Statistical Machine Learning Lab

News

2023

• Mar 2023: Ardhendu receives the NSF CISE Research Initiation Initiative (CRII) award.
• Mar 2023: Paper titled Using Geographic Location-Based Public Health Features in Survival Analysis accepted for publication in the 2023 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) to be held as part of the 2023 ACM Federated Computing Research Conference in Orlando, Florida. Authors are Navid Seidi, Ardhendu Tripathy, and Sajal Das.
• Feb 2023: Ardhendu organizes a programming activity for high school students in the Computer Science Pre-College Initiative event organized in collaboration with the National Society of Black Engineers student group.
• Feb 2023: Ardhendu attends the 37th AAAI Conference in Artificial Intelligence in Washington, DC.
• Jan 2023: Raja Sunkara joins the lab as a graduate research student.

2022

• Dec 2022: In collaboration with the Kummer Center for STEM Education, Ardhendu organizes a hands-on activity for 6-8 grade students in the Computer Science Education Week event.
• Oct 2022: Ardhendu gives an invited talk on Chernoff Sampling for Active Testing and Extension to Active Regression in the LIONS seminar series at Arizona State University.
• Sep 2022: Ardhendu is serving as an Area Chair for the 26th AISTATS conference to be held in 2023.
• Aug 2022: Joshua is accepted into the 2022-23 OURE (Opportunities for Undergraduate Research Experience) cohort and will continue his research in the Statistical Machine Learning Lab.
• Jun and Jul 2022: In collaboration with the Kummer Center for STEM Education, Ardhendu and Navid organize programming activities for high-school students participating in the Jackling and Cyberminer summer camps.
• Mar 2022: Ardhendu gives an invited talk on MaxGap Bandit: Adaptive Algorithms for Approximate Ranking in the Session on Recovering Permuted Data in the 56th Annual CISS conference.
• Jan 2022: Navid Seidi joins the lab as a graduate research student.
• Jan 2022: Paper titled Chernoff Sampling for Active Testing and Extension to Active Regression accepted for publication in the 25th AISTATS conference. Authors are Subhojyoti Mukherjee, Ardhendu Tripathy, and Robert Nowak.
• Jan 2022: Ardhendu Tripathy and Rui Bo from Electrical and Computer Engineering are co-PIs on a grant titled Trustworthy Machine Learning (ML) & Artificial Intelligence (AI)-based Framework Development for Hybrid and Sustainable Energy Systems that has been funded by the Kummer ignition initiative. PI is Syed Alam from Nuclear Engineering department.

2021

• Dec 2021: Lab members organize the 2021 Rolla NeurIPS Meetup. The schedule of talks is in the advertised flyer.
• Oct 2021: Joshua Caruso joins the lab as an undergraduate research student.
• Sep 2021: Shreen Gul joins the lab as a graduate research student.
• Jun 2021: Ardhendu organizes hands-on activities for high-school students participating in Missouri S&T’s Jackling summer camp.
• May 2021: Room 105 in the Computer Science building is assigned to the Statistical Machine Learning Lab.

Lab members

Raja Sunkara

Raja Sunkara is a Master’s student in Computer Science who holds a Bachelor’s degree in Aerospace Engineering from the Indian Institute of Technology, Madras. Prior to pursuing his graduate studies, he worked as a data scientist and research engineer in the fields of deep learning and computer vision. Currently, his research focuses on neural networks and global optimization for black-box functions.

Navid Seidi

Navid Seidi is a Computer Science Ph.D. student at Missouri University of Science and Technology, with research interests in Survival Analysis, Smart Health, Machine Learning, and Neural Networks. He holds a Master’s degree in IT Engineering with a focus on Computer Networks from QIAU in Iran, and a Bachelor’s degree in IT Engineering from PNU in Karaj. With over 12 years of experience as an EHR/EMR software developer and Health Informatics Expert in the health industry, Navid has practical knowledge of Health Informatics.

Shreen Gul

Shreen is a Ph.D. student in Computer Science. She received her BS in Computer Science from the University of Engineering and Technology (UET) Lahore. She is working on active learning methods for neural networks.

Joshua Caruso

Joshua is an undergraduate student enrolled in the Computer Science program at Missouri S&T. He is exploring the phenomenon of neural collapse in the terminal phase of training neural networks.