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Alexander Rodríguez – Alexander Rodríguez Æ 540.394.1730 • Q [email protected] www.cc.gatech.edu/ acastillo41/ Education Ph.D. in Computer Science Jan. 2020–Present Georgia Institute of Technology Atlanta, GA Advisor: B. Aditya Prakash Ph.D. in Computer Science (Transferred) Aug. 2018–Dec. 2019 Virginia Tech Blacksburg, VA M.S. in Data Science Jun. 2016–May 2018 University of Oklahoma Norman, OK B.S. in Mechatronics Engineering Aug. 2009–Dec. 2014 National University of Engineering Lima, Peru Employment Graduate Research Assistant Jan. 2020–Present Georgia Institute of Technology Atlanta, GA Machine Learning Intern Summer 2019, 2020 Walmart Labs Sunnyvale, CA Graduate Research Assistant Aug. 2018–Dec. 2019 Virginia Tech Blacksburg, VA Graduate Research Assistant Jun. 2016–May 2018 University of Oklahoma Norman, OK Analytics Solutions Consultant Mar. 2016–May 2016 Entrepreneurial Finance Lab Lima, Peru Publications Pre-prints............................................................................................................................... Harshavardhan Kamarthi, Alexander Rodríguez, B. Aditya Prakash. Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future. arXiv:2106.04420 Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash. When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. arXiv:2106.03904 Refereed Conferences and Workshops..................................................................................... Alexander Rodríguez*, Nikhil Muralidhar*, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan, B. Aditya Prakash. Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19. AAAI Conference on Artificial Intelligence (AAAI-21). February 2021. Acceptance Rate: 21%. Alexander Rodríguez, Anika Tabassum, Jiaming Cui, Jiajia Xie, Javen Ho, Pulak Agarwal, Bijaya Adhikari, B. Aditya Prakash. DeepCOVID: An Operational DL-driven Framework for Explainable Real-time COVID-19 Forecasting. AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI-21). February 2021. Alexander Rodríguez, Bijaya Adhikari, Andrés González, Charles Nicholson, Anil Vullikanti, B. Aditya Prakash. Mapping Network States using Connectivity Queries. IEEE International Conference on Big Data 2020, Atlanta, GA. December 2020 (Long paper). Acceptance Rate: 15.5%. Alexander Rodríguez, Bijaya Adhikari, Andrés González, Charles Nicholson, Anil Vullikanti, B. Aditya Prakash. Using Connectivity Queries to Map Network States. NeurIPS Artificial Intelligence and Humanitarian and Disaster 1/4 Relief (AI + HADR) Workshop, Virtual Event. December 2020. Alexander Rodríguez*, Nikhil Muralidhar*, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan, B. Aditya Prakash. Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19. NeurIPS Machine Learning in Public Health (MLPH) Workshop, Virtual Event. December 2020. Sorour E Amiri, Bijaya Adhikari, John Wenskovitch, Alexander Rodríguez, Michelle Dowling, Christopher North, B. Aditya Prakash. NetReAct: Interactive Learning for Network Summarization. NeurIPS Human And Machine in-the-Loop Evaluation and Learning Strategies (HAMLETS) Workshop, Virtual Event. December 2020. Alexander Rodríguez, Bijaya Adhikari, Naren Ramakrishnan, B. Aditya Prakash. Incorporating Expert Guidance in Epidemic Forecasting. ACM SIGKDD Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK) Workshop, San Diego, CA. August 2020. Charles Nicholson and Alexander Rodríguez. A Hybrid Machine Learning Approach to the Stochastic Network Design Problem For Mitigation Strategies. 2018 INFORMS Annual Meeting, Phoenix, AZ. November 2018. Alexander Rodríguez and Charles Nicholson. A Data-based Paradigm for Mitigation Decision-Making in Critical Infrastructure. IISE Annual Conference & Expo 2018, Orlando, FL. May 2018. Amirhossein Khosrojerdi, Janet Allen, Farrokh Mistree, and Alexander Rodríguez. Sustainable Design of Plug-in Hybrid Electric Vehicle Charging Stations Considering Service Level. 2014 INFORMS Annual Meeting, San Francisco, CA. November 2014. Alexander Rodríguez, David Paredes, and Jaspers Huanay. Electric Load Forecasting by Geographic Area using Support Vector Machines. IEEE XX International Congress on Electronics, Electrical Engineering and Computing, Trujillo, Peru. August 2013. Ronald A. Cardenas and Alexander Rodríguez. Tracking and Path Planning of a Ground Vehicle with Ackerman Configuration. IEEE IXX International Congress on Electronics, Electrical Engineering and Computing, Lima, Peru, August 2012. Thesis..................................................................................................................................... Alexander Rodríguez. Data-based Stochastic Network Mitigation. M.S. Thesis, University of Oklahoma, 2018. Poster Presentations................................................................................................................ Alexander Rodríguez and Charles D. Nicholson. Data-based Paradigm for Mitigation Decision-Making in Critical Infrastructure. University of Oklahoma College of Engineering’s Advisory Board Meeting, Norman, OK, November 2017. Alexander Rodríguez and Casey Carlile. Developing a sustainable electric charging station for plug-in hybrid electric vehicles. University of Oklahoma Undergraduate Research Day, Norman, OK, March 2014. Talks AI/ML for Pandemic Response. PathCheck Global Health Innovators Talk Series, May 2021. Life During Grad School (Panel). ExploreCSR @ University of Rhode Island, April 2021. DeepOutbreak: A Deep Learning Framework for Improved Situational Awareness of the Spread of COVID-19 and Flu. COVID-19 Symptom Data Challenge Winners Showcase, December 2020. 5 Minutes of Fame: Student Researchers (Panel). Techsuyo 2020, October 2020. COVID-19 Forecasting with Deep Learning. CDC/MIDAS COVID Forecasting Meeting, August 2020. Honors and Awards 1st Place at the COVID-19 Symptom Data Challenge 2020 Out of 35 teams (10+ countries). Organized by Catalyst Health, Facebook and CMU. Awarded $50000. 2nd Place at the C3.ai COVID-19 Grand Challenge 2020 Among data science teams with 700+ participants from 40+ countries. Awarded $25000. 2/4 KDD Travel Award 2020 Richard Tapia Travel Award - IBM Scholar 2019 Broadening Participation in Data Mining Scholarship (BPDM) 2016 Workshop co-located with the KDD conference. Awarded $650. Honored by the Congress of Peru (Commission for Science and Technology) 2015 In recognition to winning an international academic competition. 1st Place at the ASME Old Guard Oral Presentation Competition 2014 International competition for Latin America. Awarded $500. Peru LNG Scholarship 2013 Awarded $13000 to study at The University of Oklahoma as an exchange student for one year. Dean’s list for Mechatronics Engineering at National University of Engineering 2013 President of the Artificial Intelligence Student Research Group GISCIA 2013 4th place at National University of Engineering Entrance Exam 2009 Best engineering school in Peru (< 10% acceptance rate). Research Experience Graduate Research Assistant Jan. 2020–Present School of Computational Science and Engineering @ Georgia Institute of Technology Atlanta, GA • Addressing a diverse set of challenges in advancing machine learning for epidemiology and public health. • Research presented at NeurIPS, AAAI, KDD, and BigData and received multiple awards in data science challenges. • Our ML model for epidemic forecasting was ranked top 5 in the COVID-19 Forecast Hub. Machine Learning Intern Jun.–Aug. 2019, Jun.–Aug. 2020 Walmart Labs (Team: Machine Learning Ranking) Sunnyvale, CA • Summer 2019: Constructed a customer interaction heterogeneous network for e-commerce applications. • Summer 2020: Developed an algorithm to generate weak relevance labels from product graphs. Graduate Research Assistant Jun. 2016–May 2018 Data Analytics Laboratory @ University of Oklahoma Norman, OK • Proposed a data-based approach to the stochastic network design problem in the context of disaster mitigation. Undergraduate Research Assistant Oct. 2014–Dec. 2014 National Institute of Research in Telecommunications Lima, Peru • Modeled stability of floating sensors placed to improve fish farming in Amazon lakes. Visiting Scholar Dec. 2013–June 2014 Systems Realization Laboratory @ University of Oklahoma Norman, OK • Developed a (statistical) surrogate model to replace a consumer behavior simulation in an optimization framework. Student Researcher 2011–2013 Artificial Intelligence & Control Systems Student Group Lima, Peru • Worked in several projects related to machine learning and control systems. Teaching Experience Virginia Tech: Teaching assistant on CS 5834 Urban Computing; CS 5757 Information Visualization; CS 2114 Data Structures. University of Oklahoma: Teaching assistant on DSA 5103 Intelligent Data Analytics. 3/4 Service Academic............................................................................................................................... Organizer and Program Committee Chair epiDAMIK Workshop @ KDD 2021 Public Relations and Technical Support PREVENT Workshop 2021 External Reviewer BigData 2020, WebConf 2018, DAMI 2018 2018 – 2021 Organizer (Fundraising Committee) BPDM Workshop @ KDD 2017, 2018 Established partnerships with large tech companies to fund participants. President Artificial Intelligence & Control Systems Student Group, Lima, Peru 2013 Organized workshops and talks introducing artificial intelligence
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