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ahmad humayun google deepmind welcome to ahmad humayun s webpage i work in the ai for health team at google deepmind the team develops multi modal techniques spanning radiology pathology genomics and transcriptomics our goal is to help clinicians make better decisions for their patients and to enable scientists discover promising medicine prior to this i led the neural networks vision group at vicarious we developed visual recognition algorithms for kitting packaging and bin picking robotic applications i completed my ph d in computer vision under jim rehg at the school of interactive computing georgia tech in 2018 my thesis explored recognition problems in videos where motion and sparse labeling can be used to build a life long object learning system before georgia tech i received my masters degree in cg vision imaging in late 2010 from ucl here i researched with gabriel brostow aka gabe on detecting regions of occlusion in consecutive video frames i also did a brief stint at the university of warwick with nasir rajpoot developing registration and dimensionality reduction techniques for cancerous tissue examined under toponome imaging system previously i was stationed at lums sse where i had the honor to work with sohaib khan in my 3 years stay i collaborated with biologists at lums sse and mrc nimr in developing tracking techniques for fluorescence microscopy with some interludes in systems research with umar saif résumé last updated september 2024 phd thesis detection and incremental object learning in videos phd dissertation school of interactive computing georgia tech april 2018 pdf bibtex ms thesis learning occlusion regions ms dissertation computer graphics vision and imaging university college london sept 2010 microsoft research project prize pdf bibtex publications google scholar ms academic new incremental object learning from contiguous views computer vision and pattern recognition cvpr june 2019 webpage data code talk paper bibtex iterative machine teaching international conference on machine learning icml august 2017 code demo talk slides pdf bibtex the middle child problem revisiting parametric min cut and seeds for object proposals ieee international conference on computer vision iccv dec 2015 webpage code pdf bibtex finding temporally consistent occlusion boundaries in videos using geometric context ieee winter conference on applications of computer vision wacv jan 2015 webpage dataset pdf bibtex rigor reusing inference in graph cuts for generating object regions ieee conference on computer vision and pattern recognition cvpr june 2014 webpage code pdf bibtex video segmentation by tracking many figure ground segments ieee conference on computer vision iccv dec 2013 webpage code dataset pdf bibtex learning a confidence measure for optical flow ieee pattern analysis and machine intelligence may 2013 webpage code pdf bibtex a novel paradigm for mining cell phenotypes in multi tag bioimages using a locality preserving nonlinear embedding international conference on neural information processing iconip nov 2012 preprint pdf bibtex ramtab robust alignment of multi tag bioimages plos one feb 2012 link bibtex this journal is ranked 1st by eigenfactor across all scientific proceedings a framework for molecular co expression pattern analysis in multi channel toponome fluorescence images microscopy image analysis with apps in biology miaab sept 2011 pdf bibtex towards protein network analysis using tis imaging and exploratory data analysis workshop on computational systems biology wcsb june 2011 preprint pdf bibtex learning to find occlusion regions ieee conference on computer vision and pattern recognition cvpr june 2011 webpage code pdf bibtex myosin motors drive long range alignment of actin filaments journal of biological chemistry feb 2010 link bibtex this journal is ranked 12th by eigenfactor across all scientific proceedings notes machine learning notes i took while preparing for my phd qualifying exam references from different books kevin murphy s ml simon prince s cv models tom mitchell ml and russell and norvig s ai topics probability generative and discriminative models glms exponential family directed undirected graphical models em gaussian processes variational inference reinforcement learning etc computer vision notes i took during simon prince s computer vision class at ucl topics single multi camera geometry overview of probability learning and inference single pixel inference mrfs mcmc and graph cuts linear algebra hand written notes while listening to gilbert strang s linear algebra lectures topics factorization subspaces projections orthogonal matrices deteriminants eigenvectors fft svd optimization notes i took while taking the numerical optimization course at ucl references from chong and zak s introduction to optimization topics basics of unconstrained multivariate and constrained optimization and regularization computer graphics notes i took during jan kautz cg class at ucl gv10 topics reflection illumination view cameras representations clipping rasterization texture mapping radiosity shadows culling computational photography notes i took during gabe brostow s computational photography and capture class at ucl topics cameras and aberrations compositing blending time lapse morphing hdr bilateral filter texture synthesis deblurring deconvolution intrinsic images image processing notes i took during gabe brostow simon prince s image processing class at ucl gv12 topics segmentation transformations morphological operators image filtering edge detection corner feature detection matching and flow past projects tracking actin filaments in vitro in fluorescence microscopy nimr lums sse automatic video recording of lectures lums sse mr iterative cycles in mapreduce lums sse email voice