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X-ORIGINAL-URL:https://ee.iisc.ac.in
X-WR-CALDESC:Events for EE
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TZID:Asia/Kolkata
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TZOFFSETFROM:+0530
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DTSTART:20230101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230803T150000
DTEND;TZID=Asia/Kolkata:20230803T170000
DTSTAMP:20260528T095747
CREATED:20230802T100042Z
LAST-MODIFIED:20230802T100130Z
UID:240956-1691074800-1691082000@ee.iisc.ac.in
SUMMARY:Technical Talk by Dr. Amristanshu Pandey\, University of Vermont\, USA
DESCRIPTION:IEEE PES Student Branch Chapter\, IISc has organized a technical talk on 3rd August 2023 at 3 PM IST. Please find the talk details as below. \n\n\n\n\n\nTitle: Homotopy-based Circuit-theoretic Optimizations for Power Grids \n\n\n\n\n\nSpeaker: Dr. Amritanshu Pandey\, University of Vermont\, USA \n\n\n\n\n\nDate and Time: 3rd August 2023\, 3 PM ISTVenue: MMCR Electrical Engineering Department\, IISc\, Bengaluru.  \n\n\n\n\n\nAbstract: Optimizations are at the center of many power grid analyses. With rapid decarbonization and electrification\, the scale and complexity of these optimizations are increasing. Current state-of-the-art tools for nonconvex optimization are not always robust at solving these emerging power grid problems. In this talk\, I will discuss a novel domain-focused circuit-theoretic optimization method for power grids. In this approach\, the first-order optimality conditions for an optimization problem are mapped into a set of equivalent circuits\, the response for which represents a problem’s stationary point. As these equivalent circuits are large and highly nonlinear\, we developed and used a novel homotopy method: Incremental Model Building (IMB). I will cover this homotopy in this talk and show that this method can also be extended to optimize for discrete control variables in the grid. I will conclude the talk by showing pertinent results and comparisons against a state-of-the-art method that won the recent ARPA-E grid optimization challenge. \n\n\n\n\n\nSpeaker Bio: Amrit Pandey is an Assistant Professor in the Electrical and Biomedical department at the University of Vermont with a courtesy appointment in the Electric and Computer Engineering and Engineering and Public Policy departments at Carnegie Mellon University. His overarching research goal is to develop electric energy system technologies to help combat climate change while modernizing the underlying system. In the past\, he and his team developed a novel circuit-theoretic simulation and optimization framework for power grids. The project culminated in a new grid analytics tool: Simulation of Unified Grid Analysis and Renewables (SUGAR)\, which Pearl Street Technologies\, Inc. has since commercialized. This work has won several best paper awards\, including two best-of-the-best paper awards at IEEE PES General Meeting in 2017 and 2021. His current research focuses on developing computational methods that address problems in the space of large-scale grid simulation and optimization\, grid cybersecurity\, and energy inequity.
URL:https://ee.iisc.ac.in/event/technical-talk-by-dr-amristanshu-pandey-university-of-vermont-usa/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230803T153000
DTEND;TZID=Asia/Kolkata:20230803T173000
DTSTAMP:20260528T095747
CREATED:20230802T112318Z
LAST-MODIFIED:20230802T112938Z
UID:240963-1691076600-1691083800@ee.iisc.ac.in
SUMMARY:Orientation Program 2023
DESCRIPTION:Dear All \n  A warm welcome to all the new Masters and Research students! \nThe department of EE is flourishing with a broad spectrum of research activities and multiple master’s programs.  Being a proud member of the department\, you may be eager to know more about the department and the courses. \nFor this\, a Welcome/Orientation program is planned for the 3rd (Thursday) at 3:30 pm. The venue for the program is classroom 308 on the second floor. It will start with a brief history and current activities. Followed by a presentation by the DCC Chair about the course requirement for the masters and research students.  Then we wish to know about you!   \nCoffee & Tea will be served at the end. \n Please attend the event without fail.
URL:https://ee.iisc.ac.in/event/orientation-program-for-new-students/
LOCATION:B308\,2nd floor\, EE Dept.
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230808T110000
DTEND;TZID=Asia/Kolkata:20230808T120000
DTSTAMP:20260528T095747
CREATED:20230804T091124Z
LAST-MODIFIED:20230804T091231Z
UID:240974-1691492400-1691496000@ee.iisc.ac.in
SUMMARY:PhD Colloquium - 8 August: Resource-Aware State-Triggered Control of Networked Control Systems
DESCRIPTION:Speaker: Anusree RajanSupervisor: Pavankumar TallapragadaDate and Time: Tuesday\, 8 August 2023\, at 11amVenue: MMCR (C241)\, EE DepartmentTitle: Resource-Aware State-Triggered Control of Networked Control SystemsAbstract:Networked control systems are very popular nowadays\, with different fields of applications such as environmental monitoring\, industrial automation\, military surveillance\, and disaster management. Event- or self-triggered control is a commonly used control method in the field of networked control systems owing to its advantage of efficient utilization of resources while simultaneously achieving control objectives. In these control methods\, the communication times are opportunistic and implicitly determined by a triggering rule. Thus\, understanding inter-event times generated by a triggering rule is necessary for higher level planning and scheduling for control over shared or constrained resources as well as for analytical quantification of the usage of communication or other resources compared to a time-triggered controller.In the first part of this thesis\, we provide a systematic way to analyze the evolution of inter-event times in planar linear systems\, under a general class of scale-invariant event triggering rules. We provide a sufficient condition for the convergence or non-convergence of inter-event times to a steady state value. We also provide a sufficient condition for the asymptotic average inter-event time to be a constant for all non-zero initial states of the system. Then\, under a special case\, we comment on the asymptotic behaviour of the inter-event times\, including on whether the inter-event times converge to a periodic sequence. Later\, we extend our analysis of inter-event times to linear systems under region-based self-triggered control. In this control method\, the state space is partitioned into a finite number of conic regions and each region is associated with a fixed inter-event time. We provide several necessary conditions and sufficient conditions for the local convergence of inter-event times to a constant or to a given periodic sequence.In the second part of this thesis\, we consider a design problem. Most of the existing event- or self-triggered controllers are designed using sampled-data zero-order-hold (ZOH) control input. However\, many communication protocols used in networked control systems\, such as TCP and UDP\, have a minimum packet size. So\, ZOH control may lead to under-utilization of each packet while also increasing the number of communication instances. On the other hand\, use of non-ZOH control leads to better utilization of the minimum payload of each packet while also reducing the overall number of communication instances. With these motivations\, we propose a new control method called event-triggered parametrized control (ETPC). In this control method\, between two consecutive events\, each control input to the plant is a linear combination of a set of linearly independent scalar functions. At each event\, the coefficients of the parameterized control input are chosen to minimize the error in approximating a continuous time control signal and then they are communicated to the actuator. We\, first\, showcase this method by focusing on the specific problem of stabilization of linear systems. We design two event-triggering rules that guarantee global asymptotic stability of the origin of the closed loop system under some conditions on the model uncertainty. Later\, we use a similar idea to propose an event-triggered polynomial control method for trajectory tracking of unicycle robots. We design an event-triggered parametrized controller for trajectory tracking by a unicycle robot and provide guarantees for uniform ultimate boundedness of the tracking error.Due to time limitations\, the colloquium will focus on the first part of the thesis.——————————- All are Welcome —————————-
URL:https://ee.iisc.ac.in/event/phd-colloquium-8-august-resource-aware-state-triggered-control-of-networked-control-systems/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230811T150000
DTEND;TZID=Asia/Kolkata:20230811T170000
DTSTAMP:20260528T095747
CREATED:20230809T114701Z
LAST-MODIFIED:20230814T084627Z
UID:240977-1691766000-1691773200@ee.iisc.ac.in
SUMMARY:Ph.D. Thesis Oral Defense of Mr. Anoop C. S.: Automatic speech recognition for low-resource Indian languages
DESCRIPTION:Name of the student:  ANOOP C. S.\n\nAdvisor: Prof. A. G. Ramakrishnan & Dr. G. N. Rathna\n\nExternal examiner: Prof. Umesh S\, Dept of EE\, IIT Madras\n\nDate and Time: 11 August 2023 (Friday) 3:00 PM\n\nVenue (hybrid): MMCR\, C 241\, First Floor\, Dept. of EE\n                                                                AND\n\nMicrosoft Teams meeting link: \n\n\n\n\n\n\n\n\n\nJoin conversation\nteams.microsoft.com\n\n\n\n\n\n\n\n\n\nTITLE: Automatic speech recognition for low-resource Indian languages\n\nBuilding good models for automatic speech recognition (ASR) requires large amounts of annotated speech data. Most Indian languages are low-resourced and lack enough training data to build robust and efficient ASR systems. However\, many have an overlapping phoneme set and a strong correspondence between their character sets and pronunciations. This thesis exploits such similarities among the Indian languages to improve speech recognition in low-resource settings.\n\nSignificant contributions of the thesis:\n\nExploiting the pronunciation similarities across multiple Indian languages through shared label sets:\n\nThe use of a common set of tokens is proposed across multiple Indian languages and their performance analyzed in mono and multilingual settings.\n\n\nIt is found that the Sanskrit Library Phonetic Encoding (SLP1) tokens\, which exploit the pronunciation-based structuring of character Unicodes in Indian languages\, perform better than other grapheme-to-phoneme (G2P) based tokens in monolingual ASR settings.\nSyllable-based sub-words perform better than the character-based token units in monolingual speech recognition. However\, character-based SLP1 tokens perform better in cross-lingual transfer.\n\n\nStrategies for improving the performance of ASR systems in low-resource scenarios (target languages) exploiting the annotated data from high-resource languages (source languages):\n\nThree different low-resource settings have been studied:\n\nA) Labelled audio data is not available in the target language. Only a limited amount of unlabeled data is available. Unsupervised domain adaptation (UDA) schemes popular in image classification problems have been adopted to tackle this case.\n\n\nThe adversarial training with gradient reversal layers (GRL) and domain separation networks (DSN) provide word error rate (WER) improvements of 6.71% and 7.32%\, respectively\, on Sanskrit compared to a baseline hybrid DNN-HMM system trained on Hindi.\nThe UDA models outperform multi-task training with language recognition as the auxiliary task.\nSelection of the source language is critical in UDA systems.\n\n\nB) Target language has only a small amount of labeled speech data and has some amount of text data to build language models. In this case\, available data in high-resource languages is used through shared label sets to build unified acoustic (AM) and language models (LM).\n\n\nUnified language-agnostic AM + LM performs better than monolingual AM + LM in cases where (a) only limited speech data is available for training the acoustic models and (b) the test speech data is from domains different from that used in training.\nIn general\, multilingual AM + monolingual LM performs the best.\n\n\nC) There are N target languages with limited training data and several source languages with large training sets. In this case\, the usefulness of model-agnostic meta-learning (MAML) pre-training is established for Indian languages and improvements are proposed with text-similarity-based loss-weightings.\n\n\nMAML beats joint multilingual pretraining by an average of 5.4% in CER and 20.3% in WER.\nWith just 25% of the data\, MAML performance matches joint multilingual models trained on the whole target data.\nSimilarity with the source languages impacts the target language’s ASR performance.\nText-similarity measured through cosine and Mahalanobis distances is used to weigh the losses during MAML pretraining. It yields a mean absolute improvement of 1% in WER.\n\n\n\n                                                                                                              ALL ARE WELCOME ONLINE!\n Meeting Recording\n\n\n\nhttps://ee.iisc.ac.in/wp-content/uploads/2023/08/Anoop-PhD-Viva-20230811_150431-Meeting-Recording_Cut.mp4
URL:https://ee.iisc.ac.in/event/ph-d-thesis-oral-defense-of-mr-anoop-c-s-automatic-speech-recognition-for-low-resource-indian-languages/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230817T160000
DTEND;TZID=Asia/Kolkata:20230817T173000
DTSTAMP:20260528T095747
CREATED:20230814T111017Z
LAST-MODIFIED:20230814T111017Z
UID:240995-1692288000-1692293400@ee.iisc.ac.in
SUMMARY:[Talk] Prof Nando Ochoa of University of Melbourne 17th Aug 4 PM MMCR EE
DESCRIPTION:Title: “Smart Meter-Driven Approaches for PV-Rich Low Voltage Network Modelling\, Operation and Planning”\n \nSpeaker: Prof Nando Ochoa Pizzali\n \nAffiliation: University of Melbourne\, Australia\n \nVenue: MMCR\, EE Dept\n\nDate: 17th Aug 2023\n\nTime: 4:00 PM\n \nAbstract: Residential solar PV is installed behind the meter of mainly single-phase customers connected to three-phase low voltage (LV) feeders (e.g.\, 400V line-to-line). This means that for distribution companies to adequately quantify the impacts from reverse power flows due to excess solar PV generation\, the corresponding electrical models are required. These models are critical when calculating voltages given the non-linear and unbalance nature of LV feeders. However\, the task of producing electrical models of thousands of LV feeders is already a significant challenge for distribution companies around the world\, which\, in turn\, makes the operation and planning of PV-rich LV networks even more challenging. It is in this context that the exploitation of historical smart meter data can not only help distribution companies with their modelling tasks but also provide radical alternatives to how they operate and plan future PV-rich LV networks.\n\nThis talk presents and discusses the findings of three advanced smart meter-driven approaches using realistic case studies from Victoria\, Australia. The first enhances LV models. Using simplified three-phase voltage drop equations and multiple linear regression\, it is able to estimate three-phase and single-phase line impedances which\, in turn\, allows for the quick and accurate calculation of customer voltages for operational purposes. The second\, a more radical approach\, goes model-free. It demonstrates that neural networks can be trained to capture the physics of three-phase LV feeders with dozens of single-phase customers; making it possible to have fast and accurate voltage calculations. The last one\, from a planning perspective\, also demonstrates that regression techniques and data from early solar PV penetrations can be used to quickly estimate the hosting capacity of LV networks without the need for complex and detailed network studies.\n\n\nBio:  Prof Nando is a Professor of Smart Grids and Power Systems at The University of Melbourne\, Australia\, and Chief Scientist & Co-Founder at VoltMind. He is an IEEE PES Distinguished Lecturer\, an Editorial Board Member of the IEEE Power and Energy Magazine\, and an IEEE Senior Member. Previously\, from 2011 to 2021\, he was full and part-time with The University of Manchester\, UK. From 2007 to 2010 he was a Research Fellow in Energy Systems at the University of Edinburgh\, UK. In 2010\, he also undertook an industrial secondment with the Edinburgh-based company Psymetrix Ltd (part of GE). He hold a Bachelor’s degree in Mechanical and Electrical Engineering received from UNI (Peru)\, and a Research MSc and a PhD in Electrical Power Engineering\, both received from UNESP Ilha Solteira (Brazil).
URL:https://ee.iisc.ac.in/event/talk-prof-nando-ochoa-of-university-of-melbourne-17th-aug-4-pm-mmcr-ee/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230818T160000
DTEND;TZID=Asia/Kolkata:20230818T173000
DTSTAMP:20260528T095747
CREATED:20230810T060333Z
LAST-MODIFIED:20230810T060446Z
UID:240982-1692374400-1692379800@ee.iisc.ac.in
SUMMARY:[Talk]: Prof Ramakrishna Gokaraju University of Saskatchewan\, Canada
DESCRIPTION:Talk Title:  Future Clean Power and Energy Systems: Co-generation with New Nuclear Based Small Modular Reactors (SMRs) and Renewable Energy for Electricity and Energy Applications\n\nSpeaker:\n\nProf Ramakrishna Gokaraju\, PhD\, PEng \nProfessor\, Department of Electrical & Computer Engineering\nAssociate Dean\, Graduate Studies & Special Projects\, College of Engineering\nUniversity of Saskatchewan\, Canada\n\n\nDate: 18th August 2023\, 4 pm\n\n\nVenue: MMCR\, EE Dept\, IISc\n\n\nAbstract: \nSmall modular reactors (SMRs)—a fast-emerging nuclear power plant technology—and renewables hold significant promise for the development of future clean energy systems. They are suitable for large grids as well as remote load centers and offer load following and frequency response capabilities. This talk will first provide a background of this technology and recent developments related to this technology. Followed by this it will describe a dynamic model of an integral pressurized water reactor (iPWR)-type SMR and studies assessing the contribution of the reactor to the electrical side dynamics. SMRs with their faster response rates\, along with intermittent renewable energy sources (RESs) could be effectively used to develop sustainable clean energy systems. The talk will also describe a dynamic simulation model developed in our lab showing how SMRs along with renewable energy could be used for electricity and district heating.\n\nBiography:\nProf. Ramakrishna Gokaraju received his Bachelor of Engineering degree (with Distinction) in Electrical and Electronics Engineering from the National Institute of Technology\, Trichy\, India in April 1992. He received the M.Sc. and Ph.D. degrees in electrical and computer engineering from the University of Calgary\, Canada\, in 1996 and 2000\, respectively. He worked with IBM Toronto Lab from 2000-‘22. Prof. Gokaraju joined the Electrical & Computer Engineering Department\, University of Saskatchewan in 2003 and is a professor in the department of electrical & computer engineering. He is also currently the Associate Dean of Graduate Studies and Special Projects in the College of Engineering. His current research works are on power system protection\, smart grids and nuclear-based “SMRs” for power and energy applications. He currently serves the Natural Sciences and Engineering Council of Canada (NSERC) Evaluation Group in Electrical and Computer Engineering. His research is funded by the NSERC Discovery Grant and the Canadian Nuclear Safety Commission (CNSC).
URL:https://ee.iisc.ac.in/event/talk-prof-ramakrishna-gokaraju-university-of-saskatchewan-canada/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230823T110000
DTEND;TZID=Asia/Kolkata:20230823T130000
DTSTAMP:20260528T095747
CREATED:20230818T102510Z
LAST-MODIFIED:20230818T102510Z
UID:240997-1692788400-1692795600@ee.iisc.ac.in
SUMMARY:EE PhD Colloquium on Imaging Inverse problems
DESCRIPTION:Title : Improved Derivative based Regularizations for Imaging Inverse problems \nStudent : Manu GhulyaniAdvisor : Prof. Muthuvel Arigovindan \nDate and Time:   23.08.2023 (Wednesday)\,  11 am. \nVenue :  MMCR\, Department of Electrical Engineering \nAbstract: \nImages undergo degradation during the capturing process due to physical limitations inherent to the capturing devices. Addressing this degradation and recovering high-quality images constitute the image recovery problem\, a crucial concern with diverse applications across various fields such as biology\, astronomy\, and medicine. The enhancement of captured image resolution significantly influences these disciplines. Examples of this problem include tasks like reconstructing computed tomography images\, magnetic resonance imaging\, image deconvolution\, and microscopic image reconstruction. \nImage recovery is frequently approached using regularization techniques\, with derivative-based regularizations being popular due to their ability to exploit image smoothness\, yielding interpretable results devoid of introduced artifacts. Total Variation regularization (TV)\, proposed by Rudin\, Osher\, and Fatemi\, is a seminal approach for image recovery. TV involves the norm of the image’s gradient\, aggregated over all pixel locations. As TV encourages minimal values in the derivative norm\, it leads to piece-wise constant solutions\, resulting in what is known as the “staircase effect.” To mitigate this effect\, the Hessian Schatten norm regularization (HSN) employs second-order derivatives\, represented by the pth norm of eigenvalues in the image hessian vector\, summed across all pixels. HSN demonstrates superior structure-preserving properties compared to TV. However\, HSN solutions tend to be overly smoothed. To address this\, we introduce a non-convex shrinkage penalty applied to the Hessian’s eigenvalues\, deviating from the convex lp norm. While the analytical form of this penalty was unknown\, we derived the algorithm using proximal operations. We established that the proposed regularization adhered to restricted proximal regularity\, ensuring the algorithm’s convergence. The images recovered by this regularization were sharper than the convex counterparts. \nIn the subsequent work\, we extend the concept of the Hessian-Schatten norm. By encompassing Schatten norms of the Hessian and introducing a smoothness constraint\, we broaden the scope of Hessian Schatten norm. The resulting regularization can be derived as a Lagrange dual of the Hessian Schatten norm\, akin to the total generalized variation. Furthermore\, we present an efficient variable splitting scheme for solving image restoration challenges. \nTotal Generalized Variation (TGV) represents an important generalization of Total Variation. TGV involves multiple orders of derivatives\, with higher-order TGV leading to improved recovered image quality. This enhancement has been validated through numerical experiments in image denoising. Consequently\, a demand arises for an algorithm capable of solving TGV for any order. While various methods address TGV regularization\, many are confined to second-order TGV\, and only a few explore orders greater than three for image recovery with TGV regularization. To our knowledge\, no algorithm resolves image recovery challenges employing TGV regularization for orders exceeding three under a general forward model. This challenge arises from the intricate nature of TGV representation. We surmount this obstacle by presenting two simple matrix based representations of TGV: the direct and compact forms. We prove the equivalence of both forms with the original TGV definition. Leveraging the compact representation\, we propose a generalized ADMM-based algorithm to solve TGV regularization for any order. \nALL ARE WECOME.
URL:https://ee.iisc.ac.in/event/ee-phd-colloquium-on-imaging-inverse-problems/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230825T150000
DTEND;TZID=Asia/Kolkata:20230825T170000
DTSTAMP:20260528T095747
CREATED:20230822T095358Z
LAST-MODIFIED:20230825T073226Z
UID:240999-1692975600-1692982800@ee.iisc.ac.in
SUMMARY:Cancelled [Talk] Prof Neetesh Saxena Cardiff University UK
DESCRIPTION:Cancelled * \n\n\nDue to some unavoidable circumstances\, we are cancelling the talk by Prof Neetesh Saxena of Cardiff University scheduled today. Sorry for any inconvenience this may cause.\n\n\nTitle:  Cyber-physical Smart Grid Situational Awareness\n\nSpeaker:\n\n\nProf Neetesh Saxena \nSenior Lecturer\nSchool of Computer Science and Informatics\nCardiff University\, UK\n\n\nDate: 25th August 2023\, 3 pm\n\n\nVenue: MMCR\, EE Dept\, IISc\n\n\nAbstract: \nIn recent years\, the impact evaluation of cyber-physical security of the smart grid has become highly notable and extremely important and critical research direction due to several recent cyber-attacks attempts in different countries. The smart grid is vulnerable to cyber-attacks due to its integration with communication and control technologies. The cyber-attacks can affect operations and decision-making at the energy management system or effectively destroy the critical components\, even shut down the power operations and can disrupt service for its customers. Inaccurate information leads to triggering inappropriate actions by the operators. The cyber-attacks either can directly target a power component of the smart grid system or can be triggered through the communication network to the power system. In this talk\, I will discuss cyber security issues with a case study to explore the cyber-physical situational awareness.\n\nBiography:\nProf Neetesh is a Senior Lecturer with the School of Computer Science and Informatics at Cardiff University\, UK having 16+ years of professional experience. Previously\, he had affiliations with the Bournemouth University (UK)\, Georgia Institute of Technology (USA)\, Stony Brook University (USA) and SUNY Korea. He was a DAAD Scholar at Bonn-Aachen International Center for Information Technology (B-IT)\, Rheinische-Friedrich-Wilhelms Universität\, Bonn (Germany) and was also a TCS Research Scholar. His current research interests include cyber security and critical infrastructure security\, including cyber-physical system security: smart grid\, V2G and cellular communication networks.
URL:https://ee.iisc.ac.in/event/talk-prof-neetesh-saxena-cardiff-university-uk/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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