Md Tanvir Al Amin

Md Tanvir Al Amin
University of Illinois, Urbana-Champaign | UIUC · Department of Computer Science

PhD in Computer Science, UIUC

About

37
Publications
3,707
Reads
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698
Citations
Citations since 2016
15 Research Items
616 Citations
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2016201720182019202020212022020406080100120140
2016201720182019202020212022020406080100120140
Introduction
Skills and Expertise
Additional affiliations
May 2017 - present
Google Inc.
Position
  • Software Engineer
August 2011 - present
University of Illinois, Urbana-Champaign
Position
  • Research Assistant
April 2009 - April 2011
Bangladesh University of Engineering and Technology
Position
  • Lecturer

Publications

Publications (37)
Conference Paper
Full-text available
The paper presents a new model for crowd-sensing applications, where humans are used as the sensing sources to report information regarding the physical world. In contrast to previous work on the topic, we consider a model where the sources in question are polarized. Such might be the case, for example, in political disputes and in situations invol...
Conference Paper
Full-text available
This paper develops algorithms for improved source selection in social sensing applications that exploit social networks (such as Twitter, Flickr, or other mass dissemination networks) for reporting. The collection point in these applications would simply be authorized to view relevant information from participating clients (either by explicit clie...
Conference Paper
Full-text available
In a wireless ad hoc network, the main issue of a good broadcast protocol is to attain maximum reachability with minimal packet forwarding. Existing protocols address this issue by utilizing the knowledge of up to 2-hop neighbors to approximate an MCDS (minimum connected dominating set) via heuristics derived from techniques known as Self pruning a...
Article
Full-text available
The paper introduces a new direction in quality-of-service-aware networked sensing that designs communication protocols and scheduling policies for data delivery that are optimized specifically for decision needs. The work complements present decision monitoring and support tools and falls in the larger framework of decision-driven resource managem...
Conference Paper
Emerging distributed in-memory computing frameworks , such as Apache Spark, can process a huge amount of cached data within seconds. This remarkably high efficiency requires the system to well balance data across tasks and ensure data locality. However, it is challenging to satisfy these requirements for applications that operate on a collection of...
Conference Paper
Full-text available
This paper presents unsupervised algorithms to uncover polarization in social networks (namely, Twitter) and identify polarized groups. The approach is language-agnostic and thus broadly applicable to global and multilingual media. In cases of conflict, dispute, or situations involving multiple parties with contrasting interests, opinions get divid...
Article
The explosive growth in social networks that publish real-time content begs the question of whether their feeds can complement traditional sensors to achieve augmented sensing capabilities. One such capability is to explain anomalous sensor readings. In our previous conference paper, we built an automated anomaly clarification service, called Clari...
Chapter
This chapter demonstrates the utility of exploiting signal processing techniques common to physical sensing modalities in order to reconstruct conditions of the physical world from social network feeds. We show that, as a sensing modality, social sensing is not unlike acoustic, vibration, or magnetic sensing. A mathematical analogy is presented bet...
Conference Paper
Signal processing techniques such as filtering, detection, estimation and frequency domain analysis have long been applied to extract information from noisy sensor data. This paper describes the exploitation of these signal processing techniques to extract information from social networks, such as Twitter and Instagram. Specifically, we view social...
Article
The explosive growth in social networks that publish real-time content begs the question of whether their feeds can complement traditional sensors to achieve augmented sensing capabilities. One such capability is to explain anomalous sensor readings. In our previous conference paper, we built an automated anomaly clarification service, called Clari...
Article
Full-text available
This paper complements the large body of social sensing literature by developing means for augmenting sensing data with inference results that "fill-in" missing pieces. It specifically explores the synergy between (i) inference techniques used for filling-in missing pieces and (ii) source selection techniques used to determine which pieces to retri...
Conference Paper
This paper presents experiences with eNav, a smartphone-based vehicular GPS navigation system that has an energy-saving location sensing mode capable of drastically reducing navigation energy needs. Traditional navigation systems sample the phone's GPS at a fixed rate (usually around 1Hz), regardless of factors such as current vehicle speed and dis...
Conference Paper
Full-text available
The increasing availability of smartphones, cameras, and wearables with instant data sharing capabilities, and the exploitation of social networks for information broadcast, heralds a future of real-time information overload. With the growing excess of worldwide streaming data, such as images, geotags, text annotations, and sensory measurements, an...
Conference Paper
The proliferation of mobile sensing and communication devices in the possession of the average individual generated much recent interest in social sensing applications. Significant advances were made on the problem of uncovering ground truth from observations made by participants of unknown reliability. The problem, also called fact-finding commonl...
Article
Full-text available
Signal feature extraction and classification are two common tasks in the signal processing literature. This paper investigates the use of source identities as a common mechanism for enhancing the classification accuracy of social signals. We define social signals as outputs, such as microblog entries, geotags, or uploaded images, contributed by use...
Conference Paper
Full-text available
In this paper, we present a unique study of two successful methods for computing message reliability. The first method is based on machine learning and attempts to find a predictive model based on network features. This method is generally geared towards assessing credibility of messages and is able to generate high recall results. The second metho...
Conference Paper
Full-text available
Millions of people exchange user-generated information through online social media (SM) services. The prevalence of SM use globally and its growing significance to the evolution of events has attracted the attention of the Army and other agencies charged with protecting national security interests. The information exchanged in SM sites and the netw...
Conference Paper
This paper complements the large body of social sensing literature by developing means for augmenting sensing data with inference results that "fill-in" missing pieces. Unlike trend-extrapolation methods, we focus on prediction in disaster scenarios where disruptive trend changes occur. A set of prediction heuristics (and a standard trend extrapola...
Conference Paper
We present eNav, a smartphone-based vehicular GPS navigation system that has an energy-saving location sensing mode capable of drastically reducing navigation energy needs. Traditional implementations sample the phone GPS at the highest possible rate (usually 1Hz) to ensure constant highest possible localization accuracy. This practice results in e...
Article
This paper complements the large body of social sensing literature by developing means for augmenting sensing data with inference results that " fill-in " missing pieces. Unlike trend-extrapolation methods, we focus on prediction in disaster scenarios where disruptive trend changes occur. A set of prediction heuristics (and a standard trend extrapo...
Conference Paper
Full-text available
In this demo, a learning system, called Metis, is presented that extrapolates missing pieces in participatory sensing data. The work addresses the challenge of incomplete coverage in participatory sensing applications, where lack of complete control over participant mobility and sensing patterns may create coverage gaps in space and in time. Metis...
Article
Full-text available
Invention of Transistors in 1948 started a new era in technology, called Solid State Electronics. Since then, sustaining development and advancement in electronics and fabrication techniques has caused the devices to shrink in size and become smaller, paving the quest for increasing density and clock speed. That quest has suddenly come to a halt du...
Conference Paper
Full-text available
Presenting a clear image by reducing the noise to a minimal level is one of the most fundamental research topics in image processing. Different types of noise are initiated during the process of acquisition to digitiza-tion of an image, causing degradation in quality. As there is no way for total elimination, several methods are employed depending...
Conference Paper
Full-text available
Transmitting TV programs over the Internet has always been a great issue in multimedia service. With the ad-vent of broadband internet connectivity, real time video and audio delivery on the Internet is getting popular day by day. Although the industry is making great and highly publicized plans for future (inter)national video on demand, there is...
Article
Full-text available
This paper addresses the problem of collection and delivery of a representative subset of pictures, in participatory camera networks, to maximize coverage when a significant portion of the pictures may be redundant or irrelevant. Consider, for example, a rescue mission where volunteers and survivors of a large-scale disaster scout a wide area to ca...

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Projects (3)