Surendrabikram Thapa

Virginia Tech | VT · Department of Computer Science

Data sharing across disciplines helps to build collaboration, and advance research. With recent development in data-driven models, there is an unprecedented need for data. However, data collected from human research subjects are required to follow proper ethical guidelines. Researchers have an obligation to protect the privacy of research participa...

This paper addresses the problem of recovering the shape morphology of blood volume pulse (BVP) information from a video of a person’s face. Video-based remote plethysmography methods have shown promising results in estimating vital signs such as heart rate and breathing rate. However, recovering the instantaneous pulse rate signals is still a chal...

This paper considers methods for extracting blood volume pulse (BVP) representations from video of the human face. Whereas most previous systems have been concerned with estimating vital signs such as average heart rate, this paper addresses the more difficult problem of recovering BVP signal morphology. We present a new approach that is inspired b...

Large Language Models (LLMs) such as ChatGPT and Bard have emerged as groundbreaking interactive chatbots, capturing significant attention and transforming the biomedical research landscape. These powerful tools offer immense potential for advancing scientific inquiry, but they also present challenges and pitfalls. Leveraging large language models,...

Human factors research in transportation relies on naturalistic driving studies (NDS) which collect real-world data from drivers on actual roads. NDS data offer valuable insights into driving behavior, styles, habits, and safety-critical events. However, these data often contain personally identifiable information (PII), such as driver face videos,...

In the ever-evolving landscape of online discourse and political dialogue, the rise of hate speech poses a significant challenge to maintaining a respectful and inclusive digital environment. The context becomes particularly complex when considering the Hindi language—a low-resource language with limited available data. To address this pressing con...

The discourse surrounding climate change on social media platforms has emerged as a significant avenue for understanding public sentiments, perspectives, and engagement with this critical global issue. The unavailability of publicly available datasets, coupled with ignoring the multi-aspect analysis of climate discourse on social media platforms, h...

BACKGROUND Medical image analysis, particularly in the context of Visual Question Answering (VQA) and image captioning, is crucial for accurate diagnosis and educational purposes. OBJECTIVE Our study introduces BioMedBLIP models, fine-tuned for VQA tasks using specialized medical datasets like ROCO and MIMIC-CXR, and evaluates their performance in...

Background Medical image analysis, particularly in the context of visual question answering (VQA) and image captioning, is crucial for accurate diagnosis and educational purposes. Objective Our study aims to introduce BioMedBLIP models, fine-tuned for VQA tasks using specialized medical data sets such as Radiology Objects in Context and Medical In...

This paper explores the dual role of Large Language Models (LLMs) in the context of online misinformation and disinformation. In today’s digital landscape, where the internet and social media facilitate the rapid dissemination of information, discerning between accurate content and falsified information presents a formidable challenge. Misinformati...

Social media users often use disease or symptom terms in ways other than describing their health conditions, which can lead to flawed conclusions in data-driven public health surveillance. The health mention classification (HMC) task aims to identify posts in which users use disease or symptom terms to discuss their health conditions instead of usi...

The growing need to identify mental health conditions has paved the way for automated computational methods for mental health surveillance on social media. However, inferring the accurate state of a user’s mind requires understanding the history of the user’s mental health condition, which is critical for identifying the mental health landscape of...

Natural language processing has advanced with AI-driven language models (LMs), that are applied widely from text generation to question answering. These models are pre-trained on a wide spectrum of data sources, enhancing accuracy and responsiveness. However, this process inadvertently entails the absorption of a diverse spectrum of viewpoints inhe...

The use of social media during election campaigns has become increasingly popular. However, the unbridled nature of online discourse can lead to the propagation of hate speech, which has far-reaching implications for the democratic process. Natural Language Processing (NLP) techniques are being used to counteract the spread of hate speech and promo...

We provide a summary of the sixth edition of the CASE workshop that is held in the scope of RANLP 2023. The workshop consists of regular papers, three keynotes, working papers of shared task participants, and shared task overview papers. This workshop series has been bringing together all aspects of event information collection across technical and...

Artificial Intelligence (AI) has lately disrupted everything. From applications in day-to-day activities to applications in astronomy and quantum physics, AI has changed everything. Today, almost every sector uses AI in one form or another. Referred to as the fourth industrial revolution, AI has the potential to change the world. The world is conne...

Graph-based techniques have gained traction for representing and analyzing data in various natural language processing (NLP) tasks. Knowledge graph-based language representation models have shown promising results in leveraging domain-specific knowledge for NLP tasks, particularly in the biomedical NLP field. However, such models have limitations,...

Large Language Models (LLMs) such as ChatGPT and Bard have emerged as groundbreaking interactive chatbots, capturing significant attention and transforming the biomedical research landscape. These powerful tools offer immense potential for advancing scientific inquiry, but they also present challenges and pitfalls. Leveraging large language models,...

This paper addresses the problem of sharing drivers' face videos for transportation research while adhering to proper ethical guidelines. The paper first gives an overview of the multitude of problems associated with sharing such data and then proposes a framework on how artificial intelligence-based techniques, specifically face swapping, can be u...

The detection of hate speech in political discourse is a critical issue, and this becomes even more challenging in low-resource languages. To address this issue, we introduce a new dataset named IEHate, which contains 11,457 manually annotated Hindi tweets related to the Indian Assembly Election Campaign from November 1, 2021, to March 9, 2022. We...

Text-embedded images are frequently used on social media to convey opinions and emotions, but they can also be a medium for disseminating hate speech, propaganda, and extremist ideologies. During the Russia-Ukraine war, both sides used text-embedded images extensively to spread propaganda and hate speech. To aid in moderating such content, this pap...

Due to the increasing interest of people in the stock and financial market, the sentiment analysis of news and texts related to the sector is of utmost importance. This helps the potential investors in deciding what company to invest in and what are their long-term benefits. However, it is challenging to analyze the sentiments of texts related to t...

Artificial Intelligence (AI) has lately disrupted everything: from applications in day-to-day activities to applications in astronomy and quantum physics. Today, almost every sector uses AI in one form or another. Referred to as the fourth industrial revolution, AI has the potential to change the world. The world is connected with the internet and...

In today’s social media-dominated landscape, digital platforms wield substantial influence over public opinion, particularly during crucial political events such as electoral processes. These platforms become hubs for diverse discussions, encompassing topics, reforms, and desired changes. Notably, in times of government dissatisfaction, they serve...

In the current world of competition and constant struggle, taking care of mental well-being is of the upmost importance. With hundreds of millions of people suffering from mental disorders like depression, Alzheimer disease, schizophrenia, etc. each year, intelligent systems are needed that can diagnose, track, and manage the mental well-being of i...

This paper presents a new multi-modal dataset for identifying hateful content on social media, consisting of 5,680 text-image pairs collected from Twitter, labeled across two labels. Experimental analysis of the presented dataset has shown that understanding both modalities is essential for detecting these techniques. It is confirmed in our experim...

Alzheimer's disease (AD) is considered as progressing brain disease, which can be slowed down with the early detection and proper treatment by identifying the early symptoms. Language change serves as an early sign that a patient's cognitive functions have been impacted, potentially leading to early detection. The effects of language changes are be...

With the rapid advancement in the fields of computation and deep learning, the use cases of artificial intelligence in healthcare are blooming more than any time in history. In past years, it was supposed that only doctors and medical practitioners should handle the decisions in healthcare systems. With the rise of machine learning, the tables have...

Alzheimer’s Disease (AD) is one of the most common forms of neuropsychological disorder in elderly people. It is a slow progressive disease affecting the brain cells. This affects the cognitive abilities of people and their daily activities. During the course of the disease, memory gets brutally affected too. Working as well as long-term declarativ...

The internet has become a common platform for everyone to share their ideas and opinions. The user has freedom to post whatever he/she likes in social networking and blogging sites. However, sometimes the content when directed towards certain group of individuals with an intention to incite hate or discrimination, causes a turmoil in the society. S...

In the present era of modernization, automation and intelligent systems have become an integral part of our lives. These intelligent systems extremely rely on parallel computing technology for computation. Field Programmable Gate Arrays (FPGAs) have recently become extremely popular because of its reconfigurability. FPGA, an integrated circuit desi...

Due to vicious competition in the electrical power industry, growing environmental issues and with an ever-increasing demand for electric energy, optimization of the economic load dispatch problem has become a compulsion. This paper emphasizes on a novel modified version of PSO to obtain an optimized solution of the economic load dispatch problem....

Propelled by the advancements in the field of Natural Language Processing, generating summaries of long texts using various NLP tools and techniques has always been a subject of great interest for scientists all over the world. Data is ubiquitous and a large amount of data is processed every second in the digital space. For these reasons also, mach...

Phishing attacks are one of the most widespread problems over the internet. A lot of internet users fall into the hands of attackers every day which accounts into millions of dollars of fraud around the globe every day. The availability of the internet among people who don’t have the knowledge of cyber-attacks adds more to this problem. Thus, there...

Urban planning, in short, deals with solving the problems of the modern society we live in. The problems are complementary to the growing population in today's society. The problems in society range from mundane tasks like ensuring sanitization in society to more technical tasks like managing infrastructures. The concept of smart cities, lately, ha...

This paper introduces a unique and modified method to find the solution of the economic load dispatch (ELD) problem employing intelligent particle swarm optimization. Due to fierce competition in the electric power industry, environmental concerns, and exponentially increasing demand for electric power, it has become necessary to optimize the econo...

The advancements in engineering and technologies have boosted the unprecedented development in the field of remote sensing. The amount of details modern satellites can capture carries immense value to a wide range of applications. Such high-resolution satellite imageries help us to generate a lot of information about the geography of the earth. Apa...

With growing number of ageing population, Parkinson's disease has become a serious problem to huge fraction of people above 60. The disease severely affects the motor system and can lead to death of the patients. There is no cure available for the disease. The symptoms on motor system is seen very late which leads into difficulty in management of t...

Artificial Intelligence (AI) is considered to be the fourth industrial revolution. Arti ficial Intelligence with the hel p of big data has transformed all industries around the worl d. Arti ficial intelligence refers to the simulati on of human or ani mal intelligence in computational systems so that they are programmed to think like intelligent be...

Compressive strength of the concrete is important for analyzing the characteristics of the concrete. The compressive strength is necessary to know if the given mixture of concrete meets the specified requirements. For the sustainability of construction, the compressive strength must meet the required standards. Machine learning models have been rea...

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become an unprecedented public health crisis. To tackle this crisis in an effective way different computational solutions involving artificial intelligence and machine learning have been propounded by researchers across the world. Artifi...

Alzheimer’s disease (AD) is the most common form of neurodegenerating disorder accounting for 60–80% of all dementia cases. The lack of effective clinical treatment options to completely cure or even slow the progression of disease makes it even more serious. Treatment options are available to treat the milder stage of the disease to provide sympto...

Study of the ionosphere is important for research in various domains. Especially in communication systems, this study holds a great importance. In ionospheric research, there is a need to delineate useful and non-useful radar returns from the ionosphere. The useful radar returns can be used for further analysis and non-useful radar returns can be d...

Alzheimer's disease (AD) is a neurodegenerative disorder resulting in memory loss and cognitive decline caused due to the death of brain cells. It is the most common form of dementia and accounts for 60-80% of all dementia cases. There is no single test for diagnosis of AD, the doctors rely on medical history, neuropsychological assessments, comput...

Alzheimer’s disease (AD) which was first time identified and discussed by a German physicist and neuro-pathologist Alois Alzheimer has become one of the major problems of the world, especially for adults and older age population. According to the report by Alzheimer's Disease International in 2018, there were around 50 million people in the world l...