Lavanya Sita Tekumalla

    Industry: Over 9 years - Amazon, InMobi, Myntra, Kenome  

    Masters: Computer Graphics   ( 2002 - 2005 )
    School of Computing, University of Utah  

    Ph.D: Machine Learning   ( 2011 - 2016 )
    Dept. of Computer Science and Automation(CSA)
    Indian Institute of Science(IISc), Bangalore


    LinkedIn:     linkedin.com/in/lavanyats

About Me || Research || Industry || Publications || Talks || Videos || Program Committee || Workshops || Education

About Me

    • I am currently working with summarization data using LLMs with a Bay Area based startup as the Staff AI Scientist.
    • I have also been mentoring data science aspirants and helping them prepare for Machine Learning Interviews. I am the founder of MachineLearningInterview.com.

    Before this, I have been an ML consultant with multiple startups (Kenome, Sortly, NeoEyed, etc...). In the past, I have also been a Machine Learning Scientist at Amazon for the Core Machine Learning Team that solves a range of problems partnering with various Amazon teams to drive customer Impact. I had particularly worked on problems from the Amazon Fashion Vertical. I am a customer obsessed 2x-Amazonian.

    I had completed a PhD from IISc, where I performed most of my doctoral research at the Machine Learning Lab, CSA, IISc. I was advised by Dr. Chiranjib Bhattacharya. Prior to that, I was advised by Dr. Indrajit Bhattacharya. My research focus during PhD has been on Bayesian Non-parametric modeling, Probabilistic Graphical models and their applications. I am also interested in approaches for scaling inference algorithms and recently deep learning based techniques. So far, I have worked on probabilistic models for the e-commerce domain, systems domain, and Natural Language Processing.

    Prior to joining PhD, I had worked in the industry in a variety of roles at Amazon.com(Seattle), Myntra.com(Bangalore) and InMobi(Bangalore). During my PhD, I have worked closely with NetApp(Bangalore) on designing machine learning models for mining block I/O traces and have also interned at Xerox Research Center(Bangalore), where I worked on modeling with Copulas.

    I had also worked with Prof. Elaine Cohen (Geometric Design and Computation Group) in the Area of Geometric Modeling with B-Splines, during my Masters at University of Utah. My work involved finding novel algorithms for fitting B-Spline surfaces from noisy and incomplete point cloud data.

Some Research Projects

  • Product Size Recommendation for E-commerce (@Amazon) :

    -- Bayesian Models For Product Size Recommendation, WWW 2018, Vivek Sembium, Rajeev Rastogi, Lavanya Tekumalla, Atul Saroop.

  • Copula Based Modeling for Mixed Discrete Continuous Data (In collaboration with Xerox Research Center India-XRCI) :

    -- "Vine copulas for mixed data : multi-view clustering for mixed data beyond meta-Gaussian dependencies", Lavanya Sita Tekumalla, Vaibhav Rajan, Chiranjib Bhattacharyya, Machine Learning Journal, 2017, 10.1007/s10994-016-5624-2. (pdf)

    -- Patent Filed: Methods and Systems For Predicting the Health Condition Of a Human Subject, Inventors: Lavanya Tekumalla, Vaibhav Rajan, 20140865US01.

  • Bayesian Non-parametric modeling for systems data (In collaboration with Netapp, Bangalore) :
    Existing techniques for cache Preloading are based on analyzing short range block access level correlations. We address the novel problem of bulk preloading of Gigabytes of data at a time, minutes or hours in advance by reducing an I/O trace to a a sequence of count vectors and proposing novel BNP techniques for multivariate count data analysis (a previously unexplored topic). This is ongoing interdisciplinary work.

    -- Copula-HDP-HMM: Non-parametric models with Copulas for I/O Efficient Bulk Cache Preloading, Lavanya Sita Tekumalla, Chiranjib Bhattacharyya, Accepted at SIAM Data Mining conference, 2016.

    -- Mining Block I/O Traces for Cache Preloading with Sparse Temporal Non-parametric Mixture of Multivariate Poisson, Lavanya Sita Tekumalla, Chiranjib Bhattacharyya, SIAM Data Mining conference, Vancouver, 2015 (pdf)

    -- Honourable mention @ Xerox Research Center India Colloquium 2016.

    -- Invited Talk May 2015 @ Facebook AI Research, Palo Alto, USA: 'Statistical Models for Bulk Cache Preloading', Lavanya Sita Tekumalla

    -- Invited Talk April 2015 @ NetApp University Day, Bangalore, India: 'Mining Block I/O traces for Bulk Cache Preloading', Lavanya Sita Tekumalla

  • Multi-level Non-parametric Admixture Models - nHDP (With collaborators from IRL, Bangalore) :

    -- Deep Infinite Admixture Models, NIPS 2018, Bayesian Deep Learning Workshop, Lavanya Sita Tekumalla, Priyanka Agarwal, Indrajit Bhattacharya. (pdf)
    -- Deep Nested Hierarchical Dirichlet Processes, NIPS 2018, Bayesian Non-parametric Modeling Workshop, Lavanya Sita Tekumalla, Priyanka Agarwal, Indrajit Bhattacharya. (pdf)
    -- "Multilevel Nonparametric Admixture Modeling with Nested Hierarchical Dirichlet Process", Lavanya Tekumalla*, Priyanka Agarwal*, and Indrajit Bhattacharya. (* equal contribution authors), arXiv:1508.06446, 2015 (pdf)

    -- "Nested Hierarchical Dirichlet Process for Nonparametric Entity-Topic Analysis", Priyanka Agrawal*, Lavanya Tekumalla*, and Indrajit Bhattacharya. European Conference of Machine Learning 2013, Prague. (* equal contribution authors) (pdf)

    -- Invited Talk 2014 @ Xerox Research Labs India, Bangalore, India: "Nested Hierarchical Dirichlet Process for Nonparametric Entity-Topic Analysis", Lavanya Tekumalla

  • Reverse Engineering Point Clouds to Obtain Tensor Product B-Spline Surfaces:

    --"Smoothing Space Curves with the MLS Projection", Lavanya Sita Tekumalla, Elaine Cohen, Proceedings of Symposium on Geometric Modeling, Vizualization and Graphics, Salt Lake City, July 2005. (pdf).

    --"Hole-Filling Algorithm for Triangular Meshes"(41 citations), Lavanya Sita Tekumalla, Elaine Cohen, Technical Report, School of Computing, University of Utah, Dec 2004, UUCS-04-019. (pdf)

    --"Reverse Engineering Point Clouds to Fit Tensor Product B-Spline Surfaces by Blending Local Fits, Tech Report", May 2005 (pdf)

    -- Talk : "Reverse Engineering Point Clouds to Trimmed NURBS" , presented as a talk at the conference 'Mathematical Methods for Curves and Surfaces', Oslo, July 2004.

Education

  • PhD in CS : GPA - 7.0/8 : Indian Institute of Science (IISC), Bangalore.

    • (Google Anita Borg Scholar APAC - 2014)

  • MS in CS with Computer Graphics Emphasis: GPA-3.97/4 : School of Computing, University of Utah

  • BE in CS : 89% : Osmania University College of Engineering(Autonomous) - OUCE, Hyderabad

    • (GATE All India Rank 2 , Rank 4 in University)
Other Academic Activities at CSA, IISc
    TA for Algorithms and Programming - ESC 101 (Aug-Dec 2012)
    TA for Linear Algebra Course - E0219 (Aug-Dec 2013)
    TA for Machine Learning - E0270 (Jan-Apr 2014, 2015)
    Reviewer: Robotics and Autonomous Systems (Elsevier Journal), Machine Learning For Big Data (Sadhana Journal)

Industry

    I have spent a considerable time in the industry working in a variety of roles that I thoroughly enjoyed.

  • 2018 Oct -: Kenome.io : Consulting Product & ML Specialist: Kenome is a deep tech NLP startup that makes Knowledge Graphs for Enterprises.

  • 2017 Jan-May 2018: Amazon.com : I have worked for the Core Machine Learning team of Amazon that solves a range of problems partnering with various Amazon teams to drive customer Impact. I have particularly worked on problems from the Amazon Fashion Vertical during this period.

  • 2005 April-2008 Nov: Amazon.com : I have worked for Amazon.com designing and developing software for the Amazon Fulfilment Center. I worked on various algorithms to improve the productivity of the work force though optimal work assignment strategies at the Amazon warehouses.

  • 2009 Jan - 2009 Dec : Myntra.com : Myntra.com is a Bangalore based e-commerce start-up. I worked primarily on software to improve and finetune their order management pipeline for fullfilment.

  • 2010 Jan - 2011 July : InMobi: InMobi is a Bangalore based start-up. InMobi SmartPay is a mobile payment gateway that enables various modes of payments for digital merchandize. I joined InMobi SmartPay at its inception and helped build the codebase from scratch and lead the development effort for expanding this product to sevaral countries.

Talks


    -- Invited Panellist April 2019 @ Springboard Leap, Bangalore - "AI Across Application Domains"

    -- Invited Talk Nov 2018 @ Amazon Blink Studio with WGSN Fashion Trend Forecasting, Delhi - ”AI Trends in Fashion"

    -- Invited Talk Sep 2018 @ HasGeek AntHill Inside 2018, Bangalore - ”Product Size Recommendation in Fashion E-commerce"

    -- Invited Talk July 2018 @ Robert Bosch Center for Cyber Physical Systems, Bangalore - ”Bayesian Models for Product Size Recommendation"

    -- Invited Talk April 2018 @ Google AI/ML Workshop, Bangalore - ”Product Size Recommendation in Fashion E-commerce"

    -- Invited Talk Feb 2018 - Keynote Speaker @ Developer Weekend Bangalore, “Is Machine Learning the Future”

    -- Invited Talk Nov 2017 @ Grace Hopper India, Bangalore, ‘Machine Learning At Amazon’', Lavanya Sita Tekumalla, Rajeev Rastogi.

    -- Invited Talk Feb 2017 @ Invited talk at Conference on Data Science (CODS 2017), Bangalore: Copula-HDP-HMM: Bayesian models for Bulk Cache Preloading

    -- Invited Talk Oct 2016 @ Core Machine Learning Team, Amazon Development Center India, "Modeling Multivariate Count Data for Bulk Cache Preloading".

    -- Invited Talk May 2015 @ Facebook AI Research, Palo Alto, USA: 'Statistical Models for Bulk Cache Preloading', Lavanya Sita Tekumalla

    -- Invited Talk April 2015 @ NetApp University Day, Bangalore, India: 'Mining Block I/O traces for Bulk Cache Preloading', Lavanya Sita Tekumalla

    -- Invited Talk 2014 @ Xerox Research Labs India, Bangalore, India: "Nested Hierarchical Dirichlet Process for Nonparametric Entity-Topic Analysis", Lavanya Tekumalla

    -- Talk : "Reverse Engineering Point Clouds to Trimmed NURBS" , presented as a talk at the conference 'Mathematical Methods for Curves and Surfaces', Oslo, July 2004.

Select Youtube Videos

Workshops Organized


    -- “Deep Learning for Natural Language Processing", Online Guest Workshop @Tata Consultancy Services (TCS), 2019, India.

    -- “Introduction to Predictive Analytics with R and python”, Workshop @GraceHopperConference, GHC 2016, India.

    -- Organized the CSA Undergraduate Summer School 2014.

    -- Workshop on Probabilistic Graphical Models @ Amazon India (Gurukul Series).

Reviewer/Committee member


    -- AAAI 2018, CODS 2018, ICDM 2017, CODS 2017, Journal on Robotics and Autonomous Systems (Elsevier), Machine Learning for Big Data, Sadhana Journal (Springer)
.