Five CS Students Named 2024 Siebel Scholars

The Siebel Scholars Foundation announced its 2024 Class of Siebel Scholars, honoring 83 exceptional graduate students from top universities around the world in the fields of bioengineering, business, energy science, and computer science. Five Illinois CS students were named to this year’s class: Shivam Agarwal, Seemandhar Jain, Vidya Kamath Pailodi, Shradha Sehgal, and Ruizhong Qiu. 

 

The Siebel Scholars Class of 2024 joins an esteemed group of past Siebel Scholars to form a professional network of over 1,800 researchers, entrepreneurs, and philanthropists striving to find solutions to society’s most pressing challenges.

 

“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, 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.” 

 

Congratulations to the following Illinois CS students:

 

Shivam Agarwal is a second-year graduate student under the supervision of Professor Jiawei Han. Shivam researches data mining, trustworthy AI, and natural language processing (NLP) with a focus on developing safe, robust, and reliable NLP and machine learning (ML) systems. Before coming to Illinois, Shivam studied at the Manipal Institute of Technology in India. 

 

Previously, he worked with Cisco Systems as an electrical product engineer. He closely collaborates with Prof. Tyler Derr, Prof. Lucie Flek, Prof. Preslav Nakov, and Prof. Rajiv Shah on ML and NLP. He interned at Amazon Alexa AI last summer to devise Large Language Models (LLMs) for natural language understanding tasks.

 

He has presented over 20 papers at such prestigious conferences as the Association of Computational Linguistics (ACL) and the International Conference on Data Mining (ICDM). In 2019, his team won first place at the Intelligent Ground Vehicle Competition (IGVC).

 

Seemandhar Jain is a Master of Science student in the Department of Computer Science, working with Professor David Forsyth in the field of computer vision. Seemandhar’s research primarily focuses on the convex decomposition of indoor images and intrinsic image decomposition. He aims to leverage the potential of computer vision to drive meaningful advancements in healthcare.

 

Seemandhar earned a B.Tech. in CSE from the Indian Institute of Technology Indore, India. He has collaborated with professors across global institutions, including IMT Atlantique, the University of Witwatersrand, IITI, and the University of Alberta. His work has been featured in multiple top-tier conferences and journals. He also co-founded a small tech company, HealthAIgnite, as a platform to showcase his innovative research in healthcare and computer vision.

 

Previously, he worked as a research intern with Docomo Innovations and as a software developer with Salesforce. Beyond his academic and professional achievements, he has been an International Mathematics Olympiad rank holder, a UCMAS Scholar, and an ACM ICPC qualifier. His involvement with various NGOs has also earned him the Young Philanthropist Award from the state of Madhya Pradesh, India.

 

Vidya Kamath Pailodi is a second-year graduate student working with Professor George Chacko to explore the field of Computational Scientometrics. Specifically, she is using graph clustering, community detection, and community extraction techniques to understand the mesoscale organization of large scientific networks to gain insights that can assist policymakers, funding agencies, and researchers in planning and evaluating scientific impact in the national interest of an efficient and equitable scientific ecosystem. Vidya has contributed to a project that presents a meta-method for enforcing well-connected criteria on communities in large networks.

 

Before arriving at Illinois, Vidya worked as a software engineer in the thermotechnology department at Robert Bosch Engineering and Business Solutions Private Limited in Bengaluru, India. In that role, she developed multiple tools to aid the development and testing of application software for NEFIT boilers. 

 

Vidya graduated as a Gold Medalist in ECE from the NMAM Institute of Technology in Nitte, India where she earned an undergraduate degree in Electronics and Communication Engineering. 

 

Shradha Sehgal is a second-year graduate student in Computer Science. She is a member of the DAIS lab, where her research focuses on building machine-learning solutions for extracting knowledge from large-scale data. She works with Professor ChengXiang Zhai on creative analogy mining on the web using large language models. She has also collaborated with Professor Arindam Banerjee on developing pre-trained models for satellite imagery data.

 

Shradha completed her undergraduate degree with honors from IIIT Hyderabad, where she was recognized as a top academic performer. She has made significant contributions to the fields of Applied Machine Learning and Social Computing through publications in ACM Hypertext and ASONAM. 

 

Shradha is currently a Machine Learning Intern at Netflix and has previously completed research and engineering internships at Carnegie Mellon University and Google. 

 

Ruizhong Qiu is a second-year graduate student in Computer Science and is working with Professor Hanghang Tong. His research interest lies in non-differentiable problems in machine learning. He has presented papers on related topics at top conferences, including in NeurIPS and KDD. Before attending Illinois, Ruizhong graduated from Tsinghua University in Beijing, China with a B.E. degree in Industrial Engineering. 

 

Ruizhong interned with Qualcomm AI Research, where he worked on code generation with large language models. He also served as a research assistant at Carnegie Mellon University where he studied meta-learning for scalable neural combinatorial optimization. Since 2022, Ruizhong has worked as the lead research assistant of a C3.ai DTI research project.

 

He won the NeurIPS Scholar Award in 2022 and the Conference Presentation Award at Illinois in Fall, 2022. Additionally, he has logged extensive volunteer service over the years, including mentoring high school students and minority groups in computer science to help create a more equitable and diverse computing community for all.

 

For the complete list of 2024 Siebel Scholars, see the news release.

 

The Siebel Scholars program was founded in 2000 by the Siebel Foundation to recognize the most talented students at the world’s leading graduate schools of business, computer science, bioengineering, and energy science. These include Carnegie Mellon University; École Polytechnique; Harvard University; Johns Hopkins University; Massachusetts Institute of Technology; Northwestern University; Politecnico di Torino; Princeton University; Stanford University; Tsinghua University; University of California, Berkeley; University of California, San Diego; University of Chicago; University of Illinois Urbana-Champaign; University of Pennsylvania; and University of Tokyo. 

The Thomas and Stacey Siebel Foundation, a nonprofit, public benefit corporation, was established as a private foundation in 1996. Its mission is to foster programs and organizations that improve the quality of life, environment, and education of its community members. The Siebel Foundation funds projects to support education, the homeless and underprivileged, public health, research, and development worldwide.