KCIS Invited Talk By
Dr Karthik Desingh,
Postdoctoral position at the University of Washington (UW)
on
Robust and Generalized Perception Towards Mainstreaming Domestic Robots
Speaker’s long-term goal is to build general-purpose robots that can care for and assist the aging and disabled population by autonomously performing various real-world tasks. To robustly execute various tasks, a general-purpose robot should be capable of seamlessly perceiving and manipulating a wide variety of objects in our environment. To achieve a given task, a robot should continually perceive the state of its environment, reason with the task at hand, plan and execute appropriate actions. In this pipeline, perception is largely unsolved and one of the more challenging problems. Common indoor environments typically pose two main problems: 1) inherent occlusions leading to unreliable observations of objects, and 2) presence and involvement of a wide range of objects with varying physical and visual attributes (i.e., rigid, articulated, deformable, granular, transparent, etc.). Thus, we need algorithms that can accommodate perceptual uncertainty in the state estimation and generalize to a wide range of objects.]
August 5th, 2022, 3:00 PM
at
KRB Auditorium, IIIT Hyderabad, Gachibowli
About Honourable Speaker
Karthik Desingh will be joining the Department of Computer Science and Engineering at the University of Minnesota as an Assistant Professor in the Fall of 2022. Karthik recently completed his Postdoctoral position at the University of Washington (UW), where he worked with Professor Dieter Fox. Before joining UW, he received his Ph.D. in Computer Science and Engineering from the University of Michigan, working with Professor Chad Jenkins. During his Ph.D., he was closely associated with the Robotics Institute and Michigan AI. He earned his B.E. in Electronics and Communication Engineering at Osmania University, India, and M.S. in Computer Science at IIIT-Hyderabad and Brown University. He researches at the intersection of robotics, computer vision, and machine learning, primarily focusing on providing perceptual capabilities to robots using deep learning and probabilistic techniques to perform tasks in unstructured environments. His work has been recognized with the best workshop paper award at RSS 2019 and nominated as a finalist for the best systems paper award at CoRL 2021. He is serving as an Associate Editor for IROS 2022
KCIS Invited Talk By
Dr Sourav Garg,
Queensland University of Technology (QUT)
on
Image Representation & Learning for Mobile Robots
Perception and navigation are fundamental capabilities of an autonomous mobile robot. Sensory data in the form of RGB camera images is information-rich, convenient to use, low-cost and power-efficient. With the advent of deep learning, processing raw images into meaningful representations has made a significant stride. However, depending on the end-task, for example, those relevant for mobile robot localization, such latent representations can be defined in many different ways to cover several unique aspects of autonomous navigation. This talk will cover my research in the field of visual place recognition, discussing the use of semantics, monocular depth, hashing, sequences, and deep learning to generate image representations that address various challenges in long-term robot autonomy.
July 11th, 2022, 3:00 PM
at
A3 117, IIIT Hyderabad, Gachibowli
About Honourable Speaker
Dr. Sourav Garg is co-leading the Perception and Localization research theme at the QUT Centre for Robotics (QCR) as a Postdoctoral Research Fellow. He received his PhD from Queensland University of Technology (QUT) in 2019 while being a part of the Australian Centre for Robotic Vision (ACRV). Sourav pioneered research in the twin challenge of visual place recognition for mobile robot localization that requires dealing with scene appearance and camera viewpoint simultaneously. His research spans several aspects of robotic vision including semantics, sequences, hashing, adverse conditions, representation learning and centimeter-precise localization. His thesis received Executive Dean’s Commendation for Outstanding Thesis Award and his research published in Robotics: Science & Systems (RSS) and International Journal of Robotics Research (IJRR) won the SAGE QUT Student Publication Prize. He has published research at various top-tier international conferences and journals across both robotics and computer vision. He has also delivered invited talks at notable venues. Sourav has extensive academic research collaborations worldwide and has worked with both industry and government. His research has also been covered by numerous social media platforms including Brisbane Times, Engineers Australia Create Magazine, and Tech Xplore.
Distinguished Lecture by
Prof Soumen Chakrabarti,
on
Graph Neural Networks and Knowledge Graph Completion
Prof Soumen Chakrabarti talks about Link Prediction Algorithms and how they will materialize in the future. In this context, he will explain Graph Neural Networks (GNNs), particularly Graph Convolution Networks (GCNs). He will also lay out the proposal on PermGNN and showcase a differentiation in comparison with the earlier GNNs.
March 30th, 2021, 11:30 AM - 12:30 PM
at
Virtual Event
About Honourable Speaker
Dr Soumen Chakrabarti, currently a professor at IIT Bombay, obtained his Ph.D from University of California, Berkeley and went on to workP IBM Almaden Research Center, Camegie-Mellon University and Google. He has published extensively and his work on keyword search in databases received the 70-year influential paper award at ICDE .2012. He is the author of one of the earliest books on Web search and mining. Prof. Chakrabadi received several awards including the prestigious Shanti Swarup Bhatnagar Prize in 2014. He is a fellow of Indian National Academy of Engineering, Indian Academy of Sciences, Indian National Science Academy and a distinguished alumni of IIT Kharagpur
Distinguished Lecture by
Prof. Petri Toiviainen,
University of
Jyväskylä
on
Machine Learning in Music Research
Prof Petri research interests are in the areas of music research, psychology, computational data analysis and systemic and cognitive neuroscience
February 19th, 2020, 4:00 PM
at
KRB Auditorium, IIIT Hyderabad, Gachibowli
About Honourable Speaker
Petri Toiviainen is a professor at the University of Jyväskylä whose research interests are in the areas of music research, psychology, computational data analysis and systemic and cognitive neuroscience. Professor Toiviainen is Director of the Academy of Finland’s Centre of Excellence in Interdisciplinary Music Research. He is an internationally recognized scholar in the field of systematic musicology, specializing in the modelling of music cognition and computational methods of music analysis. His research is applied in the context of music therapy, music education and in the playing of music. He has published several articles and given a number of keynote talks on these topics, and is an editorial board member of a number of journals. He is also a co-author of several widely used software tools for music analysis, including the MIDI Toolbox, the MIRToolbox, and the Motion Capture Toolbox.
Distinguished Lecture by
Prof Amit Sheth,
University of South
Carolina
on
Knowledge Graphs and their central role in big data processing
Early use of knowledge graphs, before the start of this century, related to building a knowledge graph manually or semi-automatically and applying them for semantic applications, such as search, browsing, personalization, and advertisement. Taalee/Semagix Semantic Search in 2000 had a KG that covered many domains and supported search with an equivalent of today’s infobox. Along with the growth of big data, machine learning became the preferred technique for searching, analyzing and deriving insights from such data. Prof. Amit Sheth and his research group observed the complementary nature of bottom-up (machine learning-driven) and top-down (semantic, knowledge graph and planning based) techniques. Recently they have seen growing efforts involving the shallow use of a knowledge graph to improve the semantic and conceptual processing of data. The future promises deeper and congruent incorporation or integration of knowledge graphs in the learning techniques (which they call knowledge-infused learning), where knowledge graphs combining statistical AI (bottom-up) and symbolic AI learning techniques (top-down) play a critical role in hybrid and integrated intelligent systems. Throughout his talk, Prof. Sheth provided real-world examples, products, and applications where the knowledge graph played a pivotal role.
January 6th, 2020, 5:00 PM
at
Faculty Meeting Room, KRB, IIIT Hyderabad, Gachibowli
About Honourable Speaker
Prof. Amit Sheth is an educator, researcher, and entrepreneur. Prior to his joining the University of South Carolina as the founding director of the university-wide AI Institute, he was the LexisNexis Ohio Eminent Scholar and executive director of Ohio Center of Excellence in Knowledge-enabled Computing. He is a Fellow of IEEE, AAAI, and AAAS. He is among the highly cited computer scientists worldwide (h-index 104, >44,000 citations, listed among the top 100 in the world in 2018). He has founded three companies by licensing his university research outcomes, including the first Semantic Web company in 1999 that pioneered technology similar to what is found today in Google Semantic Search and Knowledge Graph.
Distinguished Lecture by
Prof Martin Banks,
on
Picture perception
Martin Banks’ lab works on picture perception, specifically on the perceptual bases and its importance in photography. This concept has three main photographic effects – wide angle distortion, depth compression/expansion and depth of field effects. All these are demonstrated with experiments conducted in his lab to test for the accommodations/adaptation the human visual system applies. Interesting experiments include determination of the preferred viewing distance to a display, blur as cues to absolute distance and how aperture is adjusted to reduce blur and increase the scale of the object.
November 13th, 2019, 2:00 PM
at
KRB Auditorium, IIIT Hyderabad, Gachibowli, Hyderabad.
About Honourable Speaker
Prof. Martin Banks teaches and conducts research in optometry and vision sciences at the University of California, Berkeley since 1985. His research focuses on human visual development and visual space perception and publications (over a 100) cover understanding infants visual perception, multi-modal sensory information processing and recently on evaluation of virtual display and augmented reality.
Distinguished Lecture by
Prof. Raghu Santanam,
on
AI and Future of Work
The advent of robotics, machine learning and big data analytics is disrupting jobs, industries and markets. The societal impacts of these rapid advances are exciting. But if machines can do what our colleagues are doing now, what happens to our companies? How does making an innovation in one product or service change what’s offered elsewhere?
September 24th, 2019, 4 PM
at
KRB Auditorium, IIIT Hyderabad, Gachibowli, Hyderabad.
About Honourable Speaker
Prof. Raghu Santanam is McCord Endowed Chair of Business, W. P. Carey School of Business, Arizona State University. His research interests are in Business Process Change, Health IT (EMR and PHR), Consumer Information Systems and Information Economics.
Distinguished Lecture by
Prof. Raymond M Klein,
Professor Emeritus, Dalhousie University, Canadaon
Applications of Experimental Psychology to Real World Problems
The talk will describe applied interests include attention deficits (in ADHD, autism, Parkinson’s patients, people with damage to the parietal lobe), the development of game-like tasks for repairing and assessing the networks of attention, safety (while driving, in the management of off-shore disasters, and pilot fatigue), using eye monitoring to draw conclusions about attention in every-day activities (reading, looking at art and looking at money).
August 14th, 2019, 2:00 PM
at
KRB Auditorium, IIIT-Hyderabad, Gachibowli
About Honourable Speaker
Dr. Klein is an internationally recognized expert on human attention and its relation to eye movements. His standing in the field was recognized by the Canadian Society for Brain, Behavior and Cognitive Science with the 2008 Donald O. Hebb Distinguished Contribution Award and his induction into the Royal Society of Canada.
Distinguished Lecture by
Prof. Takayuki Arai,
Sophia University, Japan
on
Introduction to Speech Science with Vocal-tract Models
The talk started with introduction to speech science and acoustic phonetics using different types of physical models. The lung model imitates the human respiratory system and produces glottal sounds. And several other types of vocal-tract models demonstrate vowel production. From straight and static through bent and dynamic, the style of the models varies greatly. Each static model has a unique vocal tract configuration which produces a single vowel, while the configuration of the dynamic models may be manipulated manually, producing multiple vowels. Then, extended models demonstrate different types of consonants: plosives, fricatives, nasals, and approximants. Moveable lips simulate bilabial sounds; a model with a nasal cavity simulates nasal consonants; and dynamic models simulate approximants. Some advanced topics were also discussed.
August 19th, 2019, 2:00 PM
at
KRB Auditorium, IIIT-Hyderabad, Gachibowli
About Honourable Speaker
Prof. Takayuki Arai obtained his Ph.D. degrees in Electrical Engineering from Sophia University, Tokyo in 1994. Prior to joining Sophia University he had worked in several places like Oregon Graduate Institute of Science and Technology, Portland; International Computer Science Institute, Berkeley and the Massachusetts Institute of Technology, Cambridge.His research interests include signal processing, acoustics, speech and hearing sciences, spoken language processing, and acoustic phonetics.
Distinguished Lecture by
Sandeep Gupta,
on
Overview of TensorFlow and its Ecosystem
An overview on TensorFlow and how it is impacting Machine Learning, an introduction to its APIs, new features, product direction, and resources to get started. Sandeep will also present other core and add-on projects that are part of the TensorFlow ecosystem. The talk will be followed by an open discussion and question/answer session
June 21st, 2019, 4:30 PM
at
Himalaya 105, IIIT Hyderabad, Gachibowli, Hyderabad.
About Honourable Speaker
Sandeep Gupta helps develop and drive the roadmap for TensorFlow (Google’s open-source library and framework for machine learning) for supporting machine learning applications and research. His current focus is on TensorFlow’s 2.0 release, improving TensorFlow’s usability and driving adoption in the community and enterprise, and on TensorFlow.js – a library bringing Machine Learning to JavaScript developers.
Distinguished Lecture by
Dr. Richard Socher,
on
The Natural Language Decathlon (DecaNLP)
Deep learning has significantly improved state-of-the-art performance for natural language processing (NLP) tasks, but each one is typically studied in isolation. The Natural Language Decathlon (decaNLP) is a new benchmark for studying general NLP models that can perform a variety of complex, natural language tasks. By requiring a single system to perform ten disparate natural language tasks, decaNLP offers a unique setting for multitask, transfer, and continual learning.
April 3rd, 2019, 11:00 AM
at
Himalaya 105, IIIT Hyderabad, Gachibowli, Hyderabad.
About Honourable Speaker
Dr. Richard Socher is a well-known researcher, developer of Salesforce Einstein and a propagator of democratizing Salesforce AI for customers. He obtained his Ph.D. from Stanford working on deep learning with Chris Manning and Andrew Ng and won the best Stanford CS Ph.D. thesis award. He was an adjunct professor at Stanford’s computer science department and founder and CEO/CTO of MetaMind which was acquired by Salesforce.
Distinguished Lecture by
Manoj Saxena,
Chairman of CognitiveScale
on
Ethics in AI Design
The current generation of Artificial Intelligence (AI) technologies is the most significant disruption in the evolution of computing. For AI technologies to advance benefit for humanity, we need to be able to define, measure and control the benefit we wish. We need to use an ethical design framework for the development and implementation of AI applications. The talk course will focus on an examination of ethical and policy issues raised by the increasing use of artificial intelligence (AI) by business and governments. It will take a cross-disciplinary approach to examining the need to balance innovation, ethics, and regulation of AI and discuss how business leaders, researchers and policy makers might address them.
March 18th, 2019, 5:00 PM
at
Himalaya 205, IIIT Hyderabad, Gachibowli.
About Honourable Speaker
Manoj Saxena is the Chairman of Cognitive Scale and a founding General Partner of The Entrepreneur’s Fund IV, overseeing investment and growth in the Cognitive and Cloud Computing space. He is a Special Advisor to IBM senior leadership where he focuses on operationalizing IBM’s $100m Watson Cloud Ecosystem Fund. He received the IBM Chairman’s award for Watson commercialization. He is a serial entrepreneur. Prior to IBM, he successfully founded, scaled, and sold two venture‐backed software companies Webify and Exterprise within a five year span.He holds two U.S. patents for web services technologies and 9 software patents. He currently serves on several boards including the Federal Reserve Bank of Dallas, San Antonio Branch, Communities In Schools, and the Saxena Family Foundation.
Distinguished Lecture by
Prof. Andrew Zisserman,
on
Principal architects of modern computer vision
The talk will describe self-supervised learning from videos with sound and will be divided his talk into two parts. The first will describe self-supervised learning from the visual stream alone, and will show the possibility of learning powerful embeddings for tasks such as facial attribute prediction and human action recognition. The second part will explore multi-modal self-supervised learning from video and audio. Zisserman will investigate two proxy loss functions, synchronization and correspondence, to link the modalities
January 2nd, 2019, 11:30 PM
at
KRB Auditorium, IIIT-Hyderabad, Gachibowli
About Honourable Speaker
Andrew Zisserman is one of the principal architects of modern computer vision. He is best known for his leading role during the 1990s in establishing the computational theory of multiple view reconstruction and the development of practical algorithms that are widely in use today. He is the only person to have been awarded the Marr Prize three times.
Distinguished Lecture by
Dr. P. Anandan,
on
Wadhwani Institute for Artificial Intelligence: Independent Not-For-Profit Research Institute for Social Good
WIAI is a new philanthropic effort by the Wadhwani brothers, Romesh Wadhwani and Sunil Wadhwani, entrepreneurs of Indian origin living in the US. Our mission is to do research in AI, ML, Data Science and related areas that will address societal challenges in a variety of domains including (but not limited to) Education, Health, Infrastructure, and Agriculture. We plan to build a strong team of researchers dedicated to this mission and plan to take an approach that is strongly driven by societal use cases keeping in mind the feasibility of deployment at scale as the ultimate measure of impact. We intend to conduct our research in collaboration with scientists from Academia and the Industry, and will be guided by Government agencies and Non-Governmental organizations who have domain and field experience. We will also work with and leverage the expertise our partners for testing our solutions and for deployment at scale. The Institute will be headquartered in India and will begin its work by addressing opportunities for research on societal impact in India.
Nov 2nd, 2017, 3.45 pm to 5.00 pm
at
Faculty Meeting Room, KRB, IIIT Hyderabad,
Gachibowli, Hyderabad.
About Honourable Speaker
P. Anandan has recently joined the newly formed Wadhwani Institute of Artificial Intelligence as its CEO. Previous to this Anandan was VP for Research at the Adobe Research Lab India (2016-2017) and before that a Distinguished Scientist and Managing Director at Microsoft Research (1997-2016).Anandan was the founding director of Microsoft Research India which he ran from 2005-2014. Prior to this, Anandan was researcher at Sarnoff corporation (1991-1997) and an Assistant Professor of Computer Science at Yale University (1987-1991). His primary research area is Computer vision where he is well known for his fundamental and lasting contributions to the problem of visual motion analysis.
Anandan received his PhD in Computer Science from University of Massachusetts, Amherst in 1987, a Masters in Computer Science from University of Nebraska, Lincoln in 1979 and his BTech in Electrical Engineering from IIT Madras, India in 1977. He is a distinguished alumnus of IIT Madras, and UMass, Amherst and is on the Nebraska Hall of Computing.
Distinguished Lecture by
Prof. Jim Foley,
on
Lecture on Computer Graphics Grand Challenge: How Real is Real Enough
A major challenge facing computer graphics researchers is to know how much realism is enough realism. It is tempting to always create the very most realistic images using the latest and greatest techniques. Technically, we can create many images that fool the eye. But is that the goal? Is it necessary? The nswer is “it depends” – on the purpose for which the graphics are being created – for entertainment, for training,for conveying specific information, for carrying out a task. Fool-the-eye realism is not always the right answer. Sometimes “less is more”; other times, “more is more”. In this talk, I categorize some of the purposes for which we create graphics images, survey experimental work, and approaches to help assess the relationship between image realism and image effectiveness, and discuss my own early realism study using the Shepherd-Metzler mental rotation task.The talk is illustrated with images and videos.
October 06th, 2017, 4.00 pm to 5.00 pm
at
Himalaya # 105, IIIT Hyderabad, Gachibowli,
Hyderabad.
About Honourable Speaker
Jim Foley is a Professor in the College of Computing at Georgia Tech. He is a member of the United States National Academy of Engineering, and a Fellow of AAAS, ACM and IEEE. He has received two lifetime achievement awards, one in computer graphics (the Coons award) from ACM/SIGGRAPH and another in human-computer interaction from ACM/SIGCHI.
Foley is co-author of five books: Fundamentals of Interactive Computer Graphics, Three editions of Computer Graphics Principles and Practice, and Introduction to Computer Graphics.
He joined Georgia Tech in 1991 as the founding director of the Graphics, Visualization and Usability Center. In 1996, US News and World Report ranked the Center number one for graduate computer science work in graphics and user interaction. From 1996-99, he was first Director of MERL - Mitsubishi Electric Research Laboratory and them CEO and Chairman of Mitsubishi Electric Information Technology Center America, responsible for Mitsubishi's corporate R&D in North America.
After returning to Georgia Tech, he was chairman (2001-2005) of the Computing Research Association - an organization of over 250 computer science and computer engineering departments, professional societies and research labs. From 2008 to 2011 he served as Vice President of ACM’s Special Interest Group for Graphics (SIGGRAPH).
Distinguished Lecture by
Prof. Jitendra Malik,
on
Deep Visual Understanding from Deep Learning
Deep learning and neural networks coupled with high-performance computing and big data have led to remarkable advances in computer vision. For example, we now have a good capability to detect and localize people or objects. But we are still quite short of “visual understanding”. I’ll sketch some of our recent progress towards this grand goal. One is to explore the role of feedback or recurrence in visual processing. Another is to unify geometric and semantic reasoning for understanding the 3D structure of a scene. Most importantly, vision in a biological setting, and for many robotics applications, is not an end in itself but to guide manipulation and locomotion. I will show results on learning to perform manipulation tasks by experimentation, as well as on a cognitive mapping and planning architecture for mobile robotics.
Sep 16th, 2017, 4.00 pm to 5.00 pm
at
Himalaya # 105, IIIT Hyderabad, Gachibowli,
Hyderabad.
About Honourable Speaker
Jitendra Malik is Arthur J. Chick Professor of Electrical Engineering and Computer Science at UC Berkeley. Over the past 30 years, Prof. Malik's research group has worked on many different topics in computer vision. Several well-known concepts and algorithms arose in this research, such as anisotropic diffusion, normalized cuts, high dynamic range imaging, shape contexts and R-CNN. Prof. Malik received the Distinguished Researcher in Computer Vision Award from IEEE PAMI-TC, the K.S. Fu Prize from the International Association of Pattern Recognition, and the Allen Newell award from ACM and AAAI. He has been elected to the National Academy of Sciences, the National Academy of Engineering and the American Academy of Arts and Sciences. He earned a B.Tech in Electrical Engineering from Indian Institute of Technology, Kanpur in 1980 and a PhD in Computer Science from Stanford University in 1985.
Distinguished Lecture by
Prof. Jaime Carbonell,
on
Advances in Machine Learning and Big Data with Industrial Applications
The advent of modern Artificial Intelligence, powered by Machine Learning and Big Data, is already having a large impact on the IT industry and is spreading to other sectors of the economy. However, not all data are equally useful; for instance data with both detailed observations (inputs) and known outcomes (desired and undesired outputs) is most useful for predictive tasks, but often data is noisy, incomplete and outcomes are at least partially unknown. New machine learning methods are needed to cope with such data, complementing the current wave of deep learning. The presentation will address proactive learning, multi-task learning, and their applications.
Sep 1st, 2017, 4.00 pm
at
Himalaya 105, IIIT Hyderabad, Gachibowli
About Honourable Speaker
University Professor and Allan Newell Professor of Computer Science Jaime G. Carbonell joined the Carnegie Mellon community as an assistant professor of computer science in 1979, and has gone on to become a widely recognized authority in machine translation, natural language processing and machine learning. Carbonell has invented a number of well-known algorithms and methods during his career, including proactive machine learning and maximal marginal relevance for information retrieval. His research has resulted in or contributed to a number of commercial enterprises, including Carnegie Speech, Carnegie Group and Dynamix Technologies.
In addition to his work on machine learning and translation, Carbonell also investigates computational proteomics and biolinguistics — fields that take computational tools used for analyzing language and adapt them to understanding biological information encoded in protein structures. This process leads to increased knowledge of protein-protein interactions and molecular signaling processes.
Carbonell's career has had an enormous impact on both Carnegie Mellon and the School of Computer Science. He created the university's Ph.D. program in language technologies, and is co-creator of the Universal Library and its Million Book Project. He founded CMU's Center for Machine Translation in 1986 and led its transformation in 1996 into the Language Technologies Institute, which he currently directs. He has advised more than 40 Ph.D. students and authored more than 300 research papers.
Before joining the Carnegie Mellon faculty, Carbonell earned bachelor's degrees in mathematics and physics at the Massachusetts Institute of Technology, and his master's degree and Ph.D. in computer science at Yale University.
Distinguished Lecture by
Dr. P. Anandan,
VP for Research, Adobe
Systems
on
How Data Science, Machine Learning, and AI are Transforming the Consumer Experience
During the last two decades, the experience of consumers has been undergoing a fundamental and dramatic transformation – giving a rich variety of informed choices, online shopping, consumption of news and entertainment on the go, and personalized shopping experiences. All of this has been powered by the massive amounts of data that is continuously being collected and the application of machine learning, data science and AI techniques to it.
Adobe is a leader in Digital Marketing and is the leading provider of solutions to enterprises that are serving customers both in the B2B and B2C space. In this talk, Dr. Anandan will outline the current state of the industry and the technology that is behind it, how Data Science and Machine Learning are gradually beginning to transform the experiences of the consumer as well as the marketer. He will also speculate on how recent developments in Artificial Intelligence will lead to deep personalization and richer experiences for the consumer as well as more powerful and tailored end-to-end capabilities for the marketer.
April 11th, 2017, 3:30 p.m.
at
Himalaya 105, IIIT Hyderabad, Gachibowli
About Honourable Speaker
Dr. P. Anandan is responsible for developing research strategy for Adobe, especially in the Artificial Intelligence and Machine Learning as applied to Digital Marketing and for leading the Adobe India Research lab.
Prior to Adobe, Dr. Anandan was a Distinguished Scientist and Managing Director of Microsoft Research Outreach. Previously, he was Distinguished Scientist and Managing Director at Microsoft Research India, which he founded in December 2004 in Bangaluru. He joined Microsoft Research in Redmond, Washington in 1997, where he founded and built the Interactive Visual Media group. Before joining Microsoft, Dr. Anandan was the Head of Video Information Processing research at Sarnoff Corporation from 1991-1997. He was an Assistant Professor of Computer Science at Yale University from 1987-1991.
Dr. Anandan holds an undergraduate degree in electrical engineering from the Indian Institute of Technology Madras, a Master of Science in Computer Science from the University of Nebraska, Lincoln, and a Ph.D. in Computer Science from the University of Massachusetts, Amherst. He is a Distinguished Alumnus of the University of Massachusetts as well as of IIT Madras, and has been inducted to the Nebraska Hall of Computing. During a research career spanning over three decades, Dr. Anandan has also done pioneering research in Computer Vision, specifically in the area of Visual Motion Analysis and Optical Flow Estimation.
Distinguished Lecture by
Dr. Jaideep Ganguly,
Amazon, Hyderabad
on
Recurrent Neural Networks in Sequence Learning for Dialog Systems
In this talk, we review architectures, algorithms, results and distill intuitions that have guided this largely heuristic and empirical field. We go over historic perspectives and qualitative arguments in Neural Networks. The concept of recurrent nets is introduced, the mathematical basis, and the challenges in convergence. We then discuss LSTM, its effectiveness and, specifically, its application to Dialog Systems. I present Amazon achievements (videos) in multiple areas. Finally, and most importantly, we discuss some open problems that require research. Industry is at the forefront in actively using the latest machine learning techniques for everyday tasks.
November 16th,2016, 3:45pm
at
Himalaya 105, IIIT Hyderabad, Gachibowli
About Honourable Speaker
Dr. Jaideep Ganguly is Director of Software Development, Seller Experience Technology in Amazon and is based in Hyderabad. He has software development teams located at Hyderabad, New Delhi and Detroit that report into him. At Amazon, Dr. Jaideep’s team is responsible for building massively scalable and highly reliable software robots that power automation and dialog systems. He has over 25 years of experience in leading large scale software development. Dr. Jaideep holds the degrees of Doctor of Science and Master of Science, both from MIT and an undergraduate degree from IIT - Kharagpur.
Distinguished Lecture by
Prof. Manuela Veloso,
Carnegie Mellon
University
on
Symbiotic Robot Autonomy and Learning
We research on autonomous mobile robots with a seamless integration of perception, cognition, and action. In this talk, I will first introduce our CoBot service robots and their novel localization and symbiotic autonomy, which enable them to consistently move in our buildings, now for more than 1,000km. I will then introduce the CoBot robots as novel mobile data collectors of vital information of our buildings, and present their data representation, their active data gathering algorithm, and the particular use of the gathered WiFi data by CoBot. I will further present an overview of multiple human-robot interaction contributions, and detail the use and planning for language-based complex commands. I will then conclude with some philosophical and technical points on my view on the future of autonomous robots in our environments.
The presented work is joint with my CORAL research group, and in particular refers to the past PhD theses of Joydeep Biswas, Stephanie Rosenthal, and Richard Wang, and recent work of Vittorio Perera.
August 22nd, 2016, 3:30pm
at
Himalaya 105, IIIT Hyderabad, Gachibowli
About Honourable Speaker
Manuela M Veloso is Herbert A Simon University Professor and the Head of the Machine Learning Department, in the School of Computer Science at Carnegie Mellon University. She researches in Artificial Intelligence and Robotics. She founded and directs the CORAL research laboratory, for the study of autonomous agents that Collaborate, Observe, Reason, Act, and Learn, www.cs.cmu.edu/~coral. Professor Veloso is IEEE Fellow, AAAS Fellow, AAAI Fellow, and the past President of AAAI and RoboCup. Professor Veloso and her students have worked with a variety of autonomous robots, including mobile service robots and soccer robots. See www.cs.cmu.edu/~mmv for more.
Prof Veloso is a member of the Advisory Board of KCIS.