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<!DOCTYPE HTML>
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<title>The Team</title>
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<h2>The Team</h2>
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<a class="image" href="#openModalAnna"><img src="images/team/1_resized.png"><p class="imgDescription">About Anna</p></a>
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<h2>Anna Goldenberg</h2>
<p>Dr Goldenberg is a Senior Scientist in Genetics and Genome Biology program at SickKids Research Institute, recently
appointed as the first Varma Family Chair in Biomedical Informatics and Artificial Intelligence. She is also an Associate
Professor in the Department of Computer Science at the University of Toronto, faculty member and an Associate Research Director,
Health at Vector Institute and a fellow at the Canadian Institute for Advanced Research (CIFAR), Child and Brain Development
group. Dr Goldenberg trained in machine learning at Carnegie Mellon University, with a post-doctoral focus in computational
biology and medicine. The current focus of her lab is on developing machine learning methods that capture heterogeneity and
identify disease mechanisms in complex human diseases as well as developing risk prediction and early warning clinical systems.
Dr Goldenberg is a recipient of the Early Researcher Award from the Ministry of Research and Innovation and a Canada Research
Chair in Computational Medicine. She is strongly committed to creating responsible AI to benefit patients across a variety
of conditions.</p>
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<h7>Anna Goldenberg</h7>
<p1>Principal Investigator</p1>
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<h2>Alex</h2>
<p>Alex graduated with a Master's degree in computer science from U of T in 2019, and is currently pursuing a PhD. Alex is interested
in building machine learning models that have stable performance once deployed in the real world. The unanticipated influence of model
predictions on the outcomes of future samples, as well as the complex trust dynamics which occur between human users and ML models are
his primary focus. Alex believes that to safely harness the power of AI, one must be able to detect when predictions are no longer
reliable, and determine how to optimally update models on frequently shifting data streams.<br>
Awards: NSERC CGS-D<br>
<a href="http://proceedings.mlr.press/v126/adam20a.html">Hidden Risks of Machine Learning Applied to Healthcare</a><br>
<a href="https://arxiv.org/pdf/2106.01127.pdf">Towards Robust Classification Model by Counterfactual and Invariant Data Generation</a><br>
<a href="https://www.nature.com/articles/s41586-020-2766-y">Transparency and reproducibility in artificial intelligence</a><br>
LinkedIn: <a href="https://www.linkedin.com/in/alex-a-23ba02107/">https://www.linkedin.com/in/alex-a-23ba02107/</a><br>
Medium: <a href="https://georgealexadam.medium.com/">https://georgealexadam.medium.com/</a><br>
Website: <a href="http://alexadam.ca">http://alexadam.ca</a></p>
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<h7>Alex Adam</h7>
<p1>PhD Student</p1>
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<h2>Kingsley</h2>
<p>Chun-Hao (Kingsley) is a 5-th year PhD student in Computer Science at University of Toronto with Professor Anna Goldenberg.
His main research works include Interpretability, Robustness, and application to Healthcare. He has worked as intern in Google,
Ｍicrosoft and Facebook.<br>
Website: <a href="http://www.cs.toronto.edu/~kingsley/">http://www.cs.toronto.edu/~kingsley/</a></p>
</div>
</div>
<h7>Chun-Hao (Kingsley) Chang </h7>
<p1>PhD Student</p1>
</div>
</div>
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<h2>Lauren</h2>
<p>Lauren Erdman is the Project Manager for SickKids Hospital’s new Data Science team and a PhD student in Computer Science at University of
Toronto under the supervision of Anna Goldenberg. Previously she completed a MSc in Computer Science and a MSc in Biostatistics at
University of Toronto under the supervision of Anna Goldenberg and Lisa Strug, respectively. Her research is focused on developing and
applying machine learning methods primarily for data integration and improved translational discovery in the areas of population genetics,
genome biology, and complex disease.<br>
Google Scholar: <a href="https://scholar.google.com/citations?user=bSKEpp8AAAAJ&hl=en">https://scholar.google.com/citations?user=bSKEpp8AAAAJ&hl=en</a><br>
Website: <a href="https://sites.google.com/view/laurenerdman/home">https://sites.google.com/view/laurenerdman/home</a></p>
</div>
</div>
<h7>Lauren Erdman</h7>
<p1>PhD Student</p1>
</div>
</div>
<div class="3u">
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<h2>Abhishek</h2>
<p>Abhishek Moturu received his HBSc in 2019 from the University of Toronto (Trinity College) where he pursued a Mathematics major and a
Computer Science specialist. He received his MSc in Computer Science at the University of Toronto in 2021, working with Dr. Babak Taati
on automated pain detection for older adults with dementia at the UHN KITE Research Institute. At the Goldenberg Lab, he is working on
pediatric cancer surveillance in whole-body MRIs. During his PhD, his interests lie in developing theory and
applications for deep learning and federated learning in the healthcare setting. In his free time, Abhishek enjoys driving,
film, cooking, and tennis. He is currently also an Academic Don for Computer Science, Mathematics, and Physics at Trinity College.<br>
Awards: NSERC USRA ($6K), CIHR CGS-M ($17.5K), QEII-GSST ($15K)<br>
Google Scholar: <a href="https://scholar.google.ca/citations?user=pr333dYAAAAJ&hl=en">https://scholar.google.ca/citations?user=pr333dYAAAAJ&hl=en</a><br>
LinkedIn: <a href="https://www.linkedin.com/in/abhishek-moturu-116268b4/">https://www.linkedin.com/in/abhishek-moturu-116268b4/</a><br>
YouTube: <a href="https://www.youtube.com/channel/UCJ3AsjlIwbDhzteCpwGdEIg">https://www.youtube.com/channel/UCJ3AsjlIwbDhzteCpwGdEIg</a><br>
E-mail: <a href="mailto:moturuab@cs.toronto.edu">moturuab@cs.toronto.edu</a></p>
</div>
</div>
<h7>Abhishek Moturu</h7>
<p1>PhD Student</p1>
</div>
</div>
<div class="3u">
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<h2>Sujay</h2>
<p>Sujay is enrolled in the MD/PhD program at the University of Toronto and is pursuing his PhD in computer science under the supervision of
Drs. Anna Goldenberg and Sebastian Goodfellow. His research interests lie at the intersection of machine learning and medicine- specifically,
working with time-series data to learn about patient states from in-hospital as well as out-patient datasets.<br>
Awards: Ontario Graduate Scholarship 2021-2022 (15K), SickKids Restracomp PhD Scholarship (26K/year)<br>
Recent interests: wearable sensors<br>
Google Scholar: <a href="https://scholar.google.com/citations?user=8YrBnPsAAAAJ&hl=en">https://scholar.google.com/citations?user=8YrBnPsAAAAJ&hl=en</a><br>
Website: <a href="https://sujaynagaraj.github.io/">https://sujaynagaraj.github.io/</a>
</p>
</div>
</div>
<h7>Sujay Nagaraj</h7>
<p1>MD/PhD Student</p1>
</div>
</div>
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<h2>Daniel</h2>
<p>
Daniel Hidru is a Computer Science PhD student at the University of Toronto. He has previously completed a MSc in Computer Science and a BSc in Mathematics and Statistics at the same institution. His research focus is the development of models for drug response prediction. He has previously worked on the pharmacogenomic prediction of anti-TNF drug response in rheumatoid arthritis patients and is currently working on drug sensitivity prediction in cancer cell lines. He is more generally interested in the development of computational and statistical techniques to solve scientific problems, especially in the domains of biology and medicine.</p>
</div>
</div>
<h7>Daniel Hidru</h7>
<p1>PhD Student</p1>
</div>
</div> -->
<div class="3u">
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<h2>Bret</h2>
<p>Bret is interested in applying representation learning to timeseries data to improve the generalisability and safety of machine learning
algorithms in clinical practice. You can read more about his work <a href="http://www.cs.toronto.edu/~bretnestor/">here</a>.</p>
</div>
</div>
<h7>Bret Nestor</h7>
<p1>PhD Student</p1>
</div>
</div>
<div class="3u">
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<h2>Dustin</h2>
<p>Dustin is a PhD candidate with Dr. Anna Goldenberg and Dr. Michael Wilson. He develops bioinformatic tools to integrate and interpret
transcriptomic analysis. He then applies those tools with others to interrogate pubertal dynamics across puberty in different species.
In his spare time, he likes to play guitar and climb rocks.<br>
Awards: NSERC CGS-D<br>
<a href="https://academic.oup.com/nargab/article/3/1/lqab011/6148840">Single-cell mapper (scMappR): using scRNA-seq to infer the cell-type specificities of differentially expressed genes</a><br>
Google Scholar: <a href="https://scholar.google.com/citations?user=029JbjsAAAAJ&hl=en">https://scholar.google.com/citations?user=029JbjsAAAAJ&hl=en</a></p>
</div>
</div>
<h7>Dustin Sokolowski </h7>
<p1>PhD Student</p1>
</div>
</div>
<div class="3u">
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<h2>Valli</h2>
<p>Valli graduated with an Honours Bachelor of Science degree in Biomedical Science & Computer Science from Western University.
She is currently pursuing a PhD in Medical Biophysics at the University of Toronto to further her interests at the intersection of
healthcare and computer science. Her current projects involve explaining clinical heterogeneity of cancer predisposition syndromes
by analyzing complex genomics/epigenomics data and applying machine learning algorithms.<br>
Google Scholar: <a href="https://scholar.google.com/citations?user=029JbjsAAAAJ&hl=en">https://scholar.google.com/citations?user=029JbjsAAAAJ&hl=en</a></p>
</div>
</div>
<h7>Valli Subasri</h7>
<p1>PhD Student</p1>
</div>
</div>
<div class="3u">
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<h2>Sana</h2>
<p>Sana is a PhD student in the department of Computer science. Her research focus is on the challenges of modelling medical time
series, from unsupervised representation learning to explainability. She is currently an Apple scholar in AI/ML fellow and
was previously a CIHR health system impact fellow. In her free time, Sana enjoys baking, and playing basketball and tennis.<br>
Awards: <a href="https://cihr-irsc.gc.ca/e/51695.html">CIHR health system impact fellowship</a>, <a href="https://machinelearning.apple.com/updates/apple-scholars-aiml-2021">Apple scholars in AI/ML</a><br>
<a href="https://arxiv.org/abs/2106.00750">Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding</a><br>
<a href="https://arxiv.org/abs/2003.02821">What went wrong and when? Instance-wise feature importance for time-series black-box models</a><br>
<a href="https://arxiv.org/abs/1905.05134">What clinicians want: contextualizing explainable machine learning for clinical end use</a><br>
<a href="http://proceedings.mlr.press/v85/tonekaboni18a/tonekaboni18a.pdf">Prediction of cardiac arrest from physiological signals in the pediatric ICU</a><br>
Google Scholar: <a href="https://scholar.google.com/citations?user=OZDGXgwAAAAJ&hl=en">https://scholar.google.com/citations?user=OZDGXgwAAAAJ&hl=en</a><br>
LinkedIn: <a href="https://www.linkedin.com/in/sana-tonekaboni-650231b0/">https://www.linkedin.com/in/sana-tonekaboni-650231b0/</a><br>
Website: <a href="http://www.cs.toronto.edu/~stonekaboni/">http://www.cs.toronto.edu/~stonekaboni/</a></p>
</div>
</div>
<h7>Sana Tonekaboni</h7>
<p1>PhD Student</p1>
</div>
</div>
<!-- MSc's -->
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<h2>Kopal</h2>
<p>Kopal is a Masters student in Computer Science at the University of Toronto. She graduated
with a BASc in Biomedical Engineering, Co-op from the University of Waterloo. She spent the
last 2 years of her undergrad as a researcher at the Broad Institute developing computational
methods and interactive visualization tools for analysis of large-scale population genetics and
single-cell transcriptomics data. She is broadly interested in data science and machine learning
with applications across healthcare and medicine. Outside of the lab, Kopal enjoys digital art,
badminton, and baking.</p>
</div>
</div>
<h7>Kopal Garg</h7>
<p1>MSc Student</p1>
</div>
</div>
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<h2>Gabriela</h2>
<p>Gabi is an undergraduate student in bioinformatics and computational biology at the University of Toronto. She’s currently
doing her Advanced Special Project in Bioinformatics with Lauren Erdman. Her research interests include human-computer interaction,
data engineering, and robust data design. She wants to learn more about designing data systems that take into account its users’
end goals, applications in machine learning, and clinical data visualizations.<br>
Awards: <a href="https://www.artsci.utoronto.ca/news/talented-computer-science-students-driving-future-ai-thanks-deepmind-scholarships">DeepMind Scholarship</a><br>
Medium: <a href="https://morgensh.medium.com/">https://morgensh.medium.com/</a></p>
</div>
</div>
<h7>Gabriela Morgenshtern</h7>
<p1>MSc Student</p1>
</div>
</div>
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<h2>Soren</h2>
<p>Soren is currently working towards his MSc in Computer Science and his research interests revolve around the use of machine learning
to improve medical outcomes. In his spare time, he enjoys composing instrumental music and sharing it on his YouTube channel <a href="https://www.youtube.com/user/Revanchist1">Revanchist1</a>.</p>
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<h7>Soren Sarvestany</h7>
<p1>MSc Student</p1>
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<h2>Aslesha</h2>
<p>Aslesha is a Master's student in Applied Computing at the University of Toronto and a Vector Scholarship in
Artificial Intelligence Recipient 2021-22. She graduated with an Honours Bachelor of Science degree with majors
in Computer Science & Physics and a minor in Mathematics from the University of Toronto. Her research interests
include causality and machine learning and its application in healthcare. She is also broadly interested in
explainability and fairness in AI and likes watching movies and biking in her spare time.<br>
Awards: Vector Scholarship in Artificial Intelligence<br>
Linkedin: <a href="https://www.linkedin.com/in/aslesha-pokhrel/">https://www.linkedin.com/in/aslesha-pokhrel/</a></p>
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<h7>Aslesha Pokhrel</h7>
<p1>Graduate Researcher</p1>
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<h2>Parinita</h2>
<p>Parinita is an undergraduate student in computer science and statistics at the University of Toronto.
She's currently doing her 4th year research project in Computer Science with Lauren Erdman. She is
interested in the applications of machine learning in medicine. She aspires to pursue a degree in medicine;
she hopes to combine her background in computer science and her future training in medicine to improve
healthcare delivery and medical practice. In her free time, Parinita enjoys baking, swimming, and listening to podcasts.<br>
LinkedIn: <a href="https://www.linkedin.com/in/parinitae/">https://www.linkedin.com/in/parinitae/</a><br>
E-mail: <a href="mailto:parinita.edke@mail.utoronto.ca">parinita.edke@mail.utoronto.ca</a></p>
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<h7>Parinita Edke</h7>
<p1>Undergraduate Researcher</p1>
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<h2>Stanley</h2>
<p>Stan is an undergraduate, studying computer science and bioinformatics at the University of Toronto.
He is currently working with Lauren Erdman to improve prediction of obstructive hydronephrosis by integrating
the sequence of ultrasounds taken over recurring hospital visits. He is broadly interested in problems that
arise in data collection/preprocessing and modeling in a biomedical context. In his free time, he enjoys
playing video games and table tennis.<br>
Website: <a href="https://stanhua.rbind.io/">https://stanhua.rbind.io/</a><br>
LinkedIn: <a href="https://www.linkedin.com/in/stanley-z-hua/">https://www.linkedin.com/in/stanley-z-hua/</a><br>
E-mail: <a href="mailto:stanley.z.hua@gmail.com">stanley.z.hua@gmail.com</a></p>
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<h7>Stanley Hua</h7>
<p1>Undergraduate Researcher</p1>
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<h2>Xi</h2>
<p> Xi recently graduated with a BSc from the University of Toronto in Computer Science and Mathematics, focused in Computer Vision
and Artificial Intelligence. He has been working with Sana Tonekaboni on the deployment of machine learning models in the ICU,
as well as with Alistair Johnson on de-identifying medical records. He enjoys seeing AI in use in healthcare and wishes to contribute
to the community. He is an avid art and film enthusiast, and loves walking around the city to capture hidden aesthetics on camera.<br>
Awards: NSERC USRA<br>
Website: <a href="http://individual.utoronto.ca/xhuang/">http://individual.utoronto.ca/xhuang/</a><br>
LinkedIn: <a href="https://www.linkedin.com/in/xi-h/">https://www.linkedin.com/in/xi-h/</a></p>
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<h7>Xi Huang</h7>
<p1>Undergraduate Researcher</p1>
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<h2>Addison</h2>
<p>Addison grew up in Portland Maine, USA, and is an undergraduate researcher studying Computer Science
and Math at the University of Toronto. His current projects are in the area of representation learning
for medical time series data. He’s keen to explore the different ways modern deep learning methods can
be used to have profound impacts on patient lives. In his free time, Addison enjoys running, listening to
podcasts, and mentoring younger students.<br>
Website: <a href="https://addisonweatherhead.com">https://addisonweatherhead.com</a><br>
LinkedIn: <a href="https://www.linkedin.com/in/addison-weatherhead-293823b1/">https://www.linkedin.com/in/addison-weatherhead-293823b1/</a><br>
E-mail: <a href="mailto:addison.weatherhead@mail.utoronto.ca">addison.weatherhead@mail.utoronto.ca</a></p>
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<h7>Addison Weatherhead</h7>
<p1>Undergraduate Researcher</p1>
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<h2>Erik</h2>
<p> Erik grew up in British Columbia and obtained a BA and an MA in Economics from Simon Fraser University and Queen's, respectively.
After working as an Economist at the Bank of Canada for two years, Erik obtained an MSc in Statistics, taking courses in biostatistics
and bioinformatics, and then worked as a Bioinformatician at the Boutros Lab in the OICR and the Yeung Lab at SickKids. Erik's research
interests are focused on the intersection of statistics and machine learning and he is currently working as the first Machine Learning
Specialist at the Hospital. In his free time Erik enjoys reading, listening to podcasts, and playing tennis.</p>
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<h7>Erik Drysdale</h7>
<p1>Machine Learning Specialist</p1>
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<header class="major" style="padding-bottom: 1em;">
<h3>Past Lab Members</h3>
</header>
<div>
<ul>
<li type="square"> Erik Drysdale (Boston Consulting Group GAMMA) </li>
<li type="square"> Jaryd Hunter (UHN) </li>
<li type="square"> Sulagshan Raveendrakumar (Google)</li>
<li type="square"> Alex Chang (Medical student at the University of Montreal)</li>
<li type="square"> Vinith M. Suriyakumar (PhD MIT)</li>
<li type="square"> Melissa McCradden (Bioethicist at Sickkids)</li>
<li type="square"> Daniel Hidru</li>
<li type="square"> Julyan Keller-Baruch </li>
<li type="square">Farnush Farhadi (Layer 6)</li>
<li type="square">Carson McLean (Georgian partners)</li>
<li type="square">Ladislav Rampasek (Postdoc at MILA)</li>
<li type="square">Shalmali Joshi (Harvard)</li>
<li type="square">Angeline Yasodhara (Georgian partners)</li>
<li type="square">Jennifer Guo (University of Toronto)</li>
<li type="square">Aziz Mezlini (PhD, now PostDoc at Harvard Medical School/MassGen)</li>
<li type="square">Lebohang Radebe (Masters, now in South Africa)</li>
<li type="square">Walter Nelson (Undergrad, now McMaster Health System)</li>
<!-- <li type="square">Soren Sarvestany (Undergrad, now startup Waterloo)</li> -->
<li type="square">Hannah Li (Undergrad, now grad student at Stanford)</li>
<li type="square">Yasaman Mahdaviyeh (Undergrad, PhD University of Toronto)</li>
<li type="square"> Shems Saleh (Masters, now Vector)</li>
<li type="square"> Daniel Cole (Undergrad, now Shopify)</li>
<li type="square"> Won June (Undergrad, now Shopify)</li>
<li type="square"> Tal Friedman (Undergrad, now PhD candidate at UCLA).</li>
<li type="square"> Ekansh Sharma (Undergrad, PhD at University of Toronto).</li>
<li type="square">Hareem Naveed (Masters, now at Data Science for Social Good).</li>
<li type="square">Cheng Zhao (Masters, now at Google)</li>
<li type="square">Bo Wang (Illumina)</li>
<li type="square">Feyyaz Saigin Demir (Masters, now at Google)</li>
<li type="square">Ying Li (bioinformatician)</li>
<li type="square">Beyrem Khalfaoui (Now PhD student with JP Vert)</li>
<li type="square">Anne Keller (Masters, now Masters in epidemiology)</li>
<li type="square">Mohsen Hajiloo (Amazon)</li>
</ul>
</div>
</div>
<div class="6u">
<header class="major" style="padding-bottom: 1em;">
<h3>Past Visitors</h3>
</header>
<div>
<ul>
<li type="square">Vanessa Lima (Brazil)</li>
<li type="square">Xin Wang (China)</li>
<li type="square">Seunghak Lee (CMU)</li>
<li type="square">Lloyd Elliot (Oxford Stats)</li>
</ul>
</div>
</div>
</div>
<h2>Our global lab!</h2>
</section>
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var marker = L.marker([32.427908, 53.688046], {icon: pinIcon}).bindPopup('Sana Tonekaboni, Farnush Farhadi, Soren Sabet Sarvestany').addTo(map); // Iran
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var marker = L.marker([33.312806, 44.361488], {icon: pinIcon}).bindPopup('Shems Saleh').addTo(map); // Baghdad, Iraq
var marker = L.marker([17.6868, 83.2185], {icon: pinIcon}).bindPopup('Abhishek Moturu').addTo(map); // Visakhapatnam, India
var marker = L.marker([32.0853, 34.7818], {icon: pinIcon}).bindPopup('Gabriela Morgenshtern').addTo(map); // Tel Aviv, Israel
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var marker = L.marker([36.806495, 10.181532], {icon: pinIcon}).bindPopup('Aziz Mezlini').addTo(map); // Tunis, Tunisia
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