in Brazil helping improve government health system using analytics and machine learning methods so people get faster medical care.

Bianca Zadrozny – Manager, Natural Resources Analytics

Bianca leads the Natural Resources Analytics group at IBM Research-Brazil. The group’s mission is to conduct research projects in data-driven and physically-driven analytics, aiming to develop novel technologies that can help in smarter natural resources discovery and exploration. Bianca is mainly interested in machine learning and data mining, both in and outside the lab. Bianca is also active in the machine learning and data mining research communities. She has served on many editorial boards, including the Journal of Machine Learning Research (JMLR), and served on many program committees, including the International Conference in Machine Learning (ICML).

If you could solve one difficult problem using science and technology, what would it be? Agribusiness is currently the main area of growth in the Brazilian economy. But while large producers of commodities such as soybean and sugarcane have access to the latest technology, small producers have more challenges and less access to credit. I believe that science and technology in the area of digital agriculture for a larger variety of crops and tailored to small producers, making access to relevant information and tools for decision-making as well as for better linking producers to consumers, could make a big difference for our region.


Prateeti Mohapatra – Research Scientist, AI for Automation

Prateeti Mohapatra holds a Bachelors and Masters degree in Computer Science. Her interests lie in Statistical Modeling and Analysis, Natural Language Processing, Data Mining and Software Engineering. She has worked at various Research Labs (BEL Central Research Laboratory, and the University of Chicago, USA) before joining IBM in 2015. Her current work involves understanding and information extraction of both structured and unstructured text, helping and assisting end users in making better decisions. In her spare time, she enjoys playing and watching cartoon shows with her daughter.

If you could solve one difficult problem using science and technology, what would it be? The one challenge in my region (Bangalore, India) that I would most like to solve is minimizing traffic and pollution issues. One way could be by increasing citizen awareness and responsibility; making citizens  more aware of the civic issues around them, explaining how the issues are being mitigated and how they as a community can help. For the past year, I have been working on an exploratory social good project “CitiCafe: Citizen Engagement Platform”. The work involves designing and building a conversation-based intelligent platform consisting of a virtual agent and a natural language interface that can present citizens with relevant information and also help them register complaints by asking specific questions. The citizens can interact with the agent using various popular social media platforms like Twitter, Facebook Messenger, Slack etc.

Renuka Sindhgatta – Research Scientist, Cognitive Education Solutions

Renuka and her team at IBM Research in Bangalore, India have been working on building innovative services using state of the art machine learning techniques to transform learning experience across the life of a learner. The services address learners from early childhood to K-12, and from higher education to vocational and corporate. Prior to working in education research, Renuka worked on several solutions to improve efficiency and quality of software development teams using predictive analytics. In her spare time, she practices yoga, and is constantly inspired by her 85 year old yoga teacher, and enjoys listening to music with her daughter.

If you could solve one difficult problem using science and technology, what would it be? In countries like India, quality education and accessible financial services are some of the areas that need improvement. There is also the huge opportunity of having 300M people (and rapidly increasing), using internet and smart phones. Building solutions using leading edge technologies that are capable of analyzing and learning from this deluge of data,will be critical in improving quality of education and financial services. The key challenge however, is to provide innovative services supporting very high volumes at low cost.


Sachiko Yoshihama – Senior Manager, Financial Services & Blockchain Solutions

Sachiko has a passion for applying advanced technologies to industrial challenges in order to make impact on society. She is leading research and development of industry solutions and enjoys discussing with clients to understand each industry’s pain points and explore possible transformation opportunities. After receiving her Ph.D. from Yokohama National University in 2010, Sachiko started her career as a software engineer at the T.J. Watson Research Center where she led development of software architecture to enable the office of the future. She then moved to IBM Research – Tokyo and started research in security, such as trusted computing, information flow control, and Web application security. As she spends most of her work in front of a computer, she enjoys outdoor activities in weekends. She climbed many high mountains in Japan (including Mt. Fuji), and has run more than 10 marathons, although very slowly!

If you could solve one difficult problem using science and technology, what would it be? To transform financial industries with technologies, such as removing friction and resolve inefficiencies of cross-organizational processes by using blockchain.

Miki Enoki – Research Scientist, IBM Research – Tokyo

Miki started her career at IBM Research, focusing on hardware workload optimization. When a major earthquake his Japan, Miki saw an opportunity to investigate a new area of research – how to validate the reliability of information shared on social media. Leading the project as a young researchers, she gathered researchers from different fields to advance the study. While working on this project, she completed the latter half of her doctoral program in computer science at Ochanomizu University. Today, Miki is an executive assistant to the IBM Research – Tokyo lab director where she is eager to broaden her skills in cognitive computing to better understand and respond to the progression of technology. She enjoys taking photos, so wherever she goes, she always has a camera with her.

If you could solve one difficult problem using science and technology, what would it be? More and more people obtain information from social networks, and at the same time, the number of daily decisions we make is also increasing. To help this, she would like to create a secure and high-speed cloud infrastructure that uses AI to generate personalized support and decision making for every user.


Shengjiao Cao – Software Engineer, Blockchain

Shengjiao has been an IBMer since 2015 and holds a BS in Automation from Tsinghua University and  PhD in Electrical and Computer Engineering from National University of Singapore. She is now working with the IBM Center for Blockchain Innovation to bring state-of-art blockchain solutions to various industry and financial organizzations. Shengjiao explored different areas of research, including bioinformatics and image processing during her undergraduate studies and digital signal processing for optical communication in her PhD work. Other than exploring different research opportunities, she also loves to explore the nature world through activities like rock-climbing and mountaineering.

If you could solve one difficult problem using science and technology, what would it be? If Blockchain is the answer, it is more important to be asking, “what is the question”? I would like to solve the “Question” with the “Answer”!
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