BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//HasGeek//NONSGML Funnel//EN
DESCRIPTION:A conference on AI and Deep Learning
X-WR-CALDESC:A conference on AI and Deep Learning
NAME:Anthill Inside 2019
X-WR-CALNAME:Anthill Inside 2019
REFRESH-INTERVAL;VALUE=DURATION:PT12H
SUMMARY:Anthill Inside 2019
TIMEZONE-ID:Asia/Kolkata
X-PUBLISHED-TTL:PT12H
X-WR-TIMEZONE:Asia/Kolkata
BEGIN:VEVENT
SUMMARY:Check-in and onsite registrations
DTSTART:20191123T030000Z
DTEND:20191123T034500Z
DTSTAMP:20260421T125340Z
UID:session/Ec9vpCQADwEsMGDzdPhNR1@hasgeek.com
SEQUENCE:0
CREATED:20191114T124110Z
DESCRIPTION:\n
LAST-MODIFIED:20191114T124116Z
LOCATION:Bangalore
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
BEGIN:VALARM
ACTION:display
DESCRIPTION:Check-in and onsite registrations in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Introduction to Anthill Inside 2019
DTSTART:20191123T034500Z
DTEND:20191123T035500Z
DTSTAMP:20260421T125340Z
UID:session/PrDzFs3FZr1XLF5Xt2RJzE@hasgeek.com
SEQUENCE:0
CREATED:20190806T093441Z
DESCRIPTION:\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20191122T060940Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
BEGIN:VALARM
ACTION:display
DESCRIPTION:Introduction to Anthill Inside 2019 in Ballroom in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Introduction to Naman Kumar's talk on Robotics
DTSTART:20191123T035500Z
DTEND:20191123T040000Z
DTSTAMP:20260421T125340Z
UID:session/VuYzkHmRJyCidtttsY9Sjk@hasgeek.com
SEQUENCE:0
CREATED:20191122T061009Z
DESCRIPTION:\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20191122T061137Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
BEGIN:VALARM
ACTION:display
DESCRIPTION:Introduction to Naman Kumar's talk on Robotics in Ballroom in 
 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:What can software learn from robots and math
DTSTART:20191123T040000Z
DTEND:20191123T044000Z
DTSTAMP:20260421T125340Z
UID:session/Rda85rrDA6EbXbiRTcAQCz@hasgeek.com
SEQUENCE:2
CATEGORIES:Full talk,Advanced,Lecture
CREATED:20191027T070555Z
DESCRIPTION:If you have no clue about what is going on\, don’t worry. In
  this presentation\, I will try to build your intuition with a series of s
 imple examples. Then\, with a little bit of math\, I will demonstrate how 
 the Kalman filter works its charm. Finally\, I will end by giving you a gl
 impse of its numerous applications in different fields and how you can pro
 bably use it in your own project.\n\n### Speaker bio\n\nhttps://www.linked
 in.com/in/naman-kumar-0582004a/\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/what-can-software-lear
 n-from-robots-and-math-Rda85rrDA6EbXbiRTcAQCz
BEGIN:VALARM
ACTION:display
DESCRIPTION:What can software learn from robots and math in Ballroom in 5 
 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Rigorous evaluation of NLP models for real-world deployment
DTSTART:20191123T044000Z
DTEND:20191123T052000Z
DTSTAMP:20260421T125340Z
UID:session/DhgpbXL1ZBCmoVJucovFu3@hasgeek.com
SEQUENCE:2
CATEGORIES:Full talk,Intermediate,Discussion
CREATED:20191014T064157Z
DESCRIPTION:We motivate why rigorous evaluation of NLP models beyond simpl
 e metrics such as F1-score/accuracy are needed for real world deployment w
 ith a few historical use-cases/examples. We then talk about the "CleverHan
 s Moment for NLP" (https://www.linkedin.com/posts/sandya_nlps-clever-hans-
 moment-has-arrived-activity-6573894455768768512-MDVW). We discuss the late
 st research around model evaluation for NLP. We then take up the example o
 f a sentiment analysis task as a case-study and discuss the methodology fo
 r rigorous evaluation. We conclude by pointing out future work directions 
 in this topic.\n\n### Speaker bio\n\nSandya Mannarswamy (https://www.linke
 din.com/in/sandya/) is an independent NLP researcher. She was previously a
  senior research scientist at Conduent Labs India in the Natural Language 
 Processing research group.  She holds a Ph.D. in computer science from Ind
 ian Institute of Science\, Bangalore. Her research interests span natural 
 language processing\, machine learning and compilers.  Her research career
  spans over 19 years\, at various R&D labs\, including Hewlett Packard Ltd
 \, IBM Research etc.  She has co-organized a number of workshops including
  workshops at International Conference on Data Management\, Machine Learni
 ng Debates workshop at ICML-2018 etc. Her current research is focused on s
 oftware testing and evaluation of  Natural Language Processing application
 s. She has a number of international research publications and patents in 
 the area of natural language processing (https://scholar.google.co.in/cita
 tions?hl=en&user=i27nd3oAAAAJ&view_op=list_works&sortby=pubdate) She co-au
 thored a paper at International Conference on Artificial Intelligence (IJC
 AI) 2018\, which focused on the challenges in taking AI applications from 
 research to real world.  Her current research is focussed on rigorous eval
 uation of NLP applications (“using NLP to evaluate NLP”).  She is the 
 author of the popular “CodeSport” column in Open Source For You magazi
 ne. (https://opensourceforu.com/tag/codesport/).\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/rigorous-evaluation-of
 -nlp-models-for-real-world-deployment-DhgpbXL1ZBCmoVJucovFu3
BEGIN:VALARM
ACTION:display
DESCRIPTION:Rigorous evaluation of NLP models for real-world deployment in
  Ballroom in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:How we applied sampling algorithms to extract meaning from data
DTSTART:20191123T052000Z
DTEND:20191123T055000Z
DTSTAMP:20260421T125340Z
UID:session/6PKGqBS9ekuyka7NzhtFZr@hasgeek.com
SEQUENCE:2
CATEGORIES:Full talk of 40 mins
CREATED:20191108T060506Z
DESCRIPTION:Generative models => Basic idea of sampling algorithms to infe
 rence parameters => Simple example using Gibbs sampling => Application to 
 a more complex problem of resume understanding at Belong.co\n\n### Speaker
  bio\n\nCurrently CTO at Belong.co\, Vinodh Kumar is one of the top indust
 ry leaders with more than a decade of hands-on experience in search\, rank
 ing and machine learning. Prior to Belong\, Vinodh used to be CTO/M.D of B
 loomreach driving their e-commerce search engine efforts. Earlier Vinodh s
 pent more than 6 years at Google leading the Google News team and building
  the ranking algorithms that power Google News. He did his masters in comp
 uter science from the Indian Institute of Science after securing the All I
 ndia Rank #1 in Graduate Engineering Entrance Exam (GATE '99) in computer 
 science. He has more than 10 patents to his name.\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/how-we-applied-samplin
 g-algorithms-to-extract-meaning-from-data-belong-co-6PKGqBS9ekuyka7NzhtFZr
BEGIN:VALARM
ACTION:display
DESCRIPTION:How we applied sampling algorithms to extract meaning from dat
 a in Ballroom in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Poster session: Model interpretability\, explainable AI and the Ri
 ght to Information (RTI)
DTSTART:20191123T052000Z
DTEND:20191123T055000Z
DTSTAMP:20260421T125340Z
UID:session/B986KGjGMnGc38PSHCC3yr@hasgeek.com
SEQUENCE:2
CATEGORIES:Crisp talk,Beginner,Discussion,None,Accepted as poster session
CREATED:20191021T104704Z
DESCRIPTION:Consequential machine decision making is now pervasive. Automa
 ted decisions (to different degrees of automation) are now applied in fiel
 ds of welfare allocation\, policing and criminal justice\, finance and ins
 urance and online content moderation\, among others. Many of these tools u
 se complex algorithmic systems\, including machine learning techniques\, w
 hich are conventionally difficult to interpret. Efforts toward interpretat
 ion have traditionally focused on model interpretation through explaining 
 the 'black box' of algorithmic systems (for example through local linear e
 xplanations or models). However\, these techniques of interpretability hav
 e limited significance where end-users are concerned\, for a number of rea
 sons\, including the ability of a lay citizen to parse technical models\, 
 as well as the limited information it provides for achieving instrumental 
 purposes of explanation (for example\, the ability to use an explanation t
 o overturn a decision). Some techniques have focused on explainability wit
 hout opening the black box\, including through methods like counterfactual
  explanations. However\, limited work exists on how the non-interpretabili
 ty of machine decisions impacts important constitutional concepts of due p
 rocess and the right to information as well as legal mechanisms like the R
 TI Act which actualise these rights. The RTI Act\, in particular\, places 
 positive obligations upon the state to explain certain decisions\, includi
 ng administrative decisions taken that impact individuals. The extent to w
 hich techniques of explainability in AI can be incorporated to ensure that
  the RTI remains a robust instrument for holding government systems accoun
 table will be the focus of this session.\n\n### Speaker bio\n\nI am a lawy
 er and a legal researcher\, working in the field of technology policy. I h
 ave researched and written extensively on issues of internet openness and 
 digital rights. In my role as a technology policy fellow at the Mozilla Fo
 undation\, I am focussing on creating policy for improving machine decisio
 n making systems in India.\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Poster sessions and BOF track - Taj M G Road\, Bangalore\nBangalo
 re\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/model-interpretability
 -explainable-ai-and-the-right-to-information-B986KGjGMnGc38PSHCC3yr
BEGIN:VALARM
ACTION:display
DESCRIPTION:Poster session: Model interpretability\, explainable AI and th
 e Right to Information (RTI) in Poster sessions and BOF track in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Morning beverage break
DTSTART:20191123T055000Z
DTEND:20191123T062000Z
DTSTAMP:20260421T125340Z
UID:session/Ciey1ABEGSSV774988skH4@hasgeek.com
SEQUENCE:0
CREATED:20191108T062213Z
DESCRIPTION:\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20191108T062220Z
LOCATION:Poster sessions and BOF track - Taj M G Road\, Bangalore\nBangalo
 re\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
BEGIN:VALARM
ACTION:display
DESCRIPTION:Morning beverage break in Poster sessions and BOF track in 5 m
 inutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Morning beverage break
DTSTART:20191123T055000Z
DTEND:20191123T062000Z
DTSTAMP:20260421T125340Z
UID:session/W4rYhjqq5ShMRQyasiCDnL@hasgeek.com
SEQUENCE:0
CREATED:20190806T093621Z
DESCRIPTION:\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20191108T062216Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
BEGIN:VALARM
ACTION:display
DESCRIPTION:Morning beverage break in Ballroom in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Introduction to Mira Abboud's talk on automated investments with A
 rtificial Intelligence
DTSTART:20191123T062000Z
DTEND:20191123T062500Z
DTSTAMP:20260421T125340Z
UID:session/5Gbyb97dK6Z6SmyhYd79Bt@hasgeek.com
SEQUENCE:0
CREATED:20191122T061126Z
DESCRIPTION:\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20191122T061147Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
BEGIN:VALARM
ACTION:display
DESCRIPTION:Introduction to Mira Abboud's talk on automated investments wi
 th Artificial Intelligence in Ballroom in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Artificial Intelligence for automated investment
DTSTART:20191123T062500Z
DTEND:20191123T070500Z
DTSTAMP:20260421T125340Z
UID:session/8ZESyev9B324VvquhnCvB1@hasgeek.com
SEQUENCE:2
CATEGORIES:Full talk,Advanced,Lecture
CREATED:20191014T064002Z
DESCRIPTION:The talk will cover the following areas:\n-  AI in finance vs 
 AI in other fields.\n-  Challenges faced while applying machine learning a
 lgorithms on stock market data (Daily data\, problems of Over/Under fittin
 g\, fat tails\, etc).\n-  Limitations/problems of Supervised and Unsupervi
 sed learning\n-  State of the art solutions.\n\n### Speaker bio\n\nAs a CT
 O and a data scientist at Neotic.ai SAL\, Dr. Mira Abboud leads Neotic’s
  long-term technology vision from supervising the technical team to improv
 ing the data science process development and is responsible for implementi
 ng new ideas after studying their feasibility. Mira is a Computer Sciences
  instructor at Lebanese University and researcher in the AI field. Holder 
 of a Ph.D focused on AI and software architectures extraction\, from local
  & Nantes (France) university. Her Publications include "Towards Using KDD
  for an Interactive Software Architecture Extraction" and "KDD extension t
 ool for software architecture extraction".\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/artificial-intelligenc
 e-for-automated-investment-8ZESyev9B324VvquhnCvB1
BEGIN:VALARM
ACTION:display
DESCRIPTION:Artificial Intelligence for automated investment in Ballroom i
 n 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Birds of Feather (BOF) session: Myths and realities of data labeli
 ng for Deep Learning
DTSTART:20191123T070500Z
DTEND:20191123T080500Z
DTSTAMP:20260421T125340Z
UID:session/T6quRXcrsUZukXCBiJLasM@hasgeek.com
SEQUENCE:2
CATEGORIES:Birds Of Feather (BOF) session ,Intermediate,Discussion
CREATED:20190823T050603Z
DESCRIPTION:- setting the context : data labeling for NLP and CV\n- how to
  define a data labeling task : novice vs expert\n- does crowd sourcing of 
 data labeling really work : adv vs disadv.\n- how to manage in house data 
 labeling teams : adv vs disadv\n- what is the criticality of the correctne
 ss of data labels\n- what is the experience and expertise expectation of d
 ata labelers\n- how to ensure correctness of data labels : manual vs autom
 ated checks\n- how to resolve labeling conflicts\n- how does an engineer k
 now if she has enough labeled data\n- what are the time\, cost\, correctne
 ss trade-offs\n- how to ensure and execute class balanced data labeling\n-
  how to plan and execute weakly supervised data labeling\n- how to train m
 odels on small set of labeled data and generate 'soft tags' for the rest o
 f the unlabeled data\n- how does one know if a model is performing well in
  practice on unseen and real-time inputs\n- how does feedback loop work wh
 en some of the unseen and real-time inputs are labeled to fine-tune the mo
 dels\n\n### Speaker bio\n\nVijay is the co-founder and CTO of Infilect Tec
 hnologies\, a Computer Vision and Deep Learning start-up\, builidng B2B Sa
 aS products for global retail industry. Vijay has a PhD in CSE\, from IIT 
 Bombay. Vijay has worked as research scientist in IBM Research Labs.\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Poster sessions and BOF track - Taj M G Road\, Bangalore\nBangalo
 re\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/myths-and-realities-of
 -data-labeling-for-deep-learning-T6quRXcrsUZukXCBiJLasM
BEGIN:VALARM
ACTION:display
DESCRIPTION:Birds of Feather (BOF) session: Myths and realities of data la
 beling for Deep Learning in Poster sessions and BOF track in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Document digitization: rethinking with Deep Learning
DTSTART:20191123T070500Z
DTEND:20191123T074500Z
DTSTAMP:20260421T125340Z
UID:session/RMnNsZnN6QzwMwufoBCgwg@hasgeek.com
SEQUENCE:2
CATEGORIES:Full talk,Intermediate,Lecture
CREATED:20190827T090710Z
DESCRIPTION:This talk will outline:\n* The problems and approaches we face
 d when building deep learning networks to solve problems in the informatio
 n extraction process.\n* Thought process on why and how we chose certain d
 eep learning strategies\n* The requirement for supervised learning\n* Limi
 tations of deep learning networks\n* Planning and executing research activ
 ities in short cycles\n* Evolution of team structures to support AI produc
 t building\n* Engineering practises required in building AI systems.\n\n##
 # Speaker bio\n\nNischal HP is currently the VP of Engineering and Data sc
 ience at Berlin based company omni:us\, which operates in the building of 
 AI product for the insurance industry. \n\nPreviously\, he was a cofounder
  and data scientist at Unnati Data Labs\, where he worked towards building
  end-to-end data science systems in the fields of fintech\, marketing anal
 ytics\, event management and medical domain. Nischal is also a mentor for 
 data science on Springboard. During his tenure at former companies like Re
 dmart and SAP\, he was involved in architecting and building software for 
 ecommerce systems in catalog management\, recommendation engines\, sentime
 nt analyzers \, data crawling frameworks\, intention mining systems and ga
 mification of technical indicators for algorithmic trading platforms. \n\n
 Nischal has conducted workshops in the field of deep learning and has spok
 en at a number of data science conferences like Strata London 2019\, Qcon 
 AI SF 2019\, Pycon Canda 2018\, Oreilly strata San jose 2017\, PyData Lond
 on 2016\, Pycon Czech Republic 2015\, Fifthelephant India (2015 and 2016)\
 , Anthill\, Bangalore 2016. He is a strong believer of open source and lov
 es to architect big\, fast\, and reliable AI systems. In his free time\, h
 e enjoys traveling with his significant other\, music and groking the web.
 \n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/document-digitization-
 rethinking-it-with-deep-learning-RMnNsZnN6QzwMwufoBCgwg
BEGIN:VALARM
ACTION:display
DESCRIPTION:Document digitization: rethinking with Deep Learning in Ballro
 om in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Lunch break
DTSTART:20191123T074500Z
DTEND:20191123T083500Z
DTSTAMP:20260421T125340Z
UID:session/6ftLEGrBoybXE9pcJ6x1oB@hasgeek.com
SEQUENCE:0
CREATED:20190806T093928Z
DESCRIPTION:\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20191122T061155Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
BEGIN:VALARM
ACTION:display
DESCRIPTION:Lunch break in Ballroom in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Lunch break
DTSTART:20191123T080500Z
DTEND:20191123T083500Z
DTSTAMP:20260421T125340Z
UID:session/4Buzo2sFVQRX2RHbnXohH9@hasgeek.com
SEQUENCE:0
CREATED:20191108T062231Z
DESCRIPTION:\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20191122T061157Z
LOCATION:Poster sessions and BOF track - Taj M G Road\, Bangalore\nBangalo
 re\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
BEGIN:VALARM
ACTION:display
DESCRIPTION:Lunch break in Poster sessions and BOF track in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Birds of a Feather (BOF) session: On Interpretability
DTSTART:20191123T083500Z
DTEND:20191123T093500Z
DTSTAMP:20260421T125340Z
UID:session/YcPoT6Q3C1DaCgkDx63grZ@hasgeek.com
SEQUENCE:2
CATEGORIES:Birds Of Feather (BOF) session ,Intermediate,Discussion
CREATED:20190813T063957Z
DESCRIPTION:- Why is model interpretability important?\n- Trade off betwee
 n accuracy and interpretability.\n- Developments in explainable AI.\n- Int
 erpret black box models\, global and local interpretation.\n\n### Speaker 
 bio\n\nLed by Jacob Joseph\, Namrata Hanspal. Discussants: Nishant Sinha a
 nd Madhu Gopinathan\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Poster sessions and BOF track - Taj M G Road\, Bangalore\nBangalo
 re\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/birds-of-a-feather-on-
 interpretability-YcPoT6Q3C1DaCgkDx63grZ
BEGIN:VALARM
ACTION:display
DESCRIPTION:Birds of a Feather (BOF) session: On Interpretability in Poste
 r sessions and BOF track in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Why smart-device based virtual assistants are incapable of assisti
 ng with gender based violence concerns in India.
DTSTART:20191123T083500Z
DTEND:20191123T090500Z
DTSTAMP:20260421T125340Z
UID:session/8PUjkrJ5LYLd21ey5CtnTE@hasgeek.com
SEQUENCE:2
CATEGORIES:Full talk,Intermediate,Lecture,Full talk of 40 mins
CREATED:20191108T061238Z
DESCRIPTION:Part 1. Introduction to Gendered Biases\nThe talk will begin w
 ith a brief introduction to fairness and gendered bias concerns in Artific
 ial Intelligence technologies with relevant examples.  \n\nPart 2. Are Sma
 rt-Device Based Virtual Assistants Capable of Assisting with Gender Based 
 Violence\nConcerns in India?\nI will present my research which critically 
 examines the responses of five Virtual Assistants in India -- Siri\, Googl
 e Now\, Bixby\, Cortana\, and Alexa -- to a standardized set of concerns r
 elated to Gender-Based Violence (GBV).  A set of concerns regarding Sexual
  Violence and Cyber Violence were posed in the Virtual Assistant’s natur
 al language\, English. Non-crisis concerns were asked to set a baseline. A
 ll crisis responses by the Virtual Assistants were characterized based on 
 the ability to (1) recognize the crisis\, (2) respond with respectful lang
 uage\, and (3) refer to an appropriate helpline\, or other resources. The 
 findings of my study indicate missed opportunities to leverage technology 
 to improve referrals to crisis support services in response to gender-base
 d violence.\nRead my paper here: https://itforchange.net/e-vaw/wp-content/
 uploads/2018/01/Are-Smart-Device-Based-Virtual-Assistants-Capable-of-Assis
 ting-with-Gender-Based-Violence-Concerns-in-India-1.pdf\n\nPart 3. Feminis
 t Perspectives on the Social Media Construction of Artificial Intelligence
 \nI will analyse how Microsoft’s Twitter bot Tay went from tweeting “c
 an i just say that im stoked to meet u? humans are super cool” to “I .
 ... hate feminists and they should all die and burn in hell” and how we 
 can avoid designing such biased AI technologies for the future.\nRead my w
 ork here: https://gendermediacultureblog.wordpress.com/2018/12/24/feminist
 -perspectives-on-the-social-media-construction-of-artificial-intelligence/
 \n\n### Speaker bio\n\nI currently work as a Programme Officer at the Cent
 re for Internet and Society (CIS)\, New Delhi\, researching the intersecti
 ons of gender and emerging technologies such as Artificial Intelligence. P
 reviously\, I worked with the Internet Governance Forum of the United Nati
 ons as a Consultant on Gender and Access (2018)\, and with the Association
  of Progressive Communications (APC) (2017) on gender and technology. I ha
 ve a Master’s degree in Women’s Studies from the Tata Institute of Soc
 ial Sciences (TISS)\, Mumbai\, and a Bachelor’s degree in Computer Scien
 ce Engineering from M.S. Ramaiah Institute of Technology\, Bengaluru. Outs
 ide of work\, you will find me tweeting about feminism\, writing on Medium
 \, and engaging with grassroots political activism.\nTwitter: @so_radhikal
 \nLinkedIn: https://www.linkedin.com/in/radhika-radhakrishnan/ \nMedium: h
 ttps://medium.com/radhika-radhakrishnan\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/gendered-biases-in-art
 ificial-intelligence-8PUjkrJ5LYLd21ey5CtnTE
BEGIN:VALARM
ACTION:display
DESCRIPTION:Why smart-device based virtual assistants are incapable of ass
 isting with gender based violence concerns in India. in Ballroom in 5 minu
 tes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:ML application lifecycle: what is important at each stage
DTSTART:20191123T090500Z
DTEND:20191123T094500Z
DTSTAMP:20260421T125340Z
UID:session/KGWPdgsMtZENo8MscTWkud@hasgeek.com
SEQUENCE:2
CATEGORIES:Full talk,Intermediate,Lecture
CREATED:20191101T103137Z
DESCRIPTION:Building good ML systems is not very unlike developing good so
 ftware. Just as developing good software requires mastering not only progr
 amming theory\, tools\, and design patterns\, but also the process of soft
 ware development itself\, building a good ML system entails familiarity wi
 th the ML application lifecycle.  In this talk\, we will discuss the vario
 us stages of ML application life cycle - problem formulation\, data defini
 tions\, modeling\,  production system design  &implementation\, testing\, 
 deployment & maintenance\, online evaluation & evolution\,  and some key l
 earnings that are relevant for each of these stages.\n\n### Speaker bio\n\
 nSrujana is an independent machine learning researcher and consultant with
  over 15 years of experience. Till recently\, she was the chief scientist 
 of CuspEra\, a software marketplace startup. Prior to that\, she was a pri
 ncipal data scientist at Flipkart (Bangalore) and a volunteer for Ekstep\,
  an education startup. She has been employed with the machine learning gro
 ups at Amazon (Bangalore)\, IBM Research (Bangalore/New Delhi/Almaden/York
 town Hts)\, and Yahoo Research (Santa Clara). Srujana has published her wo
 rk in several top-tier conferences and journals on data mining/machine lea
 rning and is the recipient of multiple best paper awards. She received her
  M.S. and Ph.D. from the University of Texas at Austin and her B. Tech. de
 gree from IIT Madras.\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/ml-application-lifecyc
 le-recommendations-for-each-stage-KGWPdgsMtZENo8MscTWkud
BEGIN:VALARM
ACTION:display
DESCRIPTION:ML application lifecycle: what is important at each stage in B
 allroom in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Why you need an enterprise grade data labelling pipeline to scale 
 your ML/AI pipelines
DTSTART:20191123T094500Z
DTEND:20191123T102500Z
DTSTAMP:20260421T125340Z
UID:session/9uzSTVnNZ9F9EfinvbcJRo@hasgeek.com
SEQUENCE:2
CATEGORIES:Full talk of 40 mins
CREATED:20191108T061028Z
DESCRIPTION:In Software 2.0\, Data is code. A mindful approach to your dat
 a annotation pipeline and practices is critical to the outcomes of your ML
  algorithms. If not done right\, your ability to scale this pipeline can o
 ften prove to be a major blocker to productionization.\n\nIn this talk we 
 focus on why and how to build your data labeling pipeline to be enterprise
  grade. We will describe the considerations and insights that go into maki
 ng your data pipeline a mindful part of your development pipeline\, so tha
 t you can follow the journey from PoC to production. We describe best prac
 tices and provide pointers to designing a high quality\, iterative\, and s
 calable data annotation practice.\n\nA pipeline designed for human judgeme
 nt and incremental training on edge cases\, can provide that last mile of 
 acceptability to roll out a machine learning solution in production. We wi
 ll describe successful examples of this approach.\n\n### Speaker bio\n\nBi
 kram is broadly interested in the role of AI in addressing challenges and 
 improving outcomes in education\, skill development and employability. At 
 iMerit\, Bikram heads innovation with a primary focus on designing tech-en
 abled learning experiences that enable iMerit’s workforce – sourced la
 rgely from impact communities - develop digital economy skills and deliver
  high quality data annotation services to AI organizations. Bikram is also
  CTO of Anudip Foundation\, iMerit’s not-for-profit sister organization 
 that trains youth from underserved communities in new age digital skills a
 nd helps them find gainful employment. Prior to joining iMerit and Anudip\
 , Bikram spent 15 years at IBM Research\, establishing and leading global 
 R&D programs in educational technologies\, service delivery\, and software
  engineering. Bikram holds MS and PhD degrees in Computer Science from the
  State University of New York\, Stony Brook. He has co-authored more than 
 50 scientific publications in international journals and conferences\, and
  holds several US patents.\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/build-an-enterprise-gr
 ade-data-labelling-pipeline-to-scale-your-ml-ai-pipelines-9uzSTVnNZ9F9Efin
 vbcJRo
BEGIN:VALARM
ACTION:display
DESCRIPTION:Why you need an enterprise grade data labelling pipeline to sc
 ale your ML/AI pipelines in Ballroom in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Poster session: Open source tools and archive for tackling misinfo
 rmation on chat apps in India
DTSTART:20191123T094500Z
DTEND:20191123T101500Z
DTSTAMP:20260421T125340Z
UID:session/BgdEbU74n2oEReUJtjzkjx@hasgeek.com
SEQUENCE:2
CATEGORIES:Short talk of 20 mins
CREATED:20191114T111148Z
DESCRIPTION:* Motivation and Goals of the Project\n  * How does it aim to 
 affect the misinformation challenge in India\n* Data Collection \n  * Ways
  of collecting media from Chat Apps\n  * Collecting media from allied sour
 ces (fact checking websites)\n* Data Processing (Tools to navigate the arc
 hive)\n  * Duplicate Detection\n  * Approximate Search\n  * Semantic Searc
 h\n  * Use of embeddings over hashing\n* Ethical Considerations in this wo
 rk\n  * Consent frameworks for data collection\n  * Managing access and us
 e\n  * Managing violent and pornographic content\n\n### Speaker bio\n\nKes
 hav Joshi is a data scientist @Tattle working to bring together an archive
  of misinformation and keep developing the data science stack. Keshav has 
 several years of experience as a data scientist/researcher/lecturer\, with
  two Masters in Physics & CS from Georgia Tech.\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Poster sessions and BOF track - Taj M G Road\, Bangalore\nBangalo
 re\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/open-source-tools-and-
 archive-for-tackling-misinformation-on-chatapps-in-india-BgdEbU74n2oEReUJt
 jzkjx
BEGIN:VALARM
ACTION:display
DESCRIPTION:Poster session: Open source tools and archive for tackling mis
 information on chat apps in India in Poster sessions and BOF track in 5 mi
 nutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Evening beverage break
DTSTART:20191123T102500Z
DTEND:20191123T105000Z
DTSTAMP:20260421T125340Z
UID:session/EK48ZgdpnHRWotHQD8yhsA@hasgeek.com
SEQUENCE:0
CREATED:20190806T094544Z
DESCRIPTION:\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20191122T061209Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
BEGIN:VALARM
ACTION:display
DESCRIPTION:Evening beverage break in Ballroom in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Poster session: Accountable behavioural change detection (VEDAR) u
 sing ML
DTSTART:20191123T105000Z
DTEND:20191123T112000Z
DTSTAMP:20260421T125340Z
UID:session/CRYS2k7VgKKUQ5Jqiu2skP@hasgeek.com
SEQUENCE:2
CATEGORIES:Advanced,Potentially Anthill Inside talk ,Awaiting review on em
 ail to decide on whether to shortlist or reject,This proposal is NOT a rej
 ect yet.,Short talk of 20 mins,Under review,Has potential. Mentor proposer
 . ,Respond to comments asap,Accepted as poster session
CREATED:20191021T104609Z
DESCRIPTION:This talk mainly covers VEDAR algorithem in detail and benchma
 rks comparison with other streamingly anomoly detection.   More details in
  the https://arxiv.org/abs/1902.06663\n\n### Speaker bio\n\nAravilli Srini
 vasa Rao working as Sr. Engineering Manager in Cisco CTO group and leading
  innovation & incubation of ML and AI projects. As a speaker presented in 
 following conferences/workshops\n1) Presented about Cisco's ML/AI Applicat
 ions in PDPC/CIPL workshop in Singapore.  As a panelist shared experiences
  and thoughts on Accountable and Responsible AI. 2 ) Presented in  IoT and
  AI Sumit organized by CII ’s in India about IoT and ML applications and
  related platforms in IoT space. 3) Presented about “Streaming Anomaly D
 etection” in Cisco’s Data Science Summit in Prague \n\nHe has a patent
  in Software recommendations uisng Reinforcement Learning.\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Poster sessions and BOF track - Taj M G Road\, Bangalore\nBangalo
 re\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/accountable-behavioura
 l-change-detection-vedar-using-machine-learning-CRYS2k7VgKKUQ5Jqiu2skP
BEGIN:VALARM
ACTION:display
DESCRIPTION:Poster session: Accountable behavioural change detection (VEDA
 R) using ML in Poster sessions and BOF track in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:The shape of U
DTSTART:20191123T105000Z
DTEND:20191123T112000Z
DTSTAMP:20260421T125340Z
UID:session/PWdVmj78ALxvP8SPeZbpUe@hasgeek.com
SEQUENCE:2
CATEGORIES:Crisp talk,Advanced,Lecture
CREATED:20191027T113617Z
DESCRIPTION:In this talk\, we will showcase our efforts at OffNote Labs to
  improve the developer experience when programming with tensors. In partic
 ular\, we will discuss:\n\n1. The idea of naming dimensions of tensors and
  how named shapes can make tensor programming dramatically less painful.\n
 2. The tsalib library\, which allows used named dimensions in Python 3.x p
 rograms with multiple backend libraries (numpy\, tensorflow\, pytorch\, 
 …).\n3. The tsanley library\, which builds on tsalib\, and helps catch t
 ricky tensor shape errors at runtime and annotate existing programs with n
 amed shapes.\n\n### Speaker bio\n\nNishant Sinha is an independent researc
 her and consultant at OffNote Labs\, with broad experience in building dee
 p learning systems (across text\, vision and speech domains) and symbolic 
 reasoning systems. Nishant helps companies understand and maneuver through
  the evolving deep learning/AI space and build IP\, in-house teams and sol
 utions that enable market leadership. He is also passionate about making c
 utting-edge research consumable and building tools that improve developer 
 experience.\n\nHe received his Ph.D. from Carnegie Mellon University and B
 . Tech. in Computer Science from IIT Kharagpur.\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/the-shape-of-u-PWdVmj7
 8ALxvP8SPeZbpUe
BEGIN:VALARM
ACTION:display
DESCRIPTION:The shape of U in Ballroom in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Poster session: Tensorboard: almost a one-stop shop for ML develop
 ment
DTSTART:20191123T112000Z
DTEND:20191123T115000Z
DTSTAMP:20260421T125340Z
UID:session/NaZyDfogs5LutodcbAbQcJ@hasgeek.com
SEQUENCE:2
CATEGORIES:Full talk,Beginner,Lecture,Submit revised slides within 7 days,
 None,Accepted as poster session
CREATED:20191021T104951Z
DESCRIPTION:1. Addressing the problems faced while developing machine lear
 ning models using just terminal for interface.\n2. How some companies have
  leveraged this pain into making a paid service for monitoring model train
 ing.\n3. Why tensorboard is better than any other paid service.\n4. Showca
 se of in-house tools built at Infilect.\n\n### Speaker bio\n\nTushar Pawar
  is Machine Learning Engineer at Infilect. He has around 3 years of experi
 ence in the field of Deep Learning. Has worked with several computer visio
 n problems such as image classification\, object detection\, image generat
 ion etc.\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Poster sessions and BOF track - Taj M G Road\, Bangalore\nBangalo
 re\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/tensorboard-almost-a-o
 ne-stop-shop-for-machine-learning-development-NaZyDfogs5LutodcbAbQcJ
BEGIN:VALARM
ACTION:display
DESCRIPTION:Poster session: Tensorboard: almost a one-stop shop for ML dev
 elopment in Poster sessions and BOF track in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
BEGIN:VEVENT
SUMMARY:Closing talk: Feast - feature store for Machine Learning
DTSTART:20191123T112000Z
DTEND:20191123T120000Z
DTSTAMP:20260421T125340Z
UID:session/DrCW1PvEZ5Q6DYvh27zPR7@hasgeek.com
SEQUENCE:2
CATEGORIES:Full talk,Beginner,Lecture
CREATED:20190823T050153Z
DESCRIPTION:GOJEK\, Indonesia’s first billion-dollar startup\, has seen 
 an explosive growth in both users and data over the past three years. Toda
 y\, it uses big data-powered machine learning to inform decision making in
  its ride-hailing\, lifestyle\, logistics\, food delivery\, and payment pr
 oducts\, from selecting the right driver to dispatch to dynamically settin
 g prices to serving food recommendations to forecasting real-world events.
  Hundreds of millions of orders per month\, across 18 products\, are all d
 riven by machine learning.\n\nFeatures are at the heart of what makes thes
 e machine learning systems effective. However\, many challenges still exis
 t in the feature lifecycle. Developing features from big data is often an 
 engineering heavy task\, with challenges in both the scaling of data proce
 sses and the serving of features in production systems. Teams also face ch
 allenges in enabling discovery\, reducing duplication\, improving understa
 nding\, and providing standardization of features throughout organizations
 .\n\nWillem will explain the need for features at organizations like GOJEK
  and discuss the challenges faced in creating\, managing\, and serving the
 m in production. He'll describe how in partnership with Google\, they desi
 gned and built a feature store called Feast to address these challenges an
 d explore their motivations\, the lessons they learned along the way\, and
  the impact the feature store had on GOJEK. Finally\, he will talk about t
 he open source plans for Feast and their roadmap going forward.\n\n### Spe
 aker bio\n\nWillem Pienaar leads the data science platform team at GOJEK\,
  working on the GOJEK ML platform\, which supports a wide variety of model
 s and handles over 100 million orders every month. His main focus areas ar
 e building data and ML platforms\, allowing organizations to scale machine
  learning and drive decision making. In a previous life\, Willem founded a
 nd sold a networking startup and was a software engineer in industrial con
 trol systems.\n
GEO:12.973321659788686;77.61947496794164
LAST-MODIFIED:20230810T072606Z
LOCATION:Ballroom - Taj M G Road\, Bangalore\nBangalore\nIN
ORGANIZER;CN="Anthill Inside":MAILTO:no-reply@hasgeek.com
URL:https://hasgeek.com/anthillinside/2019/schedule/feast-feature-store-fo
 r-machine-learning-DrCW1PvEZ5Q6DYvh27zPR7
BEGIN:VALARM
ACTION:display
DESCRIPTION:Closing talk: Feast - feature store for Machine Learning in Ba
 llroom in 5 minutes
TRIGGER:-PT5M
END:VALARM
END:VEVENT
END:VCALENDAR