Arindam Paul

American Family Insurance

Materials design aims to identify the material features that provide optimal properties for various engineering applications, such as aerospace, automotive, and naval. One of the important but challenging problems for materials design is to discover multiple polycrystalline microstructures with optimal properties. This paper proposes an end-to-end...

There are two broad modeling paradigms in scientific applications: forward and inverse. While forward modeling estimates the observations based on known causes, inverse modeling attempts to infer the causes given the observations. Inverse problems are usually more critical as well as difficult in scientific applications as they seek to explore the...

There have been many efforts in the last decade in the health informatics community to develop systems that can automatically recognize and predict disclosures on social media. However, a majority of such efforts have focused on simple topic prediction or sentiment classification. However, taboo disclosures on social media that people are not comfo...

Organic Photovoltaic (OPV) Solar Cells are a rapidly developing technology with promising capabilities over leading renewable energy sources. Screening methods for determining promising donor and acceptor molecules to augment the efficiencies of such cells can be substantially accelerated through deep learning. Textual de-scriptors, specifically Si...

Microstructural materials design is one of the most important applications of inverse modeling in materials science. Generally speaking, there are two broad modeling paradigms in scientific applications: forward and inverse. While the forward modeling estimates the observations based on known parameters, the inverse modeling attempts to infer the p...

Additive Manufacturing (AM) is a manufacturing paradigm that builds three-dimensional objects from a computer-aided design model by successively adding material layer by layer. AM has become very popular in the past decade due to its utility for fast prototyping such as 3D printing as well as manufacturing functional parts with complex geometries u...

Organic solar cells are an inexpensive, flexible alternative to traditional silicon‐based solar cells but disadvantaged by low power conversion efficiency due to empirical design and complex manufacturing processes. This process can be accelerated by generating a comprehensive set of potential candidates. However, this would require a laborious tri...

Additive Manufacturing (AM) is a manufacturing paradigm that builds three-dimensional objects from a computer-aided design model by successively adding material layer by layer. AM has become very popular in the past decade due to its utility for fast prototyping such as 3D printing as well as manufacturing functional parts with complex geometries u...

Organic solar cells are an inexpensive, flexible alternative to traditional silicon-based solar cells but disadvantaged by low power conversion efficiency due to empirical design and complex manufacturing processes. This process can be accelerated by generating a comprehensive set of potential candidates. However , this would require a laborious tr...

Organic solar cells are an inexpensive, flexible alternative to traditional silicon-based solar cells but disadvantaged by low power conversion efficiency due to empirical design and complex manufacturing processes. This process can be accelerated by generating a comprehensive set of potential candidates. However , this would require a laborious tr...

Organic Solar Cells are a promising technology for solving the clean energy crisis in the world. However, generating candidate chemical compounds for solar cells is a time-consuming process requiring thousands of hours of laboratory analysis. For a solar cell, the most important property is the power conversion efficiency which is dependent on the...

Organic Solar Cells are a promising technology for solving the clean energy crisis in the world. However, generating candidate chemical compounds for solar cells is a time-consuming process requiring thousands of hours of laboratory analysis. For a solar cell, the most important property is the power conversion efficiency which is dependent on the...

Microstructure sensitive design has a critical impact on the performance of engineering materials. The safety and performance requirements of critical components, as well as the cost of material and machining of Titanium components, make dovetailing of the microstructure imperative. This paper addresses the optimization of several microstructure de...

Conventional machine learning approaches for predicting material properties from elemental compositions have emphasized the importance of leveraging domain knowledge when designing model inputs. Here, we demonstrate that by using a deep learning approach, we can bypass such manual feature engineering requiring domain knowledge and achieve much bett...

SMILES is a linear representation of chemical structures which encodes the connection table, and the stereochemistry of a molecule as a line of text with a grammar structure denoting atoms, bonds, rings and chains, and this information can be used to predict chemical properties. Molecular fingerprints are representations of chemical structures, suc...

SMILES is a linear representation of chemical structures which encodes the connection table, and the stereo-chemistry of a molecule as a line of text with a grammar structure denoting atoms, bonds, rings and chains, and this information can be used to predict chemical properties. Molecular fingerprints are representations of chemical structures, su...

Directed Energy Deposition (DED) is a growing additive manufacturing technology due to its superior properties such as build flexibility at multiple scales and limited waste. However, both experimental and physics-based models have limitations in providing accurate and computationally efficient predictions of process outcomes, which is essential fo...

Microstructures significantly impact the performance of sensitively engineered components, such as wireless impact detectors used in military vehicles or sensors used in aircrafts. These components can operate safely only within a certain range of frequencies, and frequencies outside that range can lead to instability because of resonance. This pap...

Recent progress in big data and computer vision with deep learning models has gained a lot of attention. Deep learning has been performed on tasks such as image classification , object detection, image segmentation, image captioning, visual question and answering, using large collections of annotated images. This calls for more curated large image...

There is lot of research activity in the area of opinion mining and sentiment analysis, which deals with the computational treatment of opinion, sentiment, and subjectivity in text. Social media websites have become increasingly popular for discussing uncomfortable topics. However, there are limited resources for mining and automatically labeling p...

People have long sought answers to questions online, typically using either anonymous or pseudonymous forums or social network platforms that primarily use real names. Systems that allow anonymous communication afford freedom to explore identity and discuss taboo topics, but can result in negative disinhibited behavior such as cyberbullying. Identi...

Sybil attack is an important problem as the peer-to-peer networks grow in size and become prominent means for distributing multimedia. In order to validate the feasibility of using psychometric tests as an approach to detect Sybils in their entirety as Sybil groups, an experiment is conducted by taking the tests on a population of considerable size...

Data Cleaning is a very important part of the data warehouse management process. It is not a very easy process as many different types of unclean data (bad data, incomplete data, typos, etc) can be present. Also, whether a data is clean or dirty is highly dependent on the nature and source of the raw data. Many attempts have been made to clean the...

Software measurement is a key factor in managing, controlling, and improving the software development processes. Software quality is one of the most important factors for assessing the global competitive position of any software company. Thus the quantification of quality parameters and integrating them into quality models is very essential. Softwa...

Software quality is the measure of appropriateness of the design of the software and how well it adheres to that design. There are some metrics and measurements to determine the software quality. Software quality measurement is possible only by quantifying the characteristics affecting the software quality. For measuring the quality, the parameters...

Software quality is the measure of appropriateness of the design of the software and how well it adheres to that design. There are some metrics and measurements to determine the software quality. Software quality measurement is possible only by quantifying the characteristics affecting the software quality. For measuring the quality, the parameters...

Peer to peer networks are fast becoming the most popular file sharing media, guaranteeing complete user anonymity to the clients. However, modern P2P networks suffer from Sybil attacks, which forge multiple identities to influence the global decisions in the network. This paper suggests a novel solution to minimize Sybils influence using unique com...