Department of Computer Science and Engineering

Indian Institute of Technology Hyderabad (IITH) is a premier institute of science and technology established in 2008. IITH has been consistently ranked in the&nbsp;<a href="https://iith.ac.in/reports/" rel="noopener noreferrer">top 10 institutes</a>&nbsp;in India for Engineering&nbsp;<a href="https://www.nirfindia.org/2021/EngineeringRanking.html" rel="noopener noreferrer" target="_blank">according to NIRF</a>&nbsp;making it one of the most coveted schools for science and technology in the country.

IITH offers&nbsp;<a href="https://iith.ac.in/academics/under-graduate/">undergraduate programs</a>&nbsp;in all the classical engineering disciplines, applied sciences, design, as well as several modern interdisciplinary areas. Students are given a flexibility to explore a broad set of areas, and potentially pursue a minor or double major in a discipline that is not their own. Students who wish to seek a deeper understanding of their own discipline are strongly encouraged to get involved in cutting-edge research with the help of a faculty to mentor them, and earn an Honors in their own field.

The very foundation of IIT Hyderabad is based on&nbsp;<a href="https://iith.ac.in/research/">research and innovation</a>. The vibrant research culture is evident from the number of patents and publications that IITH produces consistently every year. IITH offers&nbsp;<a href="https://iith.ac.in/academics/programmes-offered/">graduate programs</a>&nbsp;at both a masters, and a doctoral level, in several diverse areas. There are separate programs for technology, design, science, and liberal arts. The&nbsp;<a href="https://iith.ac.in/academics/post-graduate/">MTech program</a>&nbsp;is offered in various modes and durations to cater to the ever-growing need of postgraduate level professionals in the country.

IITH encourages and supports&nbsp;<a href="https://iic-iith.netlify.app/index.html" rel="noopener noreferrer" target="_blank">innovation and entrepreneurship</a>&nbsp;at every stage. The minor program in entrepreneurship is open to all students of IITH, and many of the courses are offered by industrialists who are entrepreneurs themselves. There are various&nbsp;<a href="https://iith.ac.in/research/centres-incubators/">innovation centers and incubators</a>&nbsp;that promote entrepreneurship and help mentor young innovators. IITH has been very successful in building tie-ups with leading academic institutions around the globe.

IITH enjoys a very special relationship with Japanese universities and industries that goes beyond academic and research collaborations. In fact, some of the iconic buildings in IITH campus will carry the signature of Japanese architecture.

IITH creates a unique holistic ecosystem for education that offers interactive learning, a very flexible academic structure, cutting-edge research, strong industry collaboration, and entrepreneurship. This is an environment which enables students and faculty to translate their dreams into realities.

IIT Hyderabad

Let F be a family of graphs. Given an input graph G and a positive integer κ, testing whether G has a κ-sized subset of vertices S, such that G\ S belongs to F, is a prototype vertex deletion problem. These type of problems have attracted a lot of attention in recent times in the domain of parameterized complexity. In this paper, we study two such problems; when F is either a family of cactus graphs or a family of odd-cactus graphs. A graph H is called a cactus graph if every pair of cycles in H intersect on at most one vertex. Furthermore, a cactus graph H is called an odd cactus, if every cycle of H is of odd length. Let us denote by C and Codd, families of cactus and odd cactus, respectively. The vertex deletion problems corresponding to C and Codd are called Diamond Hitting Set and Even Cycle Transversal, respectively. In this paper we design randomized algorithms with running time 12κnO(1) for both these problems. Our algorithms considerably improve the running time for Diamond Hitting Set and Even Cycle Transversal, compared to what is known about them. © Sudeshna Kolay, Daniel Lokshtanov, Fahad Panolan, and Saket Saurabh;.

World University root node

Leibniz International Proceedings in Informatics, LIPIcs

Quick but odd growth of cacti

The b-chromatic number of a graph G,χb(G), is the largest integer κ such that G has a κ-vertex coloring with the property that each color class has a vertex which is adjacent to at least one vertex in each of the other color classes. In the b-Chromatic Number problem, the objective is to decide whether χb (G)≥ κ. Testing whetherχb (G) =Δ(G) + 1, where Δ(G) is the maximum degree of a graph, itself is NP-complete even for connected bipartite graphs (Kratochvíl, Tuza and Voigt, WG 2002). In this paper we study b-Chromatic Number in the realm of parameterized complexity and exact exponential time algorithms. We show that b-Chromatic Number is W[1]-hard when parameterized by κ, resolving the open question posed by Havet and Sampaio (Algorithmica 2013). When κ =Δ(G) + 1, we design an algorithm for b-Chromatic Number running in time 2O(κ2 log κ)nO(1). Finally, we show that b-Chromatic Number for an n-vertex graph can be solved in time O(3nn4 log n). © Fahad Panolan, Geevarghese Philip, and Saket Saurabh;.

B-chromatic number: Beyond NP-hardness

Research on modeling time series text corpora has typically focused on predicting what text will come next, but less well studied is predicting when the next text event will occur. In this paper we address the latter case, framed as modeling continuous inter-arrival times under a log-Gaussian Cox process, a form of inhomogeneous Poisson process which captures the varying rate at which the tweets arrive over time. In an application to rumour modeling of tweets surrounding the 2014 Ferguson riots, we show how interarrival times between tweets can be accurately predicted, and that incorporating textual features further improves predictions. © 2015 Association for Computational Linguistics.

Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing

Modeling tweet arrival times using log-Gaussian Cox processes

A recent result of Moshkovitz [10] presented an ingenious method to provide a completely elementary proof of the Parallel Repetition Theorem for certain projection games via a construction called fortification. However, the construction used in [10] to fortify arbitrary label cover instances using an arbitrary extractor is insufficient to prove parallel repetition. In this paper, we provide a fix by using a stronger graph that we call fortifiers. Fortifiers are graphs that have both ℓ1 and ℓ2 guarantees on induced distributions from large subsets. We then show that an expander with sufficient spectral gap, or a bi-regular extractor with stronger parameters (the latter is also the construction used in an independent update [11] of [10] with an alternate argument), is a good fortifier. We also show that using a fortifier (in particular ℓ2 guarantees) is necessary for obtaining the robustness required for fortification. © Amey Bhangale, Ramprasad Saptharishi, Girish Varma, and Rakesh Venkat.

On fortification of projection games

Cardiovascular diseases (CVD) are a leading cause of unnecessary hospital admissions as well as fatalities placing an immense burden on the healthcare industry. A process to provide timely intervention can reduce the morbidity rate as well as control rising costs. Patients with cardiovascular diseases require quick intervention. Towards that end, automated detection of abnormal heartbeats captured by electronic cardiogram (ECG) signals is vital. While cardiologists can identify different heartbeat morphologies quite accurately among different patients, the manual evaluation is tedious and time consuming. In this chapter, we propose new features from the time and frequency domains and furthermore, feature normalization techniques to reduce inter-patient and intra-patient variations in heartbeat cycles. Our results using the adaptive learning based classifier emulate those reported in existing literature and in most cases deliver improved performance, while eliminating the need for labeling of signals by domain experts. © 2015 - IOS Press and the authors.

Bio-Medical Materials and Engineering

Adaptive learning based heartbeat classification

As there is a growing demand for biometrics usage in e-Society, the biometric recognition system faces the scalability issue as the number of people to be enrolled into the system runs into billions. In this paper, we propose an approach for iris classification using three different iris classes based on iris fiber structures, namely, stream, flower, jewel and shaker for faster retrieval of identities in large scale biometric system. A sparsity based on-line dictionary learning (ODL) algorithm is used in the proposed classification approach where dictionaries are developed for each class using log-Gabor wavelet features. Also, a method for iris adjudication process is illustrated using the iris classification to reduce the search space. The efficacy of the proposed classification approach is demonstrated on the standard UPOL iris database. © 2015 Gesellschaft für Informatik e.V.

Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)

Sparsity-based iris classification using iris fiber structures

Object classification is an important step in visual recognition and semantic analysis of visual content. In this paper, we propose a method for classification of objects that is invariant to illumination color, illumination direction and viewpoint based on 3D color histogram. A 3D color histogram of an image is represented as a 2D image, to capture the color composition while preserving the neighborhood information of color bins, to realize the necessary visual cues for classification of objects. Also, the ability of convolutional neural network (CNN) to learn invariant visual patterns is exploited for object classification. The efficacy of the proposed method is demonstrated on Amsterdam Library of Object Images (ALOI) dataset captured under various illumination conditions and angles-of-view. © 2015, Springer International Publishing Switzerland.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

View and illumination invariant object classification based on 3D color histogram using convolutional neural networks

Time slot assignments in a TDMA ad hoc wireless network (AWN) is either centrally coordinated by a root node or distributed among all the nodes in the network. In the centralized TDMA network, the root node uses the global knowledge of the network to assign slots, but becomes more challenging in case of distributed network, as each node is expected to assign a slot for itself without conflicting other nodes' slot selection. There is plenty of literature on how slots are assigned in a centralized TDMA network but only a few on distributed. Quality of Service (QoS) is critically important in AWNs and a good slot assignment scheme prioritizes its QoS metrics during the process of slot assignments. Real-time communications require end-to-end delay and jitter within acceptable limits for better overall QoS. This paper proposes a delay sensitive approach to TDMA Slot assignment problem in distributed AWNs. The proposed approach does a balancing act between end-to-end delay and spatial reuse. The experimental results demonstrate that the proposed approach obtains quality results in terms of call acceptance rate, end-to-end delay and spatial reusability. © 2015 IEEE.

2015 21st National Conference on Communications, NCC 2015

Delay sensitive TDMA slot assignment in ad hoc wireless networks

Designing high performance channel assignment schemes to harness the potential of multi-radio multi-channel deployments in wireless mesh networks (WMNs) is an active research domain. A pragmatic channel assignment approach strives to maximize network capacity by restraining the endemic interference and mitigating its adverse impact on network performance. Interference prevalent in WMNs is multi-faceted, radio co-location interference (RCI) being a crucial aspect that is seldom addressed in research endeavors. In this effort, we propose a set of intelligent channel assignment algorithms, which focus primarily on alleviating the RCI. These graph theoretic schemes are structurally inspired by the spatio-statistical characteristics of interference. We present the theoretical design foundations for each of the proposed algorithms, and demonstrate their potential to significantly enhance network capacity in comparison to some well-known existing schemes. We also demonstrate the adverse impact of radio co-location interference on the network, and the efficacy of the proposed schemes in successfully mitigating it. The experimental results to validate the proposed theoretical notions were obtained by running an exhaustive set of ns-3 simulations in IEEE 802.11g/n environments. © 2015 IEEE.

2015 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015

Radio co-location aware channel assignments for interference mitigation in wireless mesh networks

We address the problem of designing a communication system for deploying under disaster situations where the pre-disaster communication infrastructure has been uprooted. The disaster communication system is required to aid in rescue effort by providing text, voice, and video communication links between the field worker and the operation center. It is also required to provide some communication services to the affected citizens so that the overwhelming demands made on the communication infrastructure during the times of disaster are mitigated to some extent. The other highlights of the design are (i) its low-cost nature achieved by exploiting the economies of scale, (ii) constant communication between the field worker and manager, (iii) the use of basic mobile phones with text-only features for gathering victim data and populating the victim database in real-time, and (iv) web-based applications for managing victim data. © 2014 IEEE.