Abstract Submissions have now concluded.

Overview

The NISS Virtual New Researchers Conference is your chance to present the work you are passionate about—whether it’s your own original research, an important paper you’ve studied, or a review of recent developments in your field. This is a welcoming and supportive environment designed specifically for MS & PhD students, postdoctoral researchers and advanced undergraduate students.

New Researchers Competition – Outstanding Presentation Award:
Cash prizes will be awarded to outstanding presenters in two categories: students and postdoctoral researchers.

Whether you're preparing for your first professional presentation or getting ready for a bigger stage, this conference is also a great opportunity to practice and refine your presentation skills ahead of the ASA Joint Statistical Meetings later this year.

Hosted by the NISS New Researchers Network, this half-day virtual event encourages participants to share ideas, receive feedback, and connect with a network of peers and mentors from across the NISS Affiliate community.

New Researcher Presentations

Participants will present oral presentations at this conference within the following categories:

• • Original Research (their own research work),
  • Literature Research (presentation of a published paper that is not authored by the presenter), or
  • Literature Review (presentation on recent developments in an area -- this would be a chance to present a couple of papers to highlight recent developments in an area of interest.)

Selected oral presentations will involve a 10 minute live presentation.

Registration Details

Registration Fees:

• • $35 General Admission
  • $25 NISS Affiliate Admission.

Please reach out to mglenn@niss.org for the promo code for NISS Affiliates, and also for anyone who requires financial assistance. 

Conference Agenda

June 5, 2026 | 1:00 – 5:00 PM ET 
21 talks | 10 minutes each 

1:00 – 1:05 | Welcome & Opening Remarks 

Chaired By: Sharmistha Guha, PhD, Chair of the 2026 NISS Virtual New Researchers Conference; Assistant Professor, Department of Statistics, Texas A&M University 

1:05 – 2:05 PM | Session 1: Machine Learning & High-Dimensional Statistics 

Chaired By: Jianghu (James) Dong, PhD, Assistant Professor, UNMC Department of Biostatistics and Assistant Professor, UNMC Internal Medicine Division of Nephrology 

1. Pengfei Lyu — Bias-Corrected Data Synthesis for Imbalanced Learning 
2. Jiayi Xin — Conformal Prediction with Paraphrase-Aware Scoring for LLM Uncertainty Quantification 
3. Tomoki Okuno — Debiased Machine Learning for Partially Linear Accelerated Failure Time Models 
4. Hengwei Xing — Projected CUSUM Control Chart for High-Dimensional Data 
5. Adeeba Tak — Multi-Tier Inference Strategy for High-Dimensional Omics Studies with Small Samples 
6. Dyani Peterson — Machine Learning for Predicting Autism Spectrum Disorder 

2:05 – 2:15 | Questions/Feedback Discussion & Break

2:15 – 3:05 PM | Session 2: Biostatistics & Biomedical Applications 

Chaired By: Georgia Smits, PhD, Postdoctoral Researcher, University of Washington 

1. Shubhadeep Chakraborty — A Two-Stage Dose Optimization Framework for Oncology Drug Development 
2. Jennifer Antwi — Dual-Route Wells–Riley Extensions for Norovirus Infection Risk in Ghanaian Pediatric Wards 
3. Oladimeji Adewuyi — Bayesian Hierarchical Spatiotemporal Prediction of Multi-pathogen Outbreaks 
4. Taiwo Ayeni — Quadratic Functional Variable Transformation of the Exponential-Gamma Distribution 
5. Henghua Xing — Conditional Multivariable Mendelian Randomization for Reducing LD-Induced Pleiotropy 

3:05 – 3:15 | Questions/Feedback Discussion & Break

3:15 – 4:05 PM ET | Session 3: Nonparametric Methods, Statistical Computing & Causal Studies 

Chaired By: Jason Byung Jae Cho, PhD Student, Department of Statistics, Cornell University 

1. Saksham Jain — Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing 
2. Duoduo Ying — Efficient Representation and Construction of Space-Filling Designs 
3. Stephen Agyeah — Distribution Function Estimation for Sensitive Quantitative Variables 
4. Hwanwoo Kim — Enhancing Gaussian Process Surrogates for Blackbox Optimization 
5. Abhinandan Dalal — Partial Identification of Causal Effects for Endogenous Continuous Treatments 

4:05 – 4:55 PM | Session 4: Spatial, Social, & Applied Statistics 

Chaired By: Hannah Waddel, PhD, Postdoctoral Researcher, Los Alamos National Laboratory (LANL) 

1. Manushi Siriwardana — Mixture-Based Nonparametric Estimation of Spatial Covariance Functions with Applications to HIV 
2. Jacob Ornelas — When Is Volume a Sufficient Statistic? A Latent State Approach to Joint Extreme Events 
3. Alex Tapia — The Case for Reversing the Ban on AI Rent Pricing in San Francisco 
4. James Braverman — Linear Regression and Analysis of Inline Acceleration of the Saturn V Vehicle 
5. Justice Effah — Optimizing Targeted Prostate Cancer Therapy via Deep Reinforcement Learning 

4:55 – 5:00 | Awards & Closing Remarks 

Chaired By: Sharmistha Guha, PhD, Chair of the 2026 NISS Virtual New Researchers Conference; Assistant Professor, Department of Statistics, Texas A&M University

The National Institute of Statistical Sciences (NISS) is a national organization that works on issues related to information and quantitative analysis. The goal of the NISS New Researchers Network is to create connections among undergraduate and graduate students from different academic institutions and early-career professionals including Postdoctoral Researchers. The NISS New Researchers Network fosters collaboration and support among early-career statisticians, graduate students and undergraduate students offering resources and opportunities for professional growth.