The Computing and Information Sciences Program is a PhD program housed in the B. Thomas Golisano College of Computing and Information Sciences.
Dates of Existence2006-present
Documents from 2026
Towards Reliable and Trustworthy Deep Learning through Explainability and Interpretability, Dipkamal Bhusal
Understanding Computer-Mediated Human Experience in Digital-Physical Hybrid Space, Jiangnan Xu
Documents from 2025
Active Learning Methodologies and Applications, Pradeep Bajracharya
Towards Secure Runtime Auditing of Remote Embedded System Software, Adam Ilyas Caulfield
Democratizing Community Discourse Analysis in Computational Social Science, Md Towhidul Absar Chowdhury
Improving the Accessibility of Speech for Deaf and Hard-of-Hearing Individuals Through Affective Captions, Caluã de Lacerda Pataca
Dynamic Defenses to Systematically Secure Exposed Attack Surfaces in Wireless Systems, Naureen Hoque
Identifying Underspecifications in Security Requirements Using a Formal Reasoning Approach, Viktoria Koscinski
Towards Characterizing and Quantifying Interpretability of Knowledge Graph Embedding Models, Narayanan Asuri Krishnan
Crafting Human-AI Collaborative Analysis for Usability Evaluations, Emily Kuang
Using Generative Models for Data Augmentation in Medical Imaging, Nilesh Kumar
Model Explainability: From Post-hoc to Self-explainable, Xin Miao Lin
Advancing Applications of Deep Learning on Network Traffic Analysis and Fingerprinting, Nate Mathews
On the Adaptation of Latent Dynamics Models, Ryan Missel
Uncertainty-Aware Meta-Learning for Learning from Limited Data, Deep Shankar Pandey
Protein Language Models-Based Representation for Post-translational Modification Prediction, Suresh Pokharel
A Robust Learning Framework for Resource-Constrained Domain Adaptation, Xiaofan Que
Parsing of Math Formulas and Chemical Diagrams using Graph-Based Representation and Attention Models, Ayush Kumar Shah
DeFaking Deepfakes: Designing and Evaluating AI-Powered Digital Media, Saniat Javid Sohrawardi
Physics Meets Data: Merging Physics-Based Methods with Deep Learning to Model Complex Systems, Maryam Toloubidokhti
Meshed Trees: A Framework for Resilient Network Algorithms and Protocols, Peter Willis
Documents from 2024
Hierarchical Parameterization in Spherical Domains for Deforming Feature Alignment, Lizhou Cao
Robust Machine Learning Under Vulnerable Cyberinfrastructure and Varying Data Quality, Sergei Chuprov
Towards Algorithm Selection for Efficient Search-Based Software Engineering, Niranjana Deshpande
Improving Adaptation of Deep Learning with Inductive Bias, Xiajun Jiang
Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads, Avinash Maurya
Continual Learning for an Ever Evolving and Intelligent Malware Classification System, Mohammad Saidur Rahman
Learning from Disagreement in Human-Annotated Datasets, Tharindu Cyril Weerasooriya
Robust and Efficient Active Inference for Perception, Action, and Learning, Zhizhuo Yang
Documents from 2023
Human Error Assessment in Software Engineering, Benjamin S. Meyers
Characterizing and Detecting Software Attack Surface Components, Sara Moshtari
Learning to Learn from Sparse User Interactions, Krishna Prasad Neupane
Robust Weakly Supervised Learning for Real-World Anomaly Detection, Hitesh Sapkota
Designing Automatic Speech Recognition Technologies to Improve Accessibility for Deaf and Hard-of-Hearing People in Small Group Meetings, Matthew Shoji Seita
Knowledge Integration for Human-In-The-Loop Machine Learning, Ervine Zheng
Documents from 2019
Transferring Generalized Knowledge from Physics-based Simulation to Clinical Domain, Mohammed Abdullatif Alawad
Documents from 2017
Election-Attack Complexity for More Natural Models, Zack Fitzsimmons
Documents from 2016
Understanding the Impact of Diversity in Software Bugs on Bug Prediction Models, Harold Valdivia-Garcia
Bayesian Inference with Combined Dynamic and Sparsity Models: Application in 3D Electrophysiological Imaging, Jingjia Xu
Documents from 2015
The Role of Situation Awareness Metrics in the Assessment of Indoor Orientation Assistive Technologies that Aid Blind Individuals in Unfamiliar Indoor Environments, Abdulrhman A. Alkhanifer
Effects of Virtual Humans’ Facial Emotional Displays on Persuasion, Yuqiong Wang
Documents from 2014
Probabilistic Modeling and Inference for Obfuscated Network Attack Sequences, Haitao Du
Documents from 2013
Joint optimization of manifold learning and sparse representations for face and gesture analysis, Raymond Ptucha
Documents from 2012
Solving hard problems in election systems, Andrew Lin
Documents from 2010
From medical images to individualized cardiac mechanics: A Physiome approach, Chun Wong
Documents from 2009
Intelligent deployment strategies for passive underwater sensor networks, Erik Golen
Personalized noninvasive imaging of volumetric cardiac electrophysiology, Linwei Wang
