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Seminar: Multisensory Integration in the Brain

Wednesday, February 13th, 2019

 

Department of Computational and Data Sciences and IEEE SP Bangalore Chapter invite you for the following seminar

SPEAKER  : Dr. Shirin Dora, Post Doc

TITLE         : Multisensory Integration in the Brain

Date/Time   : February 14, 2019 (Thursday) 04:00 PM

Venue          : 102 CDS Seminar Hall.

 ABSTRACT

Multisensory integration is a phenomenon by which the brain infers coherent and robust representations using incoming sensory information in different modalities. It plays a significant role in perception as well as all cognitive functions from memory to decision-making. Because of its inherent multimodal nature, it is harder to study in experiments and many open questions exist regarding its underlying neural mechanisms. In my research, I approach this problem from two different perspectives using computational models in conjunction with experimental data. In the first method, I focus on understanding the neurobiological mechanisms that might support multisensory integration. I will show that deep neural networks trained using predictive coding can account for neuronal properties like selectivity and sparsity along the visual cortical hierarchy. In the second method focus shifts to identifying the underlying structures necessary for multisensory integration rather than the intermediate mechanisms that yield these structures

 BIOGRAPHY

Shirin Dora completed his PhD in machine learning from Nanyang Technological University in Singapore. His research focused on developing biologically plausible learning approaches for spiking neural networks. During his PhD, he developed a keen interest in the mechanisms of perception and cognition in the brain. This led him to pursue a post-doctoral research in computational neuroscience in the cognitive and systems neuroscience group at the University of Amsterdam. In his postdoctoral research, he collaborates with experimentalists in building models of perception and multisensory integration in the brain.

 

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                                                               ALL ARE WELCOME

Seminar: Weakly-supervised and incremental learning

Saturday, December 22nd, 2018

Talk: Computational Imaging with Few Photons, Electrons, or Ions

Wednesday, November 28th, 2018

The IEEE Signal Processing Society, Bangalore Chapter

and

Department of Electrical Engineering, Indian Institute of Science

 

cordially invite you to an IEEE Distinguished Lecture on

Computational Imaging with Few Photons, Electrons, or Ions

 

Speaker: Prof. Vivek Goyal, Boston University

 

Date and Time: December 3, 2018, 11 AM to 12 noon (coffee/tea:
10.45 AM)

 

Venue: Multimedia Classroom, Electrical Engineering Department, IISc.

 

Abstract:

LIDAR systems use single-photon detectors to enable long-range reflectivity and depth imaging.  By exploiting an inhomogeneous Poisson process observation model and the typical structure of natural scenes, first-photon imaging demonstrates the possibility of accurate LIDAR with only 1 detected photon per pixel, where half of the detections are due to (uninformative) ambient light.  I will explain the simple ideas behind first-photon imaging. Then I will touch upon related subsequent works that mitigate the limitations of detector arrays, withstand 25-times more ambient light, allow for unknown ambient light levels, and capture multiple depths per pixel. The philosophy of modeling at the level of individual particles is also at the root of current work in focused ion beam microscopy.

 

Related paper DOIs:

10.1126/science.1246775

10.1109/TSP.2015.2453093

10.1109/LSP.2015.2475274

10.1364/OE.24.001873

10.1038/ncomms12046

10.1109/TSP.2017.2706028

10.1126/science.aat2298

 

Speaker biography:

Vivek Goyal received the M.S. and Ph.D. degrees in electrical engineering from the University of California, Berkeley, where he received the Eliahu Jury Award for outstanding achievement in systems, communications, control, or signal processing.  He was a Member of Technical Staff at Bell Laboratories, a Senior Research Engineer for Digital Fountain, and the Esther and Harold E. Edgerton Associate Professor of Electrical Engineering at MIT. He was an adviser to 3dim Tech, winner of the 2013 MIT $100K Entrepreneurship Competition Launch Contest Grand Prize, and consequently with Nest Labs 2014-2016.  He is now an Associate Professor of Electrical and Computer Engineering at Boston University.

 

Dr. Goyal is a Fellow of the IEEE.  He was awarded the 2002 IEEE Signal Processing Society (SPS) Magazine Award, the 2017 IEEE SPS Best Paper Award, an NSF CAREER Award, and the Best Paper Award at the 2014 IEEE International Conference on Image Processing.  Work he supervised won student best paper awards at the IEEE Data Compression Conference in 2006 and 2011, the IEEE Sensor Array and Multichannel Signal Processing Workshop in 2012, and the IEEE International Conference on Imaging Processing in 2018 as well as five MIT thesis awards.  He currently serves on the Editorial Board of Foundations and Trends and Signal Processing, the IEEE SPS Computational Imaging SIG, and the IEEE SPS Industry DSP TC. He previously served on the Scientific Advisory Board of the Banff International Research Station for Mathematical Innovation and Discovery, as Technical Program Committee Co-chair of Sampling Theory and Applications 2015, and as Conference Co-chair of the SPIE Wavelets and Sparsity conference series 2006-2016.  He is a co-author of Foundations of Signal Processing (Cambridge University Press, 2014).

Seminar by Dr. Emtiyaz Khan

Thursday, November 1st, 2018

 

Department of Electrical Engineering
and
IEEE Signal Processing Society Bangalore Chapter

invite you to a talk by

Dr. Emtiyaz Khan, RIKEN Center for Advanced Intelligence Project, Tokyo

on

Fast and Scalable Estimation of Uncertainty using Bayesian Deep Learning

November 2, 2018; 2.30 PM, Multimedia Classroom, Electrical Engineering department, IISc

Abstract:

Uncertainty estimation is essential to design robust and reliable systems, but this usually requires more effort to implement and execute compared to maximum-likelihood methods. In this talk, I will summarize some of our recent work that enables fast and scalable estimation of uncertainty using deep models, such as Bayesian neural network. The main feature of our method is that they are extremely easy to implement within existing deep-learning softwares. I will also summarize some of the current challenges faced by the Bayesian deep-learning community and how real-world applications can be useful for our research.

Joint work with Wu Lin (UBC), Didrik Nielsen (RIKEN), Voot Tangkaratt (RIKEN), Yarin Gal (UOxford), Akash Srivastva (UEdinburgh), Zuozhu Liu (SUTD).

About the speaker:
Dr. Emtiyaz Khan is a team leader (equivalent to Full Professor) at the RIKEN center for Advanced Intelligence Project (AIP) in Tokyo where he leads the Approximate Bayesian Inference (ABI) Team. Since April 2018, he is a visiting professor at the EE department in Tokyo University of Agriculture and Technology (TUAT) and also a part-time lecturer at Waseda University.

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Co-sponsor:
IEEE Signal Processing Society
Bangalore chapter
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Seminar: Application of technology in preservation of inscription stones

Friday, October 5th, 2018

 

The Department of Electrical Engineering and
The IEEE Signal Processing Society Bangalore Chapter

invite you to a talk on

“Importance of Inscription Stones and the application of technology in their preservation”

by
Vinay Kumar and Udaya Kumar PL

Date and time: October 12, 2018; 4:00 PM (teach/coffee at 3:45pm)

Venue: Multimedia Classroom, Department of Electrical Engineering, IISc.

Abstract:
Inscriptions stones (shila shaasanas) in the Bengaluru region are original
documentation of the region’s people, culture, religion and language dating
back to as early as 750CE. These stones give us a picture of the social fabric
of the past including linguistic plurality amidst people, construction of lakes,
tax practices, donations, grants, governance and suchlike. Rampant
urbanization in Bengaluru has led to destruction of a majority of the 150
stones in the old ‘Bangalore’ region documented by B.L. Rice and others from
1894 to 1905 in the remarkable twelve-volume series Epigraphia Carnatica.
#InscriptionStonesOfBangalore is a civic activism project to raise awareness
and protect ancient inscription stones found in the Bengaluru region. The
project has been using technology (social media, mapping, 3D scanning, 3D
printing, OCR) to protect preserve & restore the dignity of the last few
remaining ‘Inscription Stones Of Bangalore’.
Facebook: https://www.facebook.com/groups/inscriptionstones
Twitter: @inscriptionblr

Biography of the speaker:
Vinay’s interests range from Mars to Mohenjodaro. He has a master’s degree
in Aerospace Engineering from University of Texas at Arlington. He is a
patent engineer who was previously with the medical device research team at
Novo Nordisk. He is also a recipient of the Govt. of India – Department of
Biotechnology Foldscope research grant, to explore possibilities of using
Foldscope as a research tool. He currently runs Sqvare Peg Labs, a non-profit
with a mission to advance public understanding of science & technology.
Udaya is a passionate Bangalorean and an accidental historianconservationist.
He has a master’s degree in Engineering Mechanics from IIT Madras and has
earlier worked in various capacities for the Tatas and General Electric.
He currently heads the Software Delivery Centre, India at Schneider
Electric, delivering industrial automation solutions to clients worldwide.

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Co-sponsor:
IEEE Signal Processing Society
Bangalore chapter
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Seminar: Deep CNN in Video Analytics for Assistive Healthcare Tech

Friday, August 17th, 2018
IEEE Signal Processing Society, Bangalore Chapter,
and Department of Computational and Data Sciences, Indian Institute of Science
Invite you to the following talk:
Title: Deep Convolutional Neural Network in Video Analytics for Assistive Healthcare Technologies.
by Dr. Bappaditya Mandal, Lecturer (Computing), Keele University, UK
Time & Date:  11:00 AM, Wednesday, August 22, 2018 
Venue: CDS Seminar Hall (Room No: 102), IISc.
Abstract:
Because of the fast advancement and price reduction in the hardware and computing facilities, deep convolutional neural network (DCNN) for video analytics has been computationally possible in practise and have shown considerable improvement in many video analytics tasks, such as object recognition, face recognition, etc. My talk will cover two aspects of my research: (1) Computer Vision on Wearable devices and (2) DCNN for two Biomedical Applications: Melanoma Skin Cancer Detections and Optic Disc and Cup Segmentation for Glaucoma Assessment. In the first part of my talk, I will talk about the development of computational methodologies in wearable devices that would help people to improve their lives. For example, camera in the wearable devices (such as Google Glass, GoPro) generates first-person-view (FPV) or egocentric videos that show near human vision field of view. They provide immerse opportunities for various applications, such as face recognition for social interaction assistance. Life-logged egocentric data are useful for summarization and retrieval (memory assistance), security, health monitoring, lifestyle analysis to memory rehabilitation (i.e., subject matters being remembered, such as time, place, object, people, context, and mental states) for dementia patients.
In the second portion of my talk I will discuss how we have improved the deep residual network with regularized Fisher framework for differentiating melanoma (malignant) from non-melanoma (benign) skin cancer cases, which is supported by large number of experimental results from benchmark databases. I will conclude my talk on how we have modified deep residual learning framework to extract more patch based discriminating features by improving the information flow in the network by introducing extra skip connections for the challenging optic disk and optic cup segmentation for glaucoma assessment.
Speaker Bio:
Bappaditya Mandal has received the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology (IIT), Roorkee, India and the Ph.D. degree in Electrical and Electronic Engineering from Nanyang Technological University (NTU), Singapore, in 2003 and 2008, respectively. His research interest are in the areas of computer vision, machine learning, pattern recognition and video analytics. Bappaditya has worked as a Scientist for >9 years at the Cognitive Vision Lab, Visual Computing Department in the Institute for Infocomm Research, A*STAR, Singapore, between May 2008 to June 2017 for a number of research projects and published extensively in Journals, conferences and workshops. He has been in the Kingston University London for a short while before joining as a Lecturer in Computer Science, School of Computing and Mathematics at Keele University, United Kingdom in March 2018.
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ALL ARE WELCOME
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Short Course on Adaptive Filters

Friday, May 11th, 2018

 

Short Course on Adaptive Filters by Prof. V. John Mathews and Prof. K.V.S. HARI

28 th May – 29 th May, 2018

 

IMPORTANT DATES

Last date for receipt of completed application:
23 rd May, 2018
Confirmation for participants through e-mail:
26 th May, 2018
Workshop starts with registration on
28 th May, 9:00AM

 

Details of this Course can be found here

 

 

 

[Seminar] CDS : 25th April 2018 : “Powering fashion e-commerce with computer vision and deep learning “

Friday, April 20th, 2018

IEEE Signal Processing Society, Bangalore Chapter,
and Department of Computational and Data Sciences, Indian Institute of Science

Invite you to the following talk:

Title: Powering fashion e-commerce with computer vision and deep learning

by Vishnu Vardhan Makkapati, Architect, Myntra,

Time & Date: 11:00 AM, Wednesday, April 25, 2018
Venue: CDS Seminar Hall (Room No: 102), IISc.

Abstract:

Fashion is a highly visual field. Images, though a rich source of domain information, are extremely subjective, and their interpretation is more art than science. Our goal is to teach a machine to interpret these varied images in a consistent manner, while eliminating subjectivity from the process. We have used our industry leading fashion catalog to understand and interpret the inherent fine-grained details in images. These details will help power very interesting use cases in fashion e-commerce such as cataloging, purchasing, personalisation etc. In this talk, we will present an overview of our work on mining catalog images using deep learning and computer vision. We will also discuss some of our recent work on generation of fashion designs using Generative Adversarial Networks.

Speaker Bio:
Vishnu Vardhan Makkapati received the B.E. (Honors) degree in electrical and electronics and the M.Sc. (Honors) degree in mathematics from the Birla Institute of Technology and Science, Pilani, India, in 2000, and the M.Sc. (Engg.) degree from the Indian Institute of Science, Bangalore, in 2007. He was with the IBM India Software Laboratory until April 2001 and, then, with the Honeywell Technology Solutions Laboratory, India, until December 2006, reaching the level of Principal Engineer. He was a Senior Scientist with Philips Research India until July 2015, where he most recently led the efforts on camera based vital signs. He is currently an Architect with Myntra. He holds six US patents with many others pending. He is a senior member of the IEEE.

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[Seminar] ECE: 26th April 2018 : “Hearing Assessment Technologies (Audiometry) and some new challenges”

Friday, April 20th, 2018

Dept of ECE, Indian Institute of Science, Bangalore
&
IEEE Signal Processing Society, Bangalore Chapter

have arranged the following technical lecture; All are welcome.

Speaker: Dr. Madhuri Gore

Title: “Hearing Assessment Technologies (Audiometry)
and some new challenges”
Date/Time: 26th April 2018, Thursday, 4-5pm
Venue: Golden Jubilee Seminar Hall, ECE Dept, IISc
Tea/Coffee: 3.45pm

Abstract:
The auditory system has unique abilities that enable to person to carry out tasks such as listening in noise, detecting differences in sound object, localizing sounds, music appreciation and learning languages, activities that are deceptively simple. Hearing assessment (common parlance referred to as audiometry) refers to behavioural and physiological tests to assess function and sometimes “structure” of the different components of the auditory pathway. For this, a number of stimuli varying from the simple pure tones to synthetic speech which are presented in different modes, at different SNRs, in an attempt to simulate real life conditions, but more often to diagnose the problem. Creating appropriate stimuli and calibration is an issue.

Speaker Bio:
Dr. Madhuri Gore is Principal and Deputy Director (T) of “Dr.S.R.Chandrasekhar Institute of Speech and Hearing,” Bangalore. She has been in academics since 1993. She has vast clinical experience in hearing disorders since 1982. Her special clinical interest in Cochlear Implants, Auditory Plasticity, Auditory Neuropathy, Spectrum Disorder; also interested in Diagnostic Audiology, Psychophysics and Speech Perception.

[Seminar] CDS : 19th April 2018 : “Image-based Crowd Analytics”

Thursday, April 12th, 2018

Dear All,

IEEE Signal Processing Society, Bangalore Chapter,
and Department of Computational and Data Sciences, Indian Institute of Science

Invite you to the following talk:

Title: Image-based Crowd Analytics
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by Vishwanath A. Sindagi, Rutgers University,

Time & Date: 11:00 AM, Thursday, April 19, 2018
Venue: CDS Seminar Hall (Room No: 102), IISc.

Abstract:

The study of human behavior based on computer vision techniques has gained a lot of interest in recent years. In particular, the behavioral analysis of crowded scenes is of great interest due to a variety of reasons. Exponential growth in the world population and the resulting urbanization has led to an increased number of activities involving high density crowd such as sporting events, political rallies, public demonstrations, thereby resulting in more frequent crowd gatherings in the recent years. In such scenarios, it is essential to analyze crowd behavior for better management, intelligence gathering, safety and security. In this talk, I will present some of my recent work on developing algorithms for crowd analytics, including crowd counting from unconstrained imagery, crowd segmentation and human detection from crowded scenes. I will conclude my talk by describing several promising directions for future research.

Bio:

Vishwanath is a second year PhD student in Dept. Of Electrical & Computer Engineering at Rutgers University. He is being advised by Prof. Vishal M Patel. Prior to joining Rutgers, he worked for Samsung R&D Bangalore and AllGo Embedded Systems. He graduated from IIIT-Bangalore with a Master’s degree in Information Technology. His current research is on computer vision and machine learning with a specific focus on crowd analytics, face detection, applications of generative modeling, domain adaptation and low-level vision.

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ALL ARE WELCOME
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