Adapting Biochemical Kripke Structures for Distributed Model Checking. - Susmit Jha; R. K. Shyamasundar (Trans. Comp. Sys. Biology, 2006)

Symbolic Reachability Analysis of Lazy Linear Hybrid Automata. - Susmit Jha; Bryan A. Brady; Sanjit A. Seshia (FORMATS, 2007)

Randomization Based Probabilistic Approach to Detect Trojan Circuits. - Susmit Jha; Sumit Kumar Jha 001 (HASE, 2008)

Random Relaxation Abstractions for Bounded Reachability Analysis of Linear Hybrid Automata: Distributed Randomized Abstractions in Model Checking. - Sumit Kumar Jha 001; Susmit Jha (HASE, 2008)

Beaver: Engineering an Efficient SMT Solver for Bit-Vector Arithmetic. - Susmit Jha; Rhishikesh Limaye; Sanjit A. Seshia (CAV, 2009)

On voting machine design for verification and testability. - Cynthia Sturton; Susmit Jha; Sanjit A. Seshia; David A. Wagner 001 (CCS, 2009)

Localizing transient faults using dynamic bayesian networks. - Susmit Jha; Wenchao Li 001; Sanjit A. Seshia (HLDVT, 2009)

On the Computational Complexity of Satisfiability Solving for String Theories - Susmit Jha; Sanjit A. Seshia; Rhishikesh Limaye (CoRR, 2009)

Statistical Analysis of Privacy and Anonymity Guarantees in Randomized Security Protocol Implementations - Susmit Jha (CoRR, 2009)

Automating Security Mediation Placement. - Dave King 002; Susmit Jha; Divya Muthukumaran; Trent Jaeger; Somesh Jha; Sanjit A. Seshia (ESOP, 2010)

Synthesizing switching logic for safety and dwell-time requirements. - Susmit Jha; Sumit Gulwani; Sanjit A. Seshia; Ashish Tiwari 001 (ICCPS, 2010)

Oracle-guided component-based program synthesis. - Susmit Jha; Sumit Gulwani; Sanjit A. Seshia; Ashish Tiwari 001 (ICSE (1), 2010)

Synthesis of optimal switching logic for hybrid systems. - Susmit Jha; Sanjit A. Seshia; Ashish Tiwari 001 (EMSOFT, 2011)

Synthesis of loop-free programs. - Sumit Gulwani; Susmit Jha; Ashish Tiwari 001; Ramarathnam Venkatesan (PLDI, 2011)

Synthesizing Switching Logic to Minimize Long-Run Cost - Susmit Jha; Sanjit A. Seshia; Ashish Tiwari 001 (CoRR, 2011)

Towards Automated System Synthesis Using SCIDUCTION. - Susmit Jha (2011)

Decision procedure based discovery of rare behaviors in Stochastic Differential Equation models of biological systems. - Arup K. Ghosh; Faraz Hussain 001; Sumit Kumar Jha 001; Christopher James Langmead; Susmit Jha (ICCABS, 2012)

Parameter discovery for stochastic biological models against temporal behavioral specifications using an SPRT based Metric for simulated annealing. - Faraz Hussain 001; Raj Gautam Dutta; Sumit Kumar Jha 001; Christopher James Langmead; Susmit Jha (ICCABS, 2012)

Synthesis of insulin pump controllers from safety specifications using Bayesian model validation. - Sumit Kumar Jha 001; Raj Gautam Dutta; Christopher James Langmead; Susmit Jha; Emily Sassano (Int. J. Bioinform. Res. Appl., 2012)

SWATI: Synthesizing Wordlengths Automatically Using Testing and Induction - Susmit Jha; Sanjit A. Seshia (CoRR, 2013)

CAPED: Context-aware personalized display brightness for mobile devices. - Matthew Schuchhardt; Susmit Jha; Raid Ayoub; Michael Kishinevsky; Gokhan Memik (CASES, 2014)

Game theoretic secure localization in wireless sensor networks. - Susmit Jha; Stavros Tripakis; Sanjit A. Seshia; Krishnendu Chatterjee (IOT, 2014)

Are There Good Mistakes? A Theoretical Analysis of CEGIS. - Susmit Jha; Sanjit A. Seshia (SYNT, 2014)

Discovering rare behaviours in stochastic differential equations using decision procedures: applications to a minimal cell cycle model. - Arup Kumar Ghosh; Faraz Hussain 001; Susmit Jha; Christopher James Langmead; Sumit Kumar Jha 001 (Int. J. Bioinform. Res. Appl., 2014)

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking. - Faraz Hussain 001; Sumit Kumar Jha 001; Susmit Jha; Christopher James Langmead (Int. J. Bioinform. Res. Appl., 2014)

Optimizing mobile display brightness by leveraging human visual perception. - Matthew Schuchhardt; Susmit Jha; Raid Ayoub; Michael Kishinevsky; Gokhan Memik (CASES, 2015)

On ∃ ∀ ∃! solving: A case study on automated synthesis of magic card tricks. - Susmit Jha; Vasumathi Raman; Sanjit A. Seshia (FMCAD, 2016)

On Optimal Control of Stochastic Linear Hybrid Systems. - Susmit Jha; Vasumathi Raman (FORMATS, 2016)

Automated Synthesis of Safe Autonomous Vehicle Control Under Perception Uncertainty. - Susmit Jha; Vasumathi Raman (NFM, 2016)

On Learning Sparse Boolean Formulae for Explaining AI Decisions. - Susmit Jha; Vasumathi Raman; Alessandro Pinto; Tuhin Sahai; Michael Francis (NFM, 2017)

TeLEx: Passive STL Learning Using Only Positive Examples. - Susmit Jha; Ashish Tiwari 001; Sanjit A. Seshia; Tuhin Sahai; Natarajan Shankar (RV, 2017)

A theory of formal synthesis via inductive learning. - Susmit Jha; Sanjit A. Seshia (Acta Informatica, 2017)

Output Range Analysis for Deep Neural Networks. - Souradeep Dutta; Susmit Jha; Sriram Sankaranarayanan 001; Ashish Tiwari 001 (CoRR, 2017)

Specification Inference from Demonstrations. - Marcell Vazquez-Chanlatte; Susmit Jha; Ashish Tiwari 001; Sanjit A. Seshia (CoRR, 2017)

Machine Learning and Formal Method (Dagstuhl Seminar 17351). - Sanjit A. Seshia; Xiaojin (Jerry) Zhu; Andreas Krause 001; Susmit Jha (Dagstuhl Reports, 2017)

Learning and Verification of Feedback Control Systems using Feedforward Neural Networks. - Souradeep Dutta; Susmit Jha; Sriram Sankaranarayanan 001; Ashish Tiwari 001 (ADHS, 2018)

Data Efficient Learning of Robust Control Policies. - Susmit Jha; Patrick Lincoln (Allerton, 2018)

Model, Data and Reward Repair: Trusted Machine Learning for Markov Decision Processes. - Shalini Ghosh; Susmit Jha; Ashish Tiwari 001; Patrick Lincoln; Xiaojin Zhu 001 (DSN Workshops, 2018)

Duality-Based Nested Controller Synthesis from STL Specifications for Stochastic Linear Systems. - Susmit Jha; Sunny Raj; Sumit Kumar Jha 001; Natarajan Shankar (FORMATS, 2018)

Will Distributed Computing Revolutionize Peace? The Emergence of Battlefield IoT. - Tarek F. Abdelzaher; Nora Ayanian; Tamer Basar; Suhas N. Diggavi; Jana Diesner; Deepak Ganesan; Ramesh Govindan; Susmit Jha; Tancrède Lepoint; Benjamin M. Marlin; Klara Nahrstedt; David M. Nicol; et al. (ICDCS, 2018)

Detecting Adversarial Examples Using Data Manifolds. - Susmit Jha; Uyeong Jang; Somesh Jha; Brian Jalaian (MILCOM, 2018)

Output Range Analysis for Deep Feedforward Neural Networks. - Souradeep Dutta; Susmit Jha; Sriram Sankaranarayanan 001; Ashish Tiwari 001 (NFM, 2018)

Learning Task Specifications from Demonstrations. - Marcell Vazquez-Chanlatte; Susmit Jha; Ashish Tiwari 001; Mark K. Ho; Sanjit A. Seshia (NeurIPS, 2018)

Toward an Internet of Battlefield Things: A Resilience Perspective. - Tarek F. Abdelzaher; Nora Ayanian; Tamer Basar; Suhas N. Diggavi; Jana Diesner; Deepak Ganesan; Ramesh Govindan; Susmit Jha; Tancrède Lepoint; Benjamin M. Marlin; Klara Nahrstedt; David M. Nicol; et al. (Computer, 2018)

Trusted Neural Networks for Safety-Constrained Autonomous Control. - Shalini Ghosh; Amaury Mercier; Dheeraj Pichapati; Susmit Jha; Vinod Yegneswaran; Patrick Lincoln (CoRR, 2018)

Safe Autonomy Under Perception Uncertainty Using Chance-Constrained Temporal Logic. - Susmit Jha; Vasumathi Raman; Dorsa Sadigh; Sanjit A. Seshia (J. Autom. Reason., 2018)

Inferring and Conveying Intentionality: Beyond Numerical Rewards to Logical Intentions. - Susmit Jha; John Rushby (AAAI Spring Symposium: Towards Conscious AI Systems, 2019)

A Risk-Sensitive Finite-Time Reachability Approach for Safety of Stochastic Dynamic Systems. - Margaret P. Chapman; Jonathan Lacotte; Aviv Tamar; Donggun Lee; Kevin M. Smith; Victoria Cheng; Jaime F. Fisac; Susmit Jha; Marco Pavone 001; Claire J. Tomlin (ACC, 2019)

Trust, Resilience and Interpretability of AI Models. - Susmit Jha (NSV@CAV, 2019)

Sherlock - A tool for verification of neural network feedback systems: demo abstract. - Souradeep Dutta; Xin Chen 002; Susmit Jha; Sriram Sankaranarayanan 001; Ashish Tiwari 001 (HSCC, 2019)

Attribution-Based Confidence Metric For Deep Neural Networks. - Susmit Jha; Sunny Raj; Steven Lawrence Fernandes; Sumit Kumar Jha 001; Somesh Jha; Brian Jalaian; Gunjan Verma; Ananthram Swami (NeurIPS, 2019)

Attribution-driven Causal Analysis for Detection of Adversarial Examples. - Susmit Jha; Sunny Raj; Steven Lawrence Fernandes; Sumit Kumar Jha 001; Somesh Jha; Gunjan Verma; Brian Jalaian; Ananthram Swami (CoRR, 2019)

TrojDRL: Trojan Attacks on Deep Reinforcement Learning Agents. - Panagiota Kiourti; Kacper Wardega; Susmit Jha; Wenchao Li 001 (CoRR, 2019)

On Need for Topology Awareness of Generative Models. - Uyeong Jang; Susmit Jha; Somesh Jha (CoRR, 2019)

TeLEx: learning signal temporal logic from positive examples using tightness metric. - Susmit Jha; Ashish Tiwari 001; Sanjit A. Seshia; Tuhin Sahai; Natarajan Shankar (Formal Methods Syst. Des., 2019)

Explaining AI Decisions Using Efficient Methods for Learning Sparse Boolean Formulae. - Susmit Jha; Tuhin Sahai; Vasumathi Raman; Alessandro Pinto; Michael Francis (J. Autom. Reason., 2019)

Estimating the Density of States of Boolean Satisfiability Problems on Classical and Quantum Computing Platforms. - Tuhin Sahai; Anurag Mishra; Jose Miguel Pasini; Susmit Jha (AAAI, 2020)

Learning Certified Control Using Contraction Metric. - Dawei Sun; Susmit Jha; Chuchu Fan (CoRL, 2020)

TrojDRL: Evaluation of Backdoor Attacks on Deep Reinforcement Learning. - Panagiota Kiourti; Kacper Wardega; Susmit Jha; Wenchao Li 001 (DAC, 2020)

On the Need for Topology-Aware Generative Models for Manifold-Based Defenses. - Uyeong Jang; Susmit Jha; Somesh Jha (ICLR, 2020)

Model-Centered Assurance for Autonomous Systems. - Susmit Jha; John Rushby; Natarajan Shankar (SAFECOMP, 2020)

An Extension of Fano's Inequality for Characterizing Model Susceptibility to Membership Inference Attacks. - Sumit Kumar Jha 001; Susmit Jha; Rickard Ewetz; Sunny Raj; Alvaro Velasquez; Laura L. Pullum; Ananthram Swami (CoRR, 2020)

MISA: Online Defense of Trojaned Models using Misattributions. - Panagiota Kiourti; Wenchao Li 001; Anirban Roy; Karan Sikka; Susmit Jha (ACSAC, 2021)

On Detection of Out of Distribution Inputs in Deep Neural Networks. - Susmit Jha; Anirban Roy (CogMI, 2021)

On Smoother Attributions using Neural Stochastic Differential Equations. - Sumit Kumar Jha 001; Rickard Ewetz; Alvaro Velasquez; Susmit Jha (IJCAI, 2021)

Automated Synthesis of Quantum Circuits Using Symbolic Abstractions and Decision Procedures. - Alvaro Velasquez; Sumit Kumar Jha 001; Rickard Ewetz; Susmit Jha (ISCAS, 2021)

Are all outliers alike? On Understanding the Diversity of Outliers for Detecting OODs. - Ramneet Kaur; Susmit Jha; Anirban Roy; Oleg Sokolsky; Insup Lee 001 (CoRR, 2021)

Online Defense of Trojaned Models using Misattributions. - Panagiota Kiourti; Wenchao Li 001; Anirban Roy; Karan Sikka; Susmit Jha (CoRR, 2021)

Detecting OODs as datapoints with High Uncertainty. - Ramneet Kaur; Susmit Jha; Anirban Roy; Sangdon Park 001; Oleg Sokolsky; Insup Lee 001 (CoRR, 2021)

Protein Folding Neural Networks Are Not Robust. - Sumit Kumar Jha 001; Arvind Ramanathan; Rickard Ewetz; Alvaro Velasquez; Susmit Jha (CoRR, 2021)

Introduction to the Special Issue on Artificial Intelligence and Cyber-Physical Systems: Part 1. - Jingtong Hu; Qi Zhu 002; Susmit Jha (ACM Trans. Cyber Phys. Syst., 2021)

Shaping Noise for Robust Attributions in Neural Stochastic Differential Equations. - Sumit Kumar Jha 001; Rickard Ewetz; Alvaro Velasquez; Arvind Ramanathan; Susmit Jha (AAAI, 2022)

iDECODe: In-Distribution Equivariance for Conformal Out-of-Distribution Detection. - Ramneet Kaur; Susmit Jha; Anirban Roy; Sangdon Park 001; Edgar Dobriban; Oleg Sokolsky; Insup Lee 001 (AAAI, 2022)

Dual-Key Multimodal Backdoors for Visual Question Answering. - Matthew Walmer; Karan Sikka; Indranil Sur; Abhinav Shrivastava; Susmit Jha (CVPR, 2022)

Trigger Hunting with a Topological Prior for Trojan Detection. - Xiaoling Hu 002; Xiao Lin; Michael Cogswell; Yi Yao; Susmit Jha; Chao Chen 012 (ICLR, 2022)

Principal Component Flows. - Edmond Cunningham; Adam D. Cobb; Susmit Jha (ICML, 2022)

ExplainIt!: A Tool for Computing Robust Attributions of DNNs. - Sumit Kumar Jha 001; Alvaro Velasquez; Rickard Ewetz; Laura Pullum; Susmit Jha (IJCAI, 2022)

Detecting Out-Of-Context Objects Using Graph Contextual Reasoning Network. - Manoj Acharya; Anirban Roy; Kaushik Koneripalli; Susmit Jha; Christopher Kanan; Ajay Divakaran (IJCAI, 2022)

Context-aware Collaborative Neuro-Symbolic Inference in IoBTs. - Tarek F. Abdelzaher; Nathaniel D. Bastian; Susmit Jha; Lance M. Kaplan; Mani B. Srivastava; Venugopal V. Veeravalli (MILCOM, 2022)

Detecting out-of-context objects using contextual cues. - Manoj Acharya; Anirban Roy; Kaushik Koneripalli; Susmit Jha; Christopher Kanan; Ajay Divakaran (CoRR, 2022)

Principal Manifold Flows. - Edmond Cunningham; Adam D. Cobb; Susmit Jha (CoRR, 2022)

Multiple Testing Framework for Out-of-Distribution Detection. - Akshayaa Magesh; Venugopal V. Veeravalli; Anirban Roy; Susmit Jha (CoRR, 2022)

CODiT: Conformal Out-of-Distribution Detection in Time-Series Data. - Ramneet Kaur; Kaustubh Sridhar; Sangdon Park 001; Susmit Jha; Anirban Roy; Oleg Sokolsky; Insup Lee 001 (CoRR, 2022)

Design of Unmanned Air Vehicles Using Transformer Surrogate Models. - Adam D. Cobb; Anirban Roy; Daniel Elenius; Susmit Jha (CoRR, 2022)

Introduction to the Special Issue on Artificial Intelligence and Cyber-Physical Systems - Part 2. - Jingtong Hu; Qi Zhu 002; Susmit Jha (ACM Trans. Cyber Phys. Syst., 2022)

Lightning Talk: Trinity - Assured Neuro-symbolic Model Inspired by Hierarchical Predictive Coding. - Susmit Jha (DAC, 2023)

Dehallucinating Large Language Models Using Formal Methods Guided Iterative Prompting. - Susmit Jha; Sumit Kumar Jha 001; Patrick Lincoln; Nathaniel D. Bastian; Alvaro Velasquez; Sandeep Neema (ICAA, 2023)

Predicting Out-of-Distribution Performance of Deep Neural Networks Using Model Conformance. - Ramneet Kaur; Susmit Jha; Anirban Roy; Oleg Sokolsky; Insup Lee 001 (ICAA, 2023)

Detecting Trojaned DNNs Using Counterfactual Attributions. - Karan Sikka; Indranil Sur; Anirban Roy; Ajay Divakaran; Susmit Jha (ICAA, 2023)

CODiT: Conformal Out-of-Distribution Detection in Time-Series Data for Cyber-Physical Systems. - Ramneet Kaur; Kaustubh Sridhar; Sangdon Park 001; Yahan Yang; Susmit Jha; Anirban Roy; Oleg Sokolsky; Insup Lee 001 (ICCPS, 2023)

TIJO: Trigger Inversion with Joint Optimization for Defending Multimodal Backdoored Models. - Indranil Sur; Karan Sikka; Matthew Walmer; Kaushik Koneripalli; Anirban Roy; Xiao Lin; Ajay Divakaran; Susmit Jha (ICCV, 2023)

Principled OOD Detection via Multiple Testing. - Akshayaa Magesh; Venugopal V. Veeravalli; Anirban Roy; Susmit Jha (ISIT, 2023)

Neural SDEs for Robust and Explainable Analysis of Electromagnetic Unintended Radiated Emissions. - Sumit Kumar Jha 001; Susmit Jha; Rickard Ewetz; Alvaro Velasquez (MILCOM, 2023)

Counterexample Guided Inductive Synthesis Using Large Language Models and Satisfiability Solving. - Sumit Kumar Jha 001; Susmit Jha; Patrick Lincoln; Nathaniel D. Bastian; Alvaro Velasquez; Rickard Ewetz; Sandeep Neema (MILCOM, 2023)

Challenges and Opportunities in Neuro-Symbolic Composition of Foundation Models. - Susmit Jha; Anirban Roy; Adam D. Cobb; Alexander M. Berenbeim; Nathaniel D. Bastian (MILCOM, 2023)

AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs. - Adam D. Cobb; Anirban Roy; Daniel Elenius; F. Michael Heim; Brian Swenson; Sydney Whittington; James D. Walker; Theodore Bapty; Joseph Hite; Karthik Ramani; Christopher McComb; Susmit Jha (NeurIPS, 2023)

On the Robustness of AlphaFold: A COVID-19 Case Study. - Ismail Alkhouri; Sumit Kumar Jha 001; Andre Beckus; George K. Atia; Alvaro Velasquez; Rickard Ewetz; Arvind Ramanathan; Susmit Jha (CoRR, 2023)

Measuring Classification Decision Certainty and Doubt. - Alexander M. Berenbeim; Iain J. Cruickshank; Susmit Jha; Robert H. Thomson 001; Nathaniel D. Bastian (CoRR, 2023)

Neural Stochastic Differential Equations for Robust and Explainable Analysis of Electromagnetic Unintended Radiated Emissions. - Sumit Kumar Jha 001; Susmit Jha; Rickard Ewetz; Alvaro Velasquez (CoRR, 2023)

Neuro Symbolic Reasoning for Planning: Counterexample Guided Inductive Synthesis using Large Language Models and Satisfiability Solving. - Sumit Kumar Jha 001; Susmit Jha; Patrick Lincoln; Nathaniel D. Bastian; Alvaro Velasquez; Rickard Ewetz; Sandeep Neema (CoRR, 2023)

math-PVS: A Large Language Model Framework to Map Scientific Publications to PVS Theories. - Hassen Saïdi; Susmit Jha; Tuhin Sahai (CoRR, 2023)

Principled Out-of-Distribution Detection via Multiple Testing. - Akshayaa Magesh; Venugopal V. Veeravalli; Anirban Roy; Susmit Jha (J. Mach. Learn. Res., 2023)

Direct Amortized Likelihood Ratio Estimation. - Adam D. Cobb; Brian Matejek; Daniel Elenius; Anirban Roy; Susmit Jha (AAAI, 2024)

On the Design of Novel Attention Mechanism for Enhanced Efficiency of Transformers. - Sumit Kumar Jha 001; Susmit Jha; Rickard Ewetz; Alvaro Velasquez (DAC, 2024)

Solving Mystery Planning Problems Using Category Theory, Functors, and Large Language Models. - Sumit Kumar Jha 001; Susmit Jha; Rickard Ewetz; Alvaro Velasquez (ICAA, 2024)

Shrinking POMCP: A Framework for Real-Time UAV Search and Rescue. - Yunuo Zhang; Baiting Luo; Ayan Mukhopadhyay; Dániel Stojcsics; Daniel Elenius; Anirban Roy; Susmit Jha; Miklos Maroti; Xenofon D. Koutsoukos; Gabor Karsai; Abhishek Dubey (ICAA, 2024)

Neuro-symbolic Generative AI Assistant for System Design. - Susmit Jha; Sumit Kumar Jha 001; Alvaro Velasquez (MEMOCODE, 2024)

Co-Synthesis of Code and Formal Models Using Large Language Models and Functors. - Sumit Kumar Jha 001; Susmit Jha; Rickard Ewetz; Alvaro Velasquez (MILCOM, 2024)

Post-hoc Uncertainty Quantification for Neurosymbolic Artificial Intelligence. - Alexander M. Berenbeim; Ramneet Kaur; Adam D. Cobb; Anirban Roy; Susmit Jha; Nathaniel D. Bastian (MILCOM, 2024)

Task-Agnostic Detector for Insertion-Based Backdoor Attacks. - Weimin Lyu; Xiao Lin; Songzhu Zheng; Lu Pang 006; Haibin Ling; Susmit Jha; Chao Chen 012 (NAACL-HLT (Findings), 2024)

Concept-Based Analysis of Neural Networks via Vision-Language Models. - Ravi Mangal; Nina Narodytska; Divya Gopinath; Boyue Caroline Hu; Anirban Roy; Susmit Jha; Corina S. Pasareanu (SAIV, 2024)

Second-Order Forward-Mode Automatic Differentiation for Optimization. - Adam D. Cobb; Atilim Günes Baydin; Barak A. Pearlmutter; Susmit Jha (CoRR, 2024)

Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI. - Ramneet Kaur; Colin Samplawski; Adam D. Cobb; Anirban Roy; Brian Matejek; Manoj Acharya; Daniel Elenius; Alexander M. Berenbeim; John A. Pavlik; Nathaniel D. Bastian; Susmit Jha (CoRR, 2024)

Exploring the Predictive Capabilities of AlphaFold Using Adversarial Protein Sequences. - Ismail R. Alkhouri; Sumit Kumar Jha 001; Andre Beckus; George K. Atia; Susmit Jha; Rickard Ewetz; Alvaro Velasquez (IEEE Trans. Artif. Intell., 2024)

Debugging and Runtime Analysis of Neural Networks with VLMs (A Case Study). - Boyue Caroline Hu; Divya Gopinath; Corina S. Pasareanu; Nina Narodytska; Ravi Mangal; Susmit Jha (CAIN, 2025)

Safety Monitoring for Learning-Enabled Cyber-Physical Systems in Out-of-Distribution Scenarios. - Vivian Lin; Ramneet Kaur; Yahan Yang; Souradeep Dutta; Yiannis Kantaros; Anirban Roy; Susmit Jha; Oleg Sokolsky; Insup Lee 001 (ICCPS, 2025)

Calibration and Correctness of Language Models for Code. - Claudio Spiess; David Gros 001; Kunal Suresh Pai; Michael Pradel; Md. Rafiqul Islam Rabin; Amin Alipour; Susmit Jha; Prem Devanbu; Toufique Ahmed (ICSE, 2025)

Taylor-Model Physics-Informed Neural Networks (PINNs) for Ordinary Differential Equations. - Chandra Kanth Nagesh; Sriram Sankaranarayanan 001; Ramneet Kaur; Tuhin Sahai; Susmit Jha (NeuS, 2025)

Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference. - Colin Samplawski; Adam D. Cobb; Manoj Acharya; Ramneet Kaur; Susmit Jha (UAI, 2025)

Zero-Shot Detection of Out-of-Context Objects Using Foundation Models. - Anirban Roy; Adam D. Cobb; Ramneet Kaur; Sumit Jha 001; Nathaniel D. Bastian; Alexander M. Berenbeim; Robert H. Thomson 001; Iain Cruickshank; Alvaro Velasquez; Susmit Jha (WACV, 2025)

SAFE-NID: Self-Attention with Normalizing-Flow Encodings for Network Intrusion Detection. - Brian Matejek; Ashish Gehani; Nathaniel D. Bastian; Daniel J. Clouse; Bradford J. Kline; Susmit Jha (Trans. Mach. Learn. Res., 2025)

TeleLoRA: Teleporting Model-Specific Alignment Across LLMs. - Xiao Lin; Manoj Acharya; Anirban Roy; Susmit Jha (CoRR, 2025)

AGENT: An Aerial Vehicle Generation and Design Tool Using Large Language Models. - Colin Samplawski; Adam D. Cobb; Susmit Jha (CoRR, 2025)

Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding. - Trilok Padhi; Ramneet Kaur; Adam D. Cobb; Manoj Acharya; Anirban Roy; Colin Samplawski; Brian Matejek; Alexander M. Berenbeim; Nathaniel D. Bastian; Susmit Jha (CoRR, 2025)

On the Evaluation of Engineering Artificial General Intelligence. - Sandeep Neema; Susmit Jha; Adam Nagel; Ethan Lew; Chandrasekar Sureshkumar; Aleksa Gordic; Chase Shimmin; Hieu Nguygen; Paul Eremenko (CoRR, 2025)

Backpropagation-Free Metropolis-Adjusted Langevin Algorithm. - Adam D. Cobb; Susmit Jha (CoRR, 2025)

TOGA: Temporally Grounded Open-Ended Video QA with Weak Supervision. - Ayush Gupta; Anirban Roy; Rama Chellappa; Nathaniel D. Bastian; Alvaro Velasquez; Susmit Jha (CoRR, 2025)