@article{vazirizade_azizsoltani_haldar_2022, title={Reliability estimation of jacket type offshore platforms against seismic and wave loadings applied in time domain}, volume={17}, ISSN={["1754-212X"]}, DOI={10.1080/17445302.2020.1827632}, abstractNote={ABSTRACT A novel approach is proposed for the reliability estimation of jacket-type offshore platforms excited by dynamic loadings (wave and seismic) applied in time domain. The information on risk is extracted with the help of multiple finite element-based deterministic analyses. This feature is expected to be attractive to practitioners for routine applications without advanced expertise in the risk-based design concept. It will also be of interest to researchers since the proposed concept innovatively integrates several advanced mathematical concepts, including the extensively modified response surface method, advanced factorial design schemes, Kriging, and other techniques producing compounding beneficial effects. For verification, an operating platform is excited by multiple time histories of wave and seismic loadings generated using current design guidelines. The probabilities of failure of the platform are estimated for both the strength and serviceability performance functions using about 200 deterministic analyses. The results are successfully verified using 10,000 Monte Carlo simulations.}, number={1}, journal={SHIPS AND OFFSHORE STRUCTURES}, author={Vazirizade, Sayyed Mohsen and Azizsoltani, Hamoon and Haldar, Achintya}, year={2022}, month={Jan}, pages={143–152} }
 @article{ausin_azizsoltani_ju_kim_chi_2021, title={InferNet for Delayed Reinforcement Tasks: Addressing the Temporal Credit Assignment Problem}, ISSN={["2639-1589"]}, DOI={10.1109/BigData52589.2021.9671827}, abstractNote={Rewards are the critical signals for Reinforcement Learning (RL) algorithms to learn the desired behavior in a sequential multi-step learning task. However, when these rewards are delayed and noisy in nature, the learning process becomes more challenging. The temporal Credit Assignment Problem (CAP) is a well-known and challenging task in AI. While RL, especially Deep RL, often works well with immediate rewards but may fail when rewards are delayed or noisy, or both. In this work, we propose delegating the CAP to a Neural Network-based algorithm named InferNet that explicitly learns to infer the immediate rewards from the delayed and noisy rewards. The effectiveness of InferNet was evaluated on three online RL tasks: a GridWorld, a CartPole, and 40 Atari games; and two offline RL tasks: GridWorld and a real-life Sepsis treatment task. The effectiveness of InferNet rewards is compared to that of immediate and delayed rewards in two settings: with and without noise. For the offline RL tasks, it is also compared to a strong baseline, InferGP [7]. Overall, our results show that InferNet is robust to delayed or noisy reward functions, and it could be used effectively for solving the temporal CAP in a wide range of RL tasks, when immediate rewards are not available or they are noisy.}, journal={2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA)}, author={Ausin, Markel Sanz and Azizsoltani, Hamoon and Ju, Song and Kim, Yeo Jin and Chi, Min}, year={2021}, pages={1337–1348} }
 @article{zhou_azizsoltani_ausin_barnes_chi_2021, title={Leveraging Granularity: Hierarchical Reinforcement Learning for Pedagogical Policy Induction}, volume={8}, ISSN={["1560-4306"]}, DOI={10.1007/s40593-021-00269-9}, journal={INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION}, author={Zhou, Guojing and Azizsoltani, Hamoon and Ausin, Markel Sanz and Barnes, Tiffany and Chi, Min}, year={2021}, month={Aug} }
 @article{haldar_gaxiola-camacho_azizsoltani_villegas-mercado_vazirizade_2020, title={Novel Geomechanics Concepts for Earthquake Excitations Applied in Time Domain}, volume={20}, ISSN={["1943-5622"]}, DOI={10.1061/(ASCE)GM.1943-5622.0001799}, abstractNote={Abstract Novel geomechanics concepts for seismic design satisfying the current performance-based seismic design (PBSD) requirements are presented. Issues related to soil conditions are explicitly a...}, number={9}, journal={INTERNATIONAL JOURNAL OF GEOMECHANICS}, author={Haldar, Achintya and Gaxiola-Camacho, J. Ramon and Azizsoltani, Hamoon and Villegas-Mercado, Francisco J. and Vazirizade, Sayyed Mohsen}, year={2020}, month={Sep} }
 @article{azizsoltani_ramon gaxiola-camacho_villegas-mercado_haldar_2019, title={Discussion of "State-of-the-Art Review on Seismic Design of Steel Structures" by Chia-Ming Uang and Michel Bruneau}, volume={145}, ISSN={["1943-541X"]}, DOI={10.1061/(ASCE)ST.1943-541X.0002312}, number={5}, journal={JOURNAL OF STRUCTURAL ENGINEERING}, author={Azizsoltani, Hamoon and Ramon Gaxiola-Camacho, J. and Villegas-Mercado, Francisco J. and Haldar, Achintya}, year={2019}, month={May} }
 @article{zhou_azizsoltani_ausin_barnes_chi_2019, title={Hierarchical Reinforcement Learning for Pedagogical Policy Induction}, volume={11625}, ISBN={["978-3-030-23203-0"]}, ISSN={["1611-3349"]}, DOI={10.1007/978-3-030-23204-7_45}, abstractNote={In interactive e-learning environments such as Intelligent Tutoring Systems, there are pedagogical decisions to make at two main levels of granularity: whole problems and single steps. Recent years have seen growing interest in data-driven techniques for such pedagogical decision making, which can dynamically tailor students’ learning experiences. Most existing data-driven approaches, however, treat these pedagogical decisions equally, or independently, disregarding the long-term impact that tutor decisions may have across these two levels of granularity. In this paper, we propose and apply an offline, off-policy Gaussian Processes based Hierarchical Reinforcement Learning (HRL) framework to induce a hierarchical pedagogical policy that makes decisions at both problem and step levels. In an empirical classroom study with 180 students, our results show that the HRL policy is significantly more effective than a Deep Q-Network (DQN) induced policy and a random yet reasonable baseline policy.}, journal={ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2019), PT I}, author={Zhou, Guojing and Azizsoltani, Hamoon and Ausin, Markel Sanz and Barnes, Tiffany and Chi, Min}, year={2019}, pages={544–556} }
 @article{azizsoltani_sadeghi_2018, title={Adaptive sequential strategy for risk estimation of engineering systems using Gaussian process regression active learning}, volume={74}, ISSN={["1873-6769"]}, DOI={10.1016/j.engappai.2018.06.007}, abstractNote={Maximizing the accuracy of the estimated risk, and minimizing the number of calls to the expensive-to-evaluate deterministic model are two major challenges engineers face. Monte Carlo method is the usual method of choice for risk estimation. Since each deterministic run for a complex engineering system may require a significant amount of time, Monte Carlo method may be very time-consuming and impractical. To reduce the computational expense of Monte Carlo method, surrogate models are presented. In this paper, an adaptive sequential strategy based on the Monte Carlo method and Gaussian process regression active learning for risk estimation of engineering systems with minimum computational cost and acceptable accuracy is presented. The proposed adaptive sequential strategy to build designs of experiments is illustrated using a simple One-dimensional explanatory example. Then, the efficiency and accuracy of the presented method are compared with the other available methodologies using several benchmark examples from literature. Finally, the applicability of the presented method for nonlinear and high-dimensional real-world problems are studied.}, journal={ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE}, author={Azizsoltani, Hamoon and Sadeghi, Elham}, year={2018}, month={Sep}, pages={146–165} }
 @article{azizsoltani_haldar_2018, title={Reliability Analysis of Lead-Free Solders in Electronic Packaging Using a Novel Surrogate Model and Kriging Concept}, volume={140}, ISSN={["1528-9044"]}, DOI={10.1115/1.4040924}, abstractNote={A novel reliability evaluation procedure of lead-free solders used in electronic packaging (EP) subjected to thermomechanical loading is proposed. A solder ball is represented by finite elements (FEs). Major sources of nonlinearities are incorporated as realistically as practicable. Uncertainties in all design variables are quantified using available information. The thermomechanical loading is represented by five design parameters and uncertainties associated with them are incorporated. Since the performance or limit state function (LSF) of such complicated problem is implicit in nature, it is approximately generated explicitly in the failure region with the help of a completely improved response surface method (RSM)-based approach and the universal Kriging method (KM). The response surface (RS) is generated by conducting as few deterministic nonlinear finite element analyses as possible by integrating several advanced factorial mathematical concepts producing compounding beneficial effect. The accuracy, efficiency, and application potential of the procedure are established with the help of Monte Carlo simulation (MCS) and the results from laboratory investigation reported in the literature. The study conclusively verified the proposed method. Similar studies can be conducted to fill the knowledge gap for cases where the available analytical and experimental studies are limited or extend the information to cases where reliability information is unavailable. The study showcased how reliability information can be extracted with the help of multiple deterministic analyses. The authors believe that they proposed an alternative to the classical MCS technique.}, number={4}, journal={JOURNAL OF ELECTRONIC PACKAGING}, author={Azizsoltani, Hamoon and Haldar, Achintya}, year={2018}, month={Dec} }
 @article{azizsoltani_ramon gaxiola-camacho_haldar_2018, title={Site-specific seismic design of damage tolerant structural systems using a novel concept}, volume={16}, ISSN={["1573-1456"]}, DOI={10.1007/s10518-018-0329-5}, number={9}, journal={BULLETIN OF EARTHQUAKE ENGINEERING}, author={Azizsoltani, Hamoon and Ramon Gaxiola-Camacho, J. and Haldar, Achintya}, year={2018}, month={Sep}, pages={3819–3843} }
 @misc{uang_bruneau_2018, title={State-of-the-Art Review on Seismic Design of Steel Structures}, volume={144}, ISSN={["1943-541X"]}, DOI={10.1061/(ASCE)ST.1943-541X.0001973}, abstractNote={AbstractThis state-of-the-art review provides an overview of the evolution of seismic design requirements for main steel building seismic force–resisting systems, as driven by new developments, the...}, number={4}, journal={JOURNAL OF STRUCTURAL ENGINEERING}, author={Uang, Chia-Ming and Bruneau, Michel}, year={2018}, month={Apr} }