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X-WR-CALDESC:Events for Computer Science and Engineering
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TZID:Asia/Kolkata
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DTSTART:20250101T000000
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DTSTART;TZID=Asia/Kolkata:20250605T100000
DTEND;TZID=Asia/Kolkata:20250605T110000
DTSTAMP:20260924T012335
CREATED:20250602T072215Z
LAST-MODIFIED:20250602T094001Z
UID:1633-1749117600-1749121200@homecse.iitd.ac.in
SUMMARY:Multimodal Learning in 3D environments: Perception\, and Simulation
DESCRIPTION:Speaker: Dr. Arun Balajee Vasudevan is currently a Research Scientist at Amazon \nAbstract: \nAutonomous robots have several potential applications such as virtual assistants\, VR/AR\, gaming\, self-driving technologies\, city planning and others. To achieve autonomy\, a robot needs to see and hear the environment\, before it can converse or navigate favorably to perform a human-desired task. Precisely\, scene understanding begins with building 3D geometry\, decoding semantics\, understanding surround objects/humans\, and planning and actions. My research talk addresses these fundamental challenges independently under two broad themes: understanding geometry and multimodal perception & data-driven simulation and navigation. \nUnder geometry and perception\, I introduce the usage of several multimodalities such as the user’s gaze\, visual sensors such as cameras or range sensors (e.g. Kinect)\, and speech/language instructions from human referrals for robot perception tasks. Further\, I delve deep into the investigation of the audio sensing modality for the task using binaural sound microphones. Secondly\, regarding the geometry\, my talk addresses one of my ongoing works about the construction of digital twins of the real world with 4D reconstruction of dynamic scenes from ground visuals of a robot. \nUnder the theme of Data-driven simulation and robot navigation. Following perception\, robots must navigate and take meaningful actions in the world. This involves broadly two aspects: wayfinding and motion planning. Earlier works address wayfinding based on directional instructions\, overlooking human aspects. I briefly talk about a new paradigm that integrates principles from cognitive science with learning-based methods to tackle the challenge of language-based wayfinding for robots in real-world outdoor environments. The second aspect is motion planning for which I propose the learning of driver behavior models for MPC-based planners to build data-driven simulators. \nLong term\, I envision to bridge the above two themes to build multimodal digital twins simulators of the real-world. This potentially helps in training and testing of planners\, VR/AR setups\, gaming\, and others. Lastly\, I also cover my future research plan in the talk. \nShort Bio: \nArun Balajee Vasudevan is currently a Research Scientist at Amazon. Previously\, he was a postdoctoral researcher at Carnegie Mellon University under Prof. Deva Ramanan till March 2025. His core research interest is in Computer Vision and Multimodal Learning. He has works in multimodal (vision\, language and sounds) perception and navigation\, 3D/4D reconstruction\, Motion Planning and improving Foundational models. He published papers predominantly in vision and machine learning conferences/journals such as CVPR\, ECCV\, ICML\, IJCV\, TPAMI\, and others. He defended his PhD under Prof. Luc Van Gool at ETH Zurich. He received his MSc in Computer Science from EPFL in 2016 and an undergraduate degree in Electrical Engineering from the Indian Institute of Technology Jodhpur in the year 2014.
URL:https://homecse.iitd.ac.in/event/multimodal-learning-in-3d-environments-perception-and-simulation/
CATEGORIES:Seminars
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DTSTART;TZID=Asia/Kolkata:20250609T120000
DTEND;TZID=Asia/Kolkata:20250609T130000
DTSTAMP:20260924T012335
CREATED:20250604T065636Z
LAST-MODIFIED:20250604T065657Z
UID:1639-1749470400-1749474000@homecse.iitd.ac.in
SUMMARY:Designing advanced cryptographic primitives in distributed settings
DESCRIPTION:Speaker: Dr. Anshu Yadav\, Postdoctoral Researcher\, Institute of Science and Technology\, Austria \nAbstract: In today’s world\, the rapid advancement of technology has led to the generation of vast amounts of sensitive data\, which must be accessed in a secure and controlled manner to facilitate research across various domains. Often this data\, associated with a single logical entity\, is generated in a distributed manner\, yet must be protected with the same level of security as if it were produced by a single source. Furthermore\, distributing authority among multiple entities is essential to avoid a single point of security failure. These are natural\, yet complex challenges in modern cryptography. My research focuses on exploring how advanced cryptographic primitives can provide effective solutions to such problems. In this talk\, I will begin with a brief overview of my research interests and profile. I will then focus on the themes discussed above. In particular\, I will briefly talk about a result on multi-input attribute based encryption which is a generalization of attribute-based encryption (ABE) – a novel encryption paradigm enabling expressive access control on encrypted data. In ABE\, a message m is encrypted under an attribute x\, and decryption keys are associated with a policy 𝑓. Decryption is possible if and only if 𝑓(x)=1\, unlike traditional public key encryption scheme where a single key can decrypt all ciphertexts. In the multi-input setting\, data is generated by k non-interacting parties\, with each party contributing an input (x_i\, m_i)\, so that x=(x_1\,…\,x_k) and m=(m_1\,…\,m_k). The function 𝑓 is now a k-ary predicate. The goal is for each party to independently encrypt their data as ct_1\,…\,ct_k\, and for a decryption algorithm with key sk_f to recover (m_1\,…\,m_k) if and only if 𝑓(x_1\,…\,x_k)=1. We formally defined the notion of multi-input ABE (k-ABE) and presented constructions for different k under different cryptographic hardness assumptions. I will describe the key challenges in designing cryptographic schemes in the multi-input setting and how our work addresses these challenges. If time permits\, I will also briefly talk about my work in threshold cryptography – a very useful and active field of cryptography with advanced practical applications in distributed environments (e.g.\, block chains\, distributed key generation\, etc.). In threshold cryptography\, a privileged operations—such as ‘signing’ in digital signature scheme or ‘decryption’ in an encryption scheme—is distributed among n parties\, ensuring that at least a threshold t of them are required to perform the operation. In this area\, my research has mostly focussed on threshold signatures\, where we improve the security of post-quantum threshold signature scheme. Finally\, I will conclude the talk with a discussion of my future research directions\, including open problems in the areas discussed above.
URL:https://homecse.iitd.ac.in/event/designing-advanced-cryptographic-primitives-in-distributed-settings/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
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