ACM-W would like to announce Dr. Manya Ghobadi as this year’s recipient of the ACM-W Rising Star Award! The ACM-W Rising Star Award recognizes a woman whose early-career research has had a significant impact on the computing discipline.

Dr Manya is currently an Associate Professor at the Massachusetts Institute of Technology (MIT) in the Electrical Engineering and Computer Science Department.

Congratulations on winning the ACM Women Rising Star Award. Can you tell us about your journey in the field of computer science and technology? What inspired you to pursue this field, and what challenges did you face along the way?

Thank you for the warm congratulations on receiving the ACM Women Rising Star Award. I’m deeply honored and humbled by this recognition. My journey in computer science and technology began during my undergraduate studies at Sharif University of Technology in Tehran, Iran, where I pursued a Bachelor’s degree in Computer Engineering. It was during this time that I developed a strong passion for technology, driven by the potential of using computation to make a positive impact on society.

My inspiration to delve further into the field came during my graduate studies at the University of Victoria and later at the University of Toronto, where I had the opportunity to research and explore my interests in congestion control and data center networks. These fields, coupled with my fascination for hardware-software co-design, optical networks, and network optimization, have shaped my career and research trajectory.

As I moved through my academic and professional career, I faced several challenges. Adapting to new work environments and cultures, such as during my time at Google and Microsoft Research, presented its own unique challenges. These experiences, however, helped me grow and learn the importance of perseverance, resilience, and embracing diversity.

In my current role at MIT, I continue to focus on my research interests, including networks for machine learning. I hope to contribute to the development of cutting-edge technologies that will revolutionize how we compute, communicate, and solve complex problems.

You initially spent some time in the industry at Microsoft Research and Google before taking up a position at MIT. What prompted you to make the switch from industry to academia? How easy/difficult is it to make the switch?

At both Microsoft Research and Google, I had the privilege of working with some of the brightest minds in the industry. My time there provided me with invaluable insights and hands-on experience, and I learned a lot about cutting-edge technologies and research methodologies. However, as fulfilling as my work in the industry was, I realized that I deeply missed the joy of working with students and contributing to their growth and development.

I always had a passion for mentoring and sharing knowledge, and academia provided the perfect opportunity to combine that passion with my research interests. The decision to transition from industry to academia was driven by my desire to contribute to the development of the next generation of computer scientists and engineers, fostering a collaborative environment where students could learn and grow.

In terms of the ease of making the switch, I would say it depends on the individual and their specific goals and circumstances. For me, the transition was relatively smooth, as I was able to leverage my industry experience and research background to devise next-generation solutions. Moreover, the skills and knowledge I gained in the industry were highly applicable to my new role in academia, and I found that I could effectively use my experiences to guide my research and teaching endeavors.

According to you, what are the most pressing problems in Computer Networks today? How do you think your research is making a difference in addressing these problems, and what impact do you hope it will have?

The most pressing problems in computer networks today are the increasing demand for efficient network infrastructures that can support the growing complexity and scale of new applications, such as machine learning, video calls, telepresence, augmented reality, and healthcare. As these applications evolve, there is an urgent need for scalable, cost-effective networks that provide high bandwidth, low end-to-end latency, and high availability, while minimizing energy consumption.

My research is focused on addressing these challenges by developing next-generation systems for emerging applications. A key aspect of my work involves enabling physical-layer reconfigurability in modern networks to achieve high throughput, low latency, and fast recovery from failures. Utilizing advanced hardware, such as optical devices, I develop network architectures, algorithms, and protocols to optimize resource use, energy consumption, and high availability.

For instance, the ever-growing demand for machine learning-based services has led to a steady increase in the dataset and model sizes of deep neural networks. Although specialized hardware accelerators and software stacks have provided significant speed-up in compute capabilities, large-scale deep neural network models still require enormous computational resources and consume substantial amounts of energy. The overarching goal of my work is to build fast, efficient, and sustainable machine learning-centric systems.

By addressing the challenges posed by the growing complexity and scale of contemporary applications, I hope that my research will provide a foundation for the real-world deployment of dynamically reconfigurable networks. This will enable better support for machine learning applications, improve the performance of network-based services, and contribute to a more sustainable, energy-efficient future.

In one of your most cited papers, “OpenTCP: Rethinking end-to-end congestion control in software-defined networks,” which was written in 2012, you and your co-authors argued for the need for a congestion control adaptation mechanism in datacenter networks. How have the insights you presented in this paper changed or held up since then?

The insights presented in the OpenTCP paper have largely held up over the years, and the need for a congestion control adaptation mechanism in datacenter networks remains as relevant today as it was then. OpenTCP has helped network operators define rules for tuning TCP as a function of network and traffic conditions, leveraging the global network view available at the network controller for faster and more accurate congestion control decisions. This shift in perspective has sparked further research into developing more sophisticated and adaptable congestion control algorithms that cater to the unique requirements of modern network applications and datacenter environments.

Despite these advancements, congestion control is still not a completely solved problem. As network infrastructure continues to evolve and new applications emerge, we must remain proactive in developing innovative solutions to address the challenges of congestion control in increasingly complex environments. This includes taking into account the unique demands of emerging applications that place different strains on network resources.

For example, in a recent paper published in 2022, my group demonstrated that fair-sharing, which has long been considered the holy grail of congestion control algorithms, is not necessarily a desirable property for machine learning training clusters. We showed that for specific combinations of jobs, introducing unfairness can improve the training time for all competing jobs. This finding underscores the importance of re-evaluating traditional congestion control paradigms and designing algorithms that cater to the specific requirements of modern network applications, such as large machine learning training jobs.

Based on your experiences studying and working at esteemed academic institutions like UofT and MIT, what advice would you give to aspiring researchers looking to maximize their potential and make the most of their time in academia?

Based on my experiences, I would offer three key pieces of advice to aspiring researchers looking to maximize their potential and make the most of their time in academia:

1. Cultivate curiosity and passion: Pursuing a research career requires genuine curiosity and passion for your chosen field. Stay open to new ideas and dive deep into subjects that truly interest you. Your enthusiasm will not only fuel your work but also inspire those around you.
2. Embrace challenges and learn from failure: Research is often a process of trial and error. Don’t be disheartened by setbacks; instead, use them as opportunities to learn and grow. Embrace challenges and remain persistent in the pursuit of your goals.
3. Collaborate and network: Engage with your peers and researchers from other disciplines. Collaboration often leads to novel insights and innovative solutions. Attend conferences, workshops, and seminars to expand your network, as these connections can lead to fruitful research partnerships and future career opportunities.

As a role model for young women in technology, how do you think we can encourage more women to pursue careers in this field?

One way to encourage more women to pursue careers in technology is by providing early exposure and education in the field. Introducing girls to technology and computer science at a young age can spark their curiosity and demonstrate the potential for creativity and innovation within the field. As they grow older, connecting them with strong female role models and mentors can offer valuable guidance, support, and inspiration, showing them the diverse range of successful women who have built careers in technology.

Creating inclusive and supportive environments is also essential. By fostering an inclusive culture within academic institutions and organizations, we can ensure that everyone has access to equal opportunities, regardless of gender. This can be achieved through policies and practices that encourage participation in networking and professional development events, which can help develop crucial connections and boost their confidence.

As I reflect on my own journey, I’m grateful for the opportunities and support I’ve received, and I’m excited to continue contributing to the advancement of technology. My hope is that, by sharing my experiences and insights, I can inspire the next generation of women in tech to break barriers and make their own lasting impact on the world.

Chandra Burnham is our new ACM-W Website Manager, effective September 2022. Chandra is a full-stack software engineer at JPMorgan Chase & Co. in Seattle, Washington. She completed her Bachelors of Science in Computer Science with a minor in Informatics in 2022 at the University of Washington, United States.

At JPMorgan Chase, Chandra participates in firm-wide diversity and inclusion efforts such as Women on the Move, the company’s initiative to support women in their careers. During her undergraduate studies, Chandra served as an officer for both her university’s ACM-W and ACM student chapters, helping to coordinate community-building events, design marketing graphics, and develop the student chapter websites. Chandra also volunteered as a computer science mentor for middle and high school girls through the University of Washington’s Girls Who Code Club in 2020. In 2021, Chandra was selected to be a representative for ACM-W at the 2021 Grace Hopper Celebration, raising awareness about ACM-W’s impact and encouraging attendees to get involved in their local chapters. Chandra looks forward to continuing her service with ACM-W at the global level.

Taneea S Agrawaal will be the next ACM-W Newsletter Editor, effective September 2022. Taneea is a PhD student in the Computer Science Department at University of Toronto, Canada. She completed her Bachelors in Technology from IIIT Delhi, India in 2018, and worked as an Engineering Associate at Goldman Sachs, India before starting her graduate study in 2021.

Taneea’s research work is interdisciplinary. She combines Human-Computer Interaction techniques with Climate Science, exploring the role of social values in Climate Science, with a special focus on climate-vulnerable groups. She is an alumnus of Rails Girls Summer of Code (RGSoC) 2016 and has also served on the program committee of RGSoC 2020. Taneea has been an active participant in several diversity initiatives in India, and has led the Rails Girls New Delhi and Indian Women in Engineering chapters. An avid reader with a penchant for writing, she also led the blog and the literary society at IIIT Delhi. She has continually mentored students in Computer Science since she first went to university. Most recently, she has been involved with HER Code Camp and Graduate Application Assistance Program (GAAP) in Toronto.

Ruth Lennon, current chair of ACM-W Europe, has been selected as the next Global Chair of ACM-W. Ruth is the director of Craobh Technology Consulting, an organization that provides personalized solutions to industry problems.

Ruth is also a Lecturer with 20 years of experience in the Department of Computing in Letterkenny Institute of Technology, Ireland. Ruth’s research interests focus on enterprise scale systems with a particular focus on DevOps and Cloud technologies. She has been a member of many technical panels and committees including chairing the NSAI/TC 2/SC 11 on cloud and distributed systems, and working on the IEEE 2675 DevOps standard. Ruth’s goal in DevOps is to ensure that security and performance are seen as core to development projects just as it is in configuration projects.

Ruth has been a member of the ACM for over 20 years and is the Chair of the ACM-W Europe. She has worked on projects to support and encourage women in computing and engineering career pathways for as long as she has been in the ACM. Highlighting the vital role that women can play in any technical team is core to her voluntary work.

When asked about her vision for ACM-W Ruth states, “I look forward to working with the team to define a strategic approach to build stronger international links in our global community of skilled, collaborative and enthusiastic researchers and practitioners. Over the next two years we will explore new ways to provide greater value to our members locally, regionally and globally.”

ACM-W would like to announce Dr. Minlan Yu as this year’s recipient of the ACM-W Rising Star Award. The ACM-W Rising Star Award recognizes a woman whose early-career research has had a significant impact on the computing discipline. 

Minlan Yu is a Gordon McKay Professor at the School of Engineering and Applied Sciences, Harvard University. Dr. Yu’s research focuses on redesigning the large-scale network infrastructure and making it fundamentally easier to manage many heterogeneous devices while achieving high performance and reliability for diverse applications. In particular, Dr. Yu has made groundbreaking contributions to network telemetry, performance diagnosis at fine timescales, offloading L4-L7 functions to programmable switches, and SDN-based network management. Dr. Yu’s work goes a full circle from important practical problems, transformative architectural design, creative algorithms and data structures, to end-to-end system design and implementations. 

Dr. Yu was recognized by various awards such as the NSF CAREER award, 10 Women in Networking/Communications That You Should Know in 2016, faculty awards from Google, Facebook, VMWare, and SIGCOMM doctoral dissertation award. Many of her works have led to deployed systems in the world’s largest production networks and adopted designs in commercial switch chips.  Her work has also resulted in IETF standards, patents, and open-source tools for developers and researchers. Before Harvard, Dr. Yu was faculty at Yale University and University of Southern California, a postdoctoral researcher at UC Berkeley, and obtained her Ph.D. in Computer Science from Princeton University.

Dr. Nutan Limaye is an associate professor in the Computer Science Department at IT University of Copenhagen, Denmark. Before this, she was an associate professor in the Department of Computer Science and Engineering, IIT Bombay, India. She finished her Ph.D. at the Institute of Mathematical Sciences (IMSc) Chennai, India in 2009. She did a one-year postdoc stint at TIFR Mumbai, before joining IIT Bombay in 2010. She was associated with the Association of Computing Machinery, India (ACM, India) as the vice-chair of the ACM-W from 2019 to 2021. She was also the treasurer for Indian Association for Research in Computing Science (IARCS), India from 2018 to 2020. She is an Associate Editor for ACM Transactions on Computation Theory (TOCT). She received the IRCC IIT Bombay Research Publication Award 2019. She has been on program committees of reputed theoretical computer science conferences such as STOC, FOCS, ITCS, and ICALP. Her research interests are in theoretical Computer Science. Specifically, she is interested in Algorithms and Complexity Theory. Her recent research has focussed on Algebraic Complexity Theory and Lower Bounds. 

Dr. My T. Thai is a University of Florida (UF) Research Foundation Professor of Computer & Information Science & Engineering and Associate Director of UF Nelms Institute for the Connected World. Dr. Thai’s current research interests include responsible AI, AI security and privacy, and optimization. The results of her work have led to 7 books and 250+ publications in highly ranked international journals and conferences, including several best papers awards from the IEEE and ACM.  

Dr. Thai has received many recognitions, notable ones including UF Research Foundation professorship, IoT Term Endowed professorship, NSF CAREER Award, and DTRA Young Investigator Award. She is an IEEE Fellow. Among many professional activities, Dr. Thai currently serves as an Editor-in-Chief (EiC) of the Journal of Combinatorial Optimization, EiC of the IET Blockchain journal, and a book series editor of Springer Optimization and its Applications. 

CHUNLEI TANG as a new member of the ACM-W leadership team is a research associate at Harvard Medical School. Tang received her PhD degree from Fudan University in Shanghai, China. Tang’s work begins with an innovative data-mining method built upon her doctoral work and applicable to various fields (e.g., finance, transportation, economics, insurance, bioinformatics, and sociology). She then endeavored to better match data products with their marketing capabilities by tackling business innovation. Inspired by business, she implemented a theoretical innovation for Data Science and proposed the (now-mainstream) definition of the data industry in 2013, stating that the data industry aims to bridge the gap between data science and economics. Being an author of The Data Industry: The Business and Economics of Information and Big Data (Wiley; 2016) and Data Capital: How Data is Reinventing Capital for Globalization (Springer; 2021), Dr. Tang is a recognized advocate for the Data Economy. She also serves as the Founder President of the Harvard Data Entrepreneurship Club. Her current focus is on applying innovation in healthcare, and she believes precision medicine is an application of the data industry.

Chair — ACM-W
Dr. Jodi Tims is a Professor of Computer Science at Baldwin Wallace University in Berea, OH…

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Vice Chair — ACM-W
Reyyan Ayer working at Bilkent University in Ankara, Turkey with a multitude of responsibilities…

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