Praveen PankajakshanData Science Researcher

AI for Social Good

EducationPhD. INRIA, Sophia Antipolis, France, (summa cum laude).

Signal & Image Processing

MS. Texas A&M University, College Station, TX, USA.Electrical and Computer Engineering

B. Tech. Indian Institute of Technology (IIT), Roorkee, India.Electrical Engineering

Research InterestsSignal & Image Processing, Inverse Problems, Time-Series Analysis, Pattern Recognition, Data Science, MachineLearning, Internet of Things (IoT).

Prior Applied AreasNew Energy, Neuroscience, Healthcare, Life Sciences, Agriculture, Environment and Sustainability, .

EXPERIENCE2017– Present Principal Data Science Manager, Corteva Agriscience, Agriculture division of DowDuPont, Hyder-

abad, India.Technical Leadership for Data Science

+ Individual Contribution: Semantic Segmentation of Leaves for quantifying Leaf Area Index (LAI) using Rasp-berry Pi3B and Pi Camera by destructive sampling,

+ Hyperspectral Image based Land Classification of Satellite Images by making a trade-o� between the Spatio-Spectral Similarity Measures exploiting local Markovian property with minimum training data and transferablemodels,

+ Built and deployed an IoT platform and solution (IP Disclosure filed) for smart agricultural research fieldsincluding novel field sensors,

+ Technical Leadership: Built a team of in-house experts in IoT, UAV and Satellite Imaging+ Built the strategy for Data Science in India by collaborating with research scientists, business and functionalleaders in a Matrix structure

+ Helped build UAV image analysis pipeline for research fields for automatically scoring the crops for diseasesand phenotyping

+ Using Satellite Imaging (Sentinel-2) for Crop Classification, and Pest Spread and Weather Suitability ConditionEstimation

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+ Bringing the “outside in” for accelerating the discovery pipeline by collaborating with both academic institutionsand start-ups

+ Conducted meet-ups and training on Artificial Intelligence within the organization+ Extended a Hackathon idea to fully developed project on IoT for precision agriculture by going from prototypeto a scalable product.

+ External Influence and Academic Collaboration: Chair and Moderator for CGIAR Big Data Convention on“Promise and Peril of AI”

+ With Confederation of Indian Industries (CII) mentored teams on Hackathon AgHack 2019+ Partnering with T-Hub and RICH, Hyderabad to mentor startups in the Indo-Australia Graft Challenge.+ Collaborating with IIT Madras and IIT Mumbai on developing new Machine Learning algorithms for SatelliteImagery

+ Partnering with private academic institutes for co-developing Machine Learning training’s for teams,+ Mentored seven research interns on Machine Learning.

2016-Present Adviser Research and Data Sciences, Brighter Minds, Bangalore, India.Research into Neuroscience and intuition

+ Adopting Neuroscience Research to enhance children’s education,+ Developing a framework for multimodal brain training for children less than 15 years,+ Electroencephalography (EEG) studies on pre- and post-training intervention group and comparison withcontrol group,

+ Design of Experiments (DoE) for mixed e�ect studies.

2014–2017 Data Analytic Scientist, Shell Technology Center Bangalore, India, Center for Computational Excel-lence (CCoE).Data Science across the value chain

+ Developing projects and innovation in the application of Machine Learning algorithms to solving problems inthe Oil and Gas Industry: Downstream to Upstream,

+ Helping building the team of Data Analytics and Machine Learning from ground-up,+ Collaborations with University of California Berkeley, Jawaharlal Nehru Center for Advanced Scientific Research(JNCASR) and Indian Institute of Science (IISc) for using Machine Learning for screening of new materials,

+ Developed a new approach in Machine Learning for understanding the governing mechanism of a system fromwhich the data is generated,

+ Collaborated with start-ups on virtual reality (VR) and demonstrated in 6 weeks,+ Mentored undergraduate interns from MIT on screening novel materials for catalysts (Zeolites and MOF),+ Integrated PlatformDevelopment for Data Analytics andMachine Learning on the Cloud forMaterials Discoveryalong with a Start-up,

+ Develop customized algorithms on Azure Machine Learning Studio platform in the Azure Cloud,+ Developed joint proposal for AI system for text mining research documents with University of California,Berkeley,

+ Multi-variate analysis of Process Plant data from first principles with subject-matter experts (SME) to modelcomplex behaviors and processes using Ensemble models,

+ These models can estimate and predict the yield, and also quantify deviations and evolution of output losses,+ Predicting the product specifications reliably for outputs from downstream units in the presence of variabilityand uncertainties in the input streams,

+ Abnormality Detection and Root-Cause Analysis on assets, in the absence of prior failure datasets, whileoperating in Downstream and Upstream units and predicting downtime days before failures,

+ Working with process engineers, computational chemists, materials scientists, and business to develop method-ologies for challenges in the energy sector from Natural Gas to Renewables,

+ Handling project specification uncertainties from stakeholders, and develop proof-of-concepts models with a

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goal to fast deployment: Discover to Demonstrate to Develop to Deploy.

2012–2013 Technical Manager, Samsung Advanced Institute of Technology (SAIT), Bangalore, India, Bio &Healthcare.Team Lead, Algorithm Group

+ Chronic cardiac server solutions: Identifying Arrhythmias from Electrocardiogram (ECG) Holters+ Mining vital patterns and abnormalities from the multivariate time series data obtained diabetic patients,+ Clinical Decision Support Systems (CDSS): Finding a minimal representation for physiological signals, obtainedfrom 24/48 hour Holters,

+ KPI is to generating patents and publications (two complete filings),+ Identifying new business areas and funding proposals in the healthcare domain.

2010–2012 Postdoctoral fellow and Contract Researcher, Quantitative Image Analysis Unit, Institute Pasteur,Paris, France.Microscope Modeling and Deconvolution

+ Determining field aberrations in 3-D images from Fluorescence MACROscopy (viz. Leica MacroFluo)+ Imaging fluorescent microspheres as specimen samples for studying vignetting+ Modeling the back focal plane for vignetting and making correspondence between the optical MACROscopeand generated model

+ Blind restoration of 3-D images a�ected by field vignetting and aberrations

2006–2009 PhD Student and Contract Researcher, Ariana Project-team, INRIA, Sophia-Antipolis, France.Breaking the Di�raction Limit

+ Optical Modeling of the 3-D imaging process in a fluorescence microscope,+ Back focal plane phase retrieval from observed fluorescent image and point sources,+ Reduced parametric modeling of optical aberrations (spherical aberrations due to Refractive Index mismatch),+ Blind restoration of specimen from 3-D images by using the Expectation Maximization algorithm and alterna-tively minimizing cost functions,

+ Mathematically modeling the illumination flatness of Zeiss Laser Scanning Microscope 510 microscope usingthe images obtained from fluorescent plastic strips and fluorescent slides. Post-acquisition correcting of thenonuniform illumination from the 3-D images,

+ Parameter estimation of the intensity loss in fluorescence images across the 3-D volume.

May–Dec ’06 Senior Research Engineer, Visual Computing Lab, Tata Elxsi, Bangalore.India

+ Automatic detection of pattern defects in Flex Tape Inspection system. The flex-tapes are inspected underreflective illumination conditions for possible pattern defects such as: Open, Short, Protrusions, Nick/Mouse bite,Island, and Pinhole. The detection is achieved automatically by a combination of referential and non-referentialtechniques,

+ Identification all pattern defect candidates, followed by classification and validation by the Design Rule Checking(DRC) method. This approach is aimed at reducing the number of false negatives (or under-kill) and improvingthe defect detection accuracy (above 90%). It aims to reduce the tuning of the algorithm to specific image profilesand reducing the number of false positives (or over-kill),

+ Estimating the velocity and acceleration from sampled displacement data using Radial Basis Function (RBF)interpolation.

2005–2006 Research Intern, Ariana Project-team, INRIA, Sophia-Antipolis, France.+ Evaluating the di�erent physical di�raction models and modeling the point-spread function (PSF) of themicroscope,

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+ Restoration of 3D Confocal Laser Scanning Microscope (CLSM) images using the Expectation Maximization(EM) algorithm,

2002–2004 Research Assistant, TEES, College Station, TX, USA.+ Identify incipient (failing) and existing fault conditions in Power System equipment by signal processing andpattern recognition,

+ Detection and localization of Power System disturbances in a distribution system based on Kalman Filtering,+ Analysis of high frequency statistical current to detect emerging or existing abnormality in Power System devicesby using an ARMA model,

+ Automatic detection of spikes in a time series data for event segmentation,+ Wavelet-based ground vehicle recognition using their acoustic signal as signatures,+ Automatic detection, localization and classification of Power Quality disturbances using Wavelets,+ Exporting automatically extracted features to MS Access, MS SQL and MySQL based ’Features Database’, withadded ability to create, write into or read from the database on stand-alone mode,

+ Testing possible configuration scenarios for synchronizing and updating acquired capture files in a SQL serverbased server-client network.

1999–2002 Undergrad. Research Assistant, DSP Lab, IIT Roorkee, India.+ Data Acquisition and Analysis for Condition Monitoring of Electrical Drives using NI DAQCard-AI-16E-4,+ Identification of bit errors in a data stream by the principle of noise segmentation technique and its removalusing an edge-sensitive modified median filter (MMF),

+ Instrumentation for wind tunnel studies on models of tall buildings, towers and chimneys.

May–July ’01 Summer intern, Pentamedia Graphics Ltd., Chennai, India.+ Evaluated algorithms for resolving rightful ownership through invisible digital Watermarking on streamingvideos,

+ Administrator for web and streaming video archive data server (numTV console).May–June ’00 Summer intern, IISc, Bangalore, India.

+ Study of di�erent image noise models,+ Evaluation of di�erent image enhancement and restoration techniques.

HONORS AND AWARDS+ Corteva Hackathon People’s Choice Award 2019.+ Research fellowship 2010–2012 from the French National Research Agency (ANR).+ Biography listed in Marquis Who’s Who in the World 2010–2013.+ Public poster award Young Researchers in Life Sciences symposium 2010.+ Nikon jury poster award in MifoBio conference 2010.+ Summa cum Laude for PhD Thesis 2009.+ Travel award IEEE International Symposium on Biomedical Imaging (ISBI), 2008.+ CORDI-s Fellowship from INRIA 2006–2009.+ ÉGIDE scholarship for international students 2005–2006.+ HCL Technologies Dataquest e-awards 2000.+ Recipient of IIT Roorkee merit scholarship.+ Best paper award TRYST, IIT, Delhi, India, Feb. 2001.+ Ranked 652 in the Roorkee Entrance Examination (REE)’98 among about 100, 000 students.

PATENTS+ ‘Method and Apparatus for Classifying Cardiac Arrhythmia,’ US Patent 20130085405, 2013.+ ‘Imaging system and method for diagnostic imaging,’ US Patent 20160015264A1, 2016.

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+ ‘A Hand-Held Based Imaging System for Diagnsotic Imaging,’ 3509/CHE/2014.

SELECTED PUBLICATIONS+ Thesis‘Blind deconvolution for three dimensional fluorescence microscopy’ Ph.D. Thesis, INRIA/ University of Nice SophiaAntipolis, France, Dec. 2009.

+ Book ChapterP. Pankajakshan, G. Engler, L. Blanc-Féraud, and J. Zerubia, ‘Deconvolution and denoising for confocal microscopy,’Modeling in Computational Biology and Biomedicine, Lecture notes in Mathematical and ComputationalBiology, Springer-Verlag, 2013.

+ JournalsP. Pankajakshan, P. Aravind and S. Sundar, ‘Spatio-Spectral Similarity Trade-O� for Hyperspectral Image Classification’,submitted to IEEE Transactions in Geoscience and Remote Sensing, December 2019.N. Kumar, P. Rajagopalan, P. Pankajakshan, A. Bhattacharyya, S. Sanyal and U. Waghmare, ‘Machine LearningConstrained with Dimensional Analysis and Scaling Laws: Simple, Transferable, and Interpretable Models of Materialsfrom Small Datasets, Chemistry of Materials, 31(2), pp. 314 − 321, 2018.U. Waghmare, P. Pankajakshan, S. Sanyal, O. E. de Noord, I. Bhattachatya, ‘Machine learning and statistical analysisfor materials science: Stability and transferability of fingerprint descriptors and chemical insights’, Abstracts of Papers ofthe American Chemical Society, 2018.P. Pankajakshan, S. Sanyal, O. E. de Noord, I. Bhattacharya, A. Bhattacharyya, ‘Machine learning and statisticalanalysis for materials science: stability and transferability of fingerprint descriptors and chemical insights’, Chemistry ofMaterials, 29(10), pp. 4190 − 4201, 2017.P. Pankajakshan, Z. Kam, A. Dieterlen, and J.-C. Olivo-Marin, ‘Characterizing the 3-D field distortions in lownumerical aperture fluorescence zooming microscope,’ Optics Express, vol. 20, pp. 9876–9889, 2012.P. Pankajakshan, Z. Kam, A. Dieterlen, and J.-C. Olivo-Marin, ‘Characterizing the 3-D field distortions in lownumerical aperture fluorescence zooming microscope,’ Optics Express, vol. 20, pp. 9876–9889, 2012.P. Pankajakshan, B. Zhang, L. Blanc-Féraud, J.-C. Olivo-Marin, and J. Zerubia, ‘Blind deconvolution for thin layeredconfocal imaging,’ Journal of Applied Optics, vol. 48, no. 21, Jul. 2009.P. Pankajakshan, ‘A unified approach for determining the underlying causes of non-stationary disturbances,’ InternationalJournal of Computer Applications in Technology, vol. 35, issue 2/3/4, pp. 241 − 261, June 2009.P. Pankajakshan, and V. Kumar, ‘Detail-preserving image information restoration guided by SVM based noise mapping,’Journal of Digital Signal Processing, vol. 17, no. 3, pp. 561 − 577, May 2007.

+ Peer-Reviewed ConferencesSonal Bakiwala, Praveen Pankajakshan, Harshit Lohani, Leela Prasad Donepudi, Ramesh Kaliyaperumal andMayank Yadav, “Spatio-temporal prediction of pest attack in India”, International Plant Protection Conference,Nov. 2019.P. Pankajakshan, R. V. Narayanan, ‘Recovering vital physiological signals from ambulatory devices,’ Proc. IASTEDConference on Biomedical Engineering, Acta Press, vol. 791, pp. 152–158, 2013.F. de Chaumont, S. Dallongeville, N. Chenouard, N. Hervé, S. Pop, T. Provoost, V. Meas-Yedid, P. Pankajakshan,T. Lecomte, Y. Le Montagner, T. Lagache, A. Dufour, J.-C. Olivo-Marin, ‘Icy: an open bioimage informatics platformfor extended reproducible research,’ Nature Methods, Jun. 2012, pp. 690–696.P. Pankajakshan, A. Dieterlen, G. Engler, Z. Kam, L. Blanc-Féraud, J. Zerubia, J.-C. Olivo-Marin, ‘Wavefrontsensing for aberration modeling in fluorescence MACROscopy,’ Proc. IEEE International Symposium on BiomedicalImaging (ISBI), pp. 905–908, Apr. 2011.E. Maalouf, P. Pankajakshan, B. Colicchio, A. Dieterlen, J.-C. Olivo-Marin, G. Engler, ‘Space variant deconvolutionapplied to 3D Fluorescence Micro & Macro-scopy,’ The Tenth International Conference on Correlation Optics,Chernivtsi, Ukraine, Sep. 2011.P. Pankajakshan, Z. Kam, A. Dieterlen, G. Engler, L. Blanc-Féraud, J. Zerubia, J.-C. Olivo-Marin, ‘Point-spreadfunction model for fluorescence MACROscopy imaging,’ Proc. Asilomar Conference on Signals, Systems and Comput-

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ers, pp. 1364–1368, Oct. 2010.P. Pankajakshan, and L. Blanc-Féraud, and Z. Kam, and J. Zerubia, ‘Point-spread function retrieval for fluourescencemicroscopy,’ Proc. IEEE International Symposium on Biomedical Imaging, Boston, USA, pp. 1095–1098, Jul.2009.P. Pankajakshan, and B. Zhang, and L. Blanc-Féraud, and Z. Kam, and J. C. Olivo-Marin, and J. Zerubia, ‘Blinddeconvolution for di�raction-limited fluorescence microscopy,’ Proc. IEEE International Symposium on BiomedicalImaging (ISBI), pp. 740 − 743, May 2008.P. Pankajakshan, and B. Zhang, and L. Blanc-Féraud, and Z. Kam, and J. C. Olivo-Marin, and J. Zerubia, ‘Para-metric Blind deconvolution for confocal laser scanning microscopy,’ Proc. IEEE International Conference of EMBS(EMBC-07), pp. 6531–6534, Aug. 2007.P. Pankajakshan, ‘Phasor estimation under nonstationary conditions,’ Proc. International Conference on AppliedMathematics (ICAM), Bandung, Indonesia, pp. 519, Aug. 2005.P. Pankajakshan, ‘KFAMP: An implementation scheme on phasor estimation for protective relays’ 7th Engineering andApplied Mathematics Conference (EMAC), Melbourne, Australia, Sept. 2005.

SELECTED TALKS+ ‘Towards Human-Centered AI’, IEEE TENCON/TENGARSS, Nov. 2019, Kochi, India.+ ‘IoT and Machine Learning: It takes two to tango’, Data Hack Summit Nov. 2018, Bengaluru.+ ‘Machine Learning and AI for the greater good’, Oct. 2018, PyCon India, Hyderabad.+ ‘Machine Learning for Material Science: Fingerprint descriptors and chemical insights’, Big-Data drivenMaterials Science,Lausanne, Sept. 2017.

+ ‘Characterizing the 3-D aberrations in large field fluorescence MACROscopy,’ Apr. 19, 2011, Focus on Microscopy,Constance, Germany.

+ ‘Point-spread function model for fluorescence MACROscopy imaging,’ Sept. 21, 2010, MIFOBIO, Seignosse, France.+ ‘Fluorescence microscopy with spherical aberration compensation,’ Jun. 25, 2010, 2nd Annual Colloqium ITS, Paris,France.

+ ‘Spherical aberation compensation for fluorescence microscoy,’ Apr. 27–29, 2010, Young Researchers in Life Sciences,Paris, France.

+ ‘Point-spread function retrieval for fluorescence microscopy,’ Oct. 23, 2009, 1st Annual Colloqium ITS, Paris, France.+ ‘On blind deconvolution and PSF retrieval,’ June 19, 2009, Quantitative Image Analysis Unit, Institut Pasteur, Paris.+ ‘On deconvolution and the hidden “phase” of an incoherent imaging system,’ Apr. 07, 2009, Cross Seminar, INRIA,Sophia Antipolis, France.

+ ‘Restoration of confocal laser scanning microscopic images,’ Jan. 14, 2009, CNES, Toulouse.+ ‘Myopic deconvolution for fluorescence microscopy,’ Dec. 18, 2008, LabEl, Lab. MIPS, Université de Haute-Alsace,Mulhouse.

+ ‘Blind deconvolution and 3D PSF modeling in biological microscopy,’ Nov. 17, 2008, high council for research, scientificand technological co-operation, status seminar program in medical imaging, Paris.

+ ‘Inverse problems in image processing,’ Aug. 06, 2008, Department of Mathematics, Indian Institute of Science(IISc) Math Initiative (IMI), Bangalore.

+ ‘Inverse problems in microscopy, Sept. 15, 2006, Department of Electrical Engineering, Indian Institute of Technol-ogy (IIT) Roorkee.

+ ‘Power signal RMS shape recognition for feeder device identification using grammatical inference technique,’ Mar. 30,2004, Student Research Week, Texas A&M University, College Station, TX, USA.

OUTREACH+ Mentoring undergraduate and graduate students.+ Indo-France and Inter university collaborative research.

ACTIVITIES AND AFFILIATIONS

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+ Reviewer: IEEE TMI, JOSAA, Elsevier DSP, SPIE Optics Express, Optic Letters, Electronics Letters, IET OpticalEngineering.

+ IEEE Senior Member.

REFERENCESReferences are available on request.

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