2022 Class of Siebel Scholars Includes Five Illinois CS Graduate Students
9/23/2021 10:30:34 AM
Five Illinois CS graduate students – Garvita Allabadi, Shengyu Feng, Revanth Gangi Reddy, Eleanor Wedell and Yiqing Xie – earned recognition for both academic excellence and leadership potential as part of the 2022 class of Siebel Scholars.
Founded in 2000, Siebel Scholars has now recognized more than 1,600 of the most talented students from the world’s leading graduate schools for business, computer science, bioengineering and energy science. The program is funded and run by the Thomas and Stacey Siebel Foundation.
“Every year, the Siebel Scholars continue to impress me with their commitment to academics and influencing future society. This year’s class is exceptional, and once again represents the best and brightest minds from around the globe who are advancing innovations in healthcare, artificial intelligence, financial services, and more,” said Thomas M. Siebel (BA History ’75, MBA ’83, MS CS ’85), Chairman of the Siebel Scholars Foundation. “It is my distinct pleasure to welcome these students into this ever-growing, lifelong community, and I personally look forward to seeing their impact and contributions unfold.
Garvita Allabadi came to Illinois CS as a graduate student after earning a bachelor’s degree from Indraprastha Institute of Information Technology (IIIT) in Delhi. Her professional background includes experience with Microsoft India and a current internship with Amazon, while her research here focuses on developing scalable and optimized algorithms for various agricultural tasks using distributed machine learning on edge devices.
To accomplish her research goals, she joined professor Vikram Adve’s LLVM Compiler Infrastructure research group. Allabadi began in program analysis and software engineering but finds motivation from digital agriculture because it presents a unique ability to directly impact real life scenarios.
Specifically, her current research focuses on two topics. First, she is investigating “Efficient Machine Learning and Inference for Digital Agriculture.” Allabadi wants to find out more about ways in which machine learning techniques can alleviate the agricultural labor crisis, encourage sustainable crop management practices, and enhance farm profitability. Second, she conducts work in “Soil Health and Monitoring,” which allows her to explore the practical nature of a soil moisture sensor at a time when there is a lack of small, low-power, and low-cost sensing devices in the industry.
In addition to her academic and professional accomplishments, Allabadi is devoted to encouraging the growth of women in tech. Before joining Illinois CS, she was an active member of the Women@Microsoft group and worked with senior women leaders at Microsoft’s “Women in Software Engineering” (WISE) program. Additionally, Allabadi has worked multiple roles with the annual Grace Hopper Celebration of Women in Computing, which offers one of the largest gatherings of women technologists.
Graduate student Shengyu Feng honed his research interest in data mining and deep learning while working with adviser and Illinois CS professor Hanghang Tong. Additionally, Feng has grown more experienced in temporal scene graph prediction through a research internship with the Intel AI Lab. Feng’s growth in these areas has led to a long-term research goal of rendering the logic reasoning ability to artificial intelligence, and enrich its applications to complex tasks like autonomous driving and multimedia systems.
To achieve his goals, Feng has worked on a wide range of tasks, including deep reinforcement learning, node classification, event coreference, image classification and video understanding. As an undergraduate student at the University of Michigan, he specifically worked on deep reinforcement learning.
This has led to current research work in graph contrastive learning, which is a self-supervised learning method that can generate high-quality representations of the data. Another of Feng’s projects is focused on multimedia event coreference, which is critical to event understanding in news articles. Finally, he has delved into visual relation extraction because visual data usually contains abundant relationships making it a meaningful problem to help solve.
Outside of his notable academic and research-based achievements, Feng is devoted to organizing student activities and helping junior schoolmates. He achieves this through organizing alumni activities and career workshops. Feng is also a teaching assistant for two different courses and co-led a project with AIFARMS, an NSF AI Institute hosted at the University of Illinois Urbana-Champaign.
In his first year as an Illinois CS graduate student, Revanth Gangi Reddy has proven his dedication to Artificial Intelligence research – particularly in its applications to natural language processing. Since working with Illinois CS adviser Heng Ji, Reddy has already published five papers building off his experience as an undergraduate student and professional.
Reddy’s commitment to AI began when he earned his bachelor’s degree from Indian Institute of Technology in Madras – where he focused on graph grammars and visual question answering. That experience built toward professional experience with Microsoft as a software engineer for the Data Integration team. Additionally, he earned a position with IBM Research AI as an AI resident.
In addition to his academic pursuits, Reddy is also the Co-founder and CTO of Iris News, which he is building as a social news application that unifies the news experience by providing news aggregation, story summarization, and a discussion platform to promote consensus and reduce polarization. His activity in other areas is deep, too. Reddy reviewed papers for multiple top-tier academic conferences, taught mathematics to middle school students in Chennai, and led the sponsorship team, as well as web-operations team, for multiple events during his undergraduate studies at IIT Madras.
His current research includes “MUMUQA: Multi-Media Multi-Hop News Question Answering via Cross-Media Grounding” and “Towards Robust Neural Retrieval Models with Synthetic Pre-Training.” This work speaks to his research goals in the field of natural language understanding, which appeals to him as a way to build AI systems that can aid humans in learning from text. Specifically, he’s interested in domain adaption of question answering systems, to extend it to scenarios with very little annotated data.
Eleanor Wedell puts her background from a bachelor’s degree in Mathematics from Drexel University to good use as a graduate student now focused on graph theoretical and machine learning solutions to outstanding problems in bioinformatics and scienceometrics. Prior to joining adviser Tandy Warnow at Illinois CS, Wedell worked as a programmer analyst for Innovative Software Solutions, Inc.
In just a year researching with Warnow, she has already made contributions to phylogeny estimation through the new eXtended-Range (XR) framework, which provides the most accurate and scalable phylogenetic placement. Her work addresses two of the outstanding problems today in biology: understanding how life evolved and understanding biodiversity. The problem derives from a need for very large phylogenetic trees – in some cases including upwards of 100,000 leaves – to prove accurate scientific discoveries in this area. Before now, accurate phylogenetic placement into large trees has remained out of reach.
But the XR framework she has developed is able to simply and effectively overcome this scalability challenge. Citing this as a breakthrough in phylogenetic placement, Wedell stated that it can obtain more accurate sequence placements with the use of larger, more densely sampled trees. Looking ahead, she will focus on speeding up the XR framework with respect to the number of DNA sequences that can be placed in a single run.
In terms of leadership, Wedell remains devoted to learning how best to work with others to help achieve goals together. She’s especially inspired by making a broad community impact, which is why she took full advantage of an opportunity to work in an area that helped provide benefits for union funds. She has since believed that she can make more of an impact by continuing her education, which is also why she found serving as a teaching assistant so fulfilling.
Yiqing Xie joined adviser Jaiwei Han’s data mining research group to achieve her research goals, which are focused on automatically extracting knowledge from massive unstructured data. Beginning with a broader research view, she narrowed her focus from other topics that included set expansion and friend recommendation. Along the way, her work has been accepted by top conferences like WWW, KDD, IJCAI and EMNLP.
Xie joined Illinois CS having graduated from Hong Kong University of Science and Technology with a bachelor’s degree in Computer Science and a double major in Mathematics. Xie’s conviction in her research comes from a belief that it should tackle real world problems. This mindset continued outside of academia, when she was also a research intern at Alibaba in 2020 exploring few-shot friend recommendations under multiple scenarios.
Up to this point, Xie’s research focused on automatically organizing unstructured data into structures to better explore, understand and analyze massive data. This is inspired by the access so many have to a massive amount of data almost everywhere and in various forms – including news articles, social media posts, user behaviors and interactions, etc. Moving forward, her long-term goal is to acquire information from large-scaled unstructured data to continue progressing on this topic.
Away from the classroom, Xie dedicated herself to helping others fulfill their goals. That’s why she established the Mainland Women’s Basketball Team. Her enthusiasm for the sport bridged a gap that other participants were also seeking at the time. Through that experience, along with a stint as the promotion secretary for the university’s Photographic Society and time spent in visual and vocal art, Xie learned that she enjoys working with others to find out more about their passions and to help them achieve what they want out of any experience.