KALAI RAMEA
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Resume

SUMMARY

Accomplished applied AI scientist with over 5 years of post-PhD experience, 2+ years of managerial experience, and 4+ years of consulting experience. Adept in setting the strategy, vision, and leading a team of researchers. Proven track record of problem-solving, collaboration, conducting advanced research and developing innovative AI solutions. Committed to advancing the state-of-the-art in AI and making a positive impact through technology.

  • Leadership: 2+ years experience in technical leadership, people management (~10 research scientists), directing, strategy setting, hiring talent.
  • Deep learning: 5+ years experience. Computer vision (image and video analysis), NLP. Tools: Keras, Tensorflow, Pytorch, Spacy, NLTK, OpenCV.

  • Machine learning, Operations Research and Statistics: 8+ years experience. Linear and Non-linear Optimization, Classification and Regression analysis, Clustering, Analysis of Variance. Tools: R (caret), Python (scikit-learn, pandas, numpy, scipy).

  • Programming: 8+ years experience. Python (pandas, numpy, scipy, pytorch, tensorflow, Jupiter), R, SQL, GPU programming (CUDA), Git.

  • Spatial Analysis: 6+ years experience. ArcGIS, ArcPy, QGIS, GRASS, PostGIS, PostgreSQL, Leaflet.

  • Visualization: 7+ years experience. R (ggplot2, lattice, Shiny), Python (matplotlib), Keynote/Powerpoint, HTML, LaTeX.

  • Consulting: 4+ years experience. Worked with cross-functional teams and various stakeholders to deliver projects on time, prepared several proposals and deliverables.

  • Communication: Delivered many professional presentations at academic and non-academic conferences, published research articles and reports, and developed many project proposals.

EXPERIENCE

  • Research Area Manager (Machine Learning and Data Science), Palo Alto Research Center (Xerox PARC), Palo Alto, CA (2020 to Current)

    • Successfully led an advanced AI research project applied to Climate Science (funded by DARPA) from concept to completion.
    • Ideated and led a team to develop a Natural Language Processing inspired application for Scope 3 carbon accounting for enterprises.
    • Effectively managed budget, timeline, and resources, delivering high-quality results on time and within budget.
    • Secured funding from DARPA ($1M) and NASA ($500K) through comprehensive proposal writing that highlighted the project's impact and potential, demonstrating excellent strategic planning and fundraising skills.
    • Demonstrated strong leadership skills by inspiring and motivating team members, fostering a positive work environment, and ensuring project success.
    • Coordinated the efforts of team members from multiple countries and institutions, effectively communicating project goals and ensuring seamless collaboration.

  • Member of Research Staff (Data Scientist), Palo Alto Research Center (Xerox PARC), Palo Alto, CA (2017 to 2020)

    • Led the development of a conversational AI chatbot that helped unemployed individuals affected by COVID-19 find information on pandemic-related benefits. Won the Most Innovative Application award by PARC in 2020.
    • Demonstrated the ability to take an AI art project (Intricate Style Transfer) from ideation to deployment, delivering a high-quality solution that meets the client's expectations. Worked closely with the client to understand their requirements and deployed the algorithm on their cloud for scalable and efficient execution.
    • Developed and implemented a cutting-edge object detection algorithm for augmented and virtual reality assistance applications, utilizing Python, Tensorflow, OpenCV, and Unity.
    • Managed user studies to evaluate the effectiveness of a conversational AI copier for visually impaired individuals.
    • Offered data science consulting services for various applications, including user behavior analysis, spatial statistics, recommender systems, and big data analysis.

  • Post-doctoral Researcher, Institute of Transportation Studies, UC Davis, CA (2016 to 2017)

    • Designed and implemented a spatial consumer segmentation algorithm to categorize buyers of advanced vehicle technologies, utilizing R and QGIS.
    • Created a framework to integrate a comprehensive energy system model output with an air quality model, leveraging Bash and HDFS.
    • Developed a highly efficient least-cost optimization model for the US energy systems, utilizing GAMS and R, resulting in cost savings and improved system performance.

  • Research Fellow, International Institute for Applied Systems Analysis, Laxenburg, Austria (Summer 2013)

    • Conducted a comprehensive independent research project for 3 months, integrating vehicle consumer behavior into IIASA’s MESSAGE energy system model for the North American region with successful results.

  • Graduate Student Researcher, Institute of Transportation Studies, UC Davis, CA (2010 to 2016)

    • Pioneered a cutting-edge methodology to incorporate behavioral elements in long-term energy systems models, with a focus on the transportation sector.
    • Conducted in-depth analysis of various policy scenarios such as consumer rebates, infrastructure investments, and feebates to determine the optimal policy options to achieve climate target goals.
    • Contributed to an international collaboration with the research team at University College Cork, Ireland, to develop a modeling approach and analyze modal choices of people in Ireland and California.
    • Provided expertise in developing an energy systems model specifically to meet the AB 32 goals in California, delivering comprehensive policy pathway reports to the California Air Resources Board.

  • Engineering Consultant, Kimley-Horn and Associates, Inc., Oakland, CA (2007 to 2010)

    • Demonstrated experience leading a team on a challenging traffic signal design project.
    • Provided expert systems engineering technical support at Traffic Management Centers and crafted fiber optic communications design plans to meet project goals.
    • Built a deep knowledge base in wireless communications design, bringing it to bear in ITS applications.
    • Streamlined deployment planning and optimized ITS devices through hands-on experience with troubleshooting, programming, and calibration.
    • Produced comprehensive specifications and cost estimates for ITS design, ensuring project success.
    • Contributed to successful project outcomes through participation in meetings with clients, stakeholders, agencies, and design team members.
    • Utilized advanced GIS mapping skills to develop deployment plans for ITS devices.
    • Authored technical reports and proposals with clear and concise writing, demonstrating strong technical writing skills.
    • Gained extensive experience in data collection and field work on traffic design projects, demonstrating a commitment to thorough research and fieldwork.

  • Staff Engineer, Iteris, Inc., Anaheim, CA (2005 to 2007)

    • Extensive experience in deployment planning, troubleshooting, programming and calibrating the Intelligent Transportation Systems (ITS) devices, such as data communications systems, fiber optic equipment, routes/switches, traffic cameras, and traffic control equipment.
    • Worked in several Traffic Management Centers (TMCs) in Orange County, and helped set up communications network between ITS devices at the signal intersections to the TMC from scratch
    • Developed AutoCAD plans for the traffic signal intersection design
    • Developed GIS maps for ITS design projects

EDUCATION

  • Ph.D., University of California, Davis (2010 to 2016)

    • Degree: Transportation Technology and Policy
    • Focus: Operations Research, Energy Systems Modeling, Econometrics
    • Dissertation: Integration of Vehicle Consumer Choice in Energy Systems Models and its Implications for Climate Policy Analysis

  • M.S., University of Southern California (2003 to 2005) Degree: Civil Engineering

  • B.S., Anna University, Chennai, India (1999 to 2003) Degree: Civil Engineering

HONORS AND AWARDS

  • US Frontiers of Engineering Symposium, National Association of Engineers--one of the 100 young engineers around the nation selected to participate in the symposium (Sep 2019)
  • Early Stage Innovation Excellence Award for Augemented Reality Assistant Project, Palo Alto Research Center (Dec 2018)
  • Early Stage Innovation Excellence Award for Conversational Agent Design, Palo Alto Research Center (Dec 2017)
  • Helene M. Overly Memorial Graduate Scholarship, WTS Sacramento (Jan 2015)
  • UCTC Dissertation Fellowship, University of California Transportation Center (Dec 2014)
  • Young Scientists Summer Program, International Institute for Applied Systems Analysis (Jun 2013)
  • ITS Davis-Chevron Fellowship, (Feb 2011)
  • Sustainable Transportation Center Fellowship, ITS Davis (Sep 2010)
  • Outstanding Academic Achievement Award, University of Southern California (Aug 2005)
  • C.R. Narayana Rao Endowment, Endowment for having secured highest GPA in I to VI semester of B.E. Civil Engineering (Aug 2002)

PUBLICATIONS

  • Dipti Swapnil Hingmire, Hansi Alice Singh, Haruki Hirasawa, Phil Rasch, Linda Hedges, Brian Dobbins, Peetak Mitra, Subhashis Hazarika, Soo Kyung Kim, Kalai Ramea. Will correcting cloud radiative biases over the Southern Ocean improve precipitation biases over the Indian subcontinent in CESM2 simulations? (2022). AGU Fall Meeting.

  • Subhashis Hazarika, Kalai Ramea, Soo Kyung Kim, Peetak Mitra, Salva Ruhling Cachay, Haruki Hirasawa, Dipti Swapnil Hingmire, Hansi Alice Singh, Phil Rasch. Interactive Visual Analytics to Study the Impacts of Cloud Radiative Properties on Climate Patterns (2022). AGU Fall Meeting.

  • Hansi Alice Singh, Kalai Ramea, Dipti Hingmire. Machine Learning Methods may Reduce Uncertainty in Earth System Model Projections: A Case Study of Ocean Heat Uptake and AMOC Collapse (2022). AGU Fall Meeting.

  • Dipti Swapnil Hingmire, Haruki Hirasawa, Hansi Alice Singh, Salva Ruhling Cachay, Soo Kyung Kim, Peetak Mitra, Subhashis Hazarika, Kalai Ramea, Phil Rasch. AI assisted evaluation of ESMs in simulating observed cloud climate interactions (2022). AGU Fall Meeting.

  • Peetak Mitra, Salva Ruhling Cachay, Soo Kyung Kim, Subhashis Hazarika, Kalai Ramea, Dipti Swapnil Hingmire, Haruki Hirasawa, Phil Rasch, Hansi Alice Singh. ClimFormer: building an attention-based climate emulator (2022). AGU Fall Meeting.

  • Hansi Alice Singh, Haruki Hirasawa, Dipti Hingmire, Subhashis Hazarika, Soo Kyung Kim, Salva Ruhling Cachay, Peetak Mitra, Kalai Ramea, Phil Rasch. Marine Cloud Brightening Intervention Optimization using a Hybrid AI Approach (2022). AGU Fall Meeting.

  • Haruki Hirasawa, Dipti Hingmire, Hansi Alice Singh, Phil Rasch, Linda Hedges, Brian Dobbins, Peetak Mitra, Subhashis Hazarika, Soo Kyung Kim, Kalai Ramea. Marine Cloud Brightening Forcing and Climate Response in the Community Earth System Model 2 (2022). AGU Fall Meeting.

  • Peetak Mitra, Dipti Swapnil Hingmire, Haruki Hirasawa, Salva Ruhling Cachay, Subhashis Hazarika, Soo Kyung Kim, Phil Rasch, Hansi Alice Singh, Kalai Ramea. On incorporating first principles based physical conservation laws into global climate emulators (2022). AGU Fall Meeting.

  • Rohit Kameshwara Sampath Sai Vuppala, Peetak Mitra, Kalai Ramea. Patient-specific modeling of hemodynamic disorders using Physics Informed Neural Networks (2022). Bulletin of the American Physical Society.

  • Poorvesh Dongre, Denis Gračanin, Shiwali Mohan, Saman Mostafavi, Kalai Ramea. Modeling and simulating thermostat behaviors of office occupants: are values more important than comfort? (2022). Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation.

  • Soo Kyung Kim, Kalai Ramea. Retrieving Atmospheric Methane from Atmospheric Carbon Dioxide from GOSAT using Deep Neural Networks (2021). AGU Fall Meeting.

  • Kalai Ramea, Md Nurul Huda. Generating high-resolution nitrogen dioxide concentration map with multispectral, synthetic aperture radar and infrared remote sensing data using a geography-informed machine learning approach (2021). AGU Fall Meeting.

  • Kyle Dent, Kalai Ramea. Conversational User Interfaces for Blind Knowledge Workers: A Case Study (2020). Computing Research Repository arXiv.

  • Sarah J Doherty, Robert Wood, Kelly Wanser, Sean Garner, Philip J Rasch, Armand Neukermans, Thomas P Ackerman, Peter N Blossey, Matthew C Wyant, Kathryn Murphy, Elif Karatay, Kalai Ramea, Gary F Cooper, Jack D Foster, Lee K Galbraith, Robert Ormond, Sudhanshu Jain. The Marine Cloud Brightening Project: An atmospheric intervention research program (2019). AGU Fall Meeting.

  • Kalai Ramea. Unsupervised Temporal Clustering to Monitor the Performance of Alternative Fueling Infrastructure (2019). International Conference on Machine Learning.

  • Kalai Ramea. An Integrated Quantitative-Qualitative Study to Monitor the Utilization and Assess the Perception of Hydrogen Fueling Stations (2019). International Journal of Hydrogen Energy.

  • Jesse Vig, Kalai Ramea.Comparison of Transfer-Learning Approaches for Response Selection in Multi-Turn Conversations (2019). Association for the Advancement of Artificial Intelligence.

  • Shiwali Mohan, Kalai Ramea, Bob Price, Matthew Shreve, Hoda Eldardiry, Les Nelson. Building Jarvis - A Learner-Aware Conversational Trainer (2019). Workshop on User-Aware Conversational Agents In conjunction with ACM Intelligent User Interfaces 2019.

  • Christopher Yang, Saleh Zakerinia, Kalai Ramea, Marshall Miller. Development of Integrated Vehicle and Fuel Scenarios in a National Energy System Model for Low Carbon US Transportation Futures (2018). UC Davis Research Report.

  • Kalai Ramea, David S Bunch, Christopher Yang, Sonia Yeh, Joan M Ogden. Integration of behavioral effects from vehicle choice models into long-term energy systems optimization models (2018). Energy Economics.

  • David L McCollum, Charlie Wilson, Michela Bevione, Samuel Carrara, Oreane Y Edelenbosch, Johannes Emmerling, Céline Guivarch, Panagiotis Karkatsoulis, Ilkka Keppo, Volker Krey, Zhenhong Lin, Eoin Ó Broin, Leonidas Paroussos, Hazel Pettifor, Kalai Ramea, Keywan Riahi, Fuminori Sano, Baltazar Solano Rodriguez, Detlef P van Vuuren. Interaction of consumer preferences and climate policies in the global transition to low-carbon vehicles (2018). Nature Energy.

  • Eamonn Mulholland, Jacopo Tattini, Kalai Ramea, Christopher Yang, Brian P.Ó Gallachóir. The cost of electrifying private transport – Evidence from an empirical consumer choice model of Ireland and Denmark (2018). Transportation Research Part D: Transport and Environment.

  • Jacopo Tattini, Kalai Ramea, Maurizio Gargiulo, Christopher Yang, Eamonn Mulholland, Sonia Yeh, Kenneth Karlsson. Improving the representation of modal choice into bottom-up optimization energy system models–The MoCho-TIMES model (2018). Applied Energy.

  • Kalai Ramea. Creating Intricate Art with Neural Style Transfer (2017). Self-Organizing Conference on Machine Learning.

  • Jacopo Tattini, Kalai Ramea, Maurizio Gargiulo, Chris Yang, Eamonn Mulholland, Sonia Yeh, Kenneth Karlsson. Improving the representation of modal choice into bottom-up optimization energy system models (2017). wholeSEM Annual Conference 2017.

  • Chris Yang, Sonia Yeh, Kalai Ramea,Saleh Zakerinia, Alan Jenn, David S. Bunch. Modeling of greenhouse gas reductions options and policies for California to 2050: Analysis and model development using the CA-TIMES model (2016). UC Davis Research Report.

  • Kalai Ramea, Christopher Yang, Michael Nicholas. Modeling and analyzing near term transitions to alternative fueled vehicles using a spatial regional consumer choice and fueling infrastructure model (2016). EVS 2016 - 29th International Electric Vehicle Symposium.

  • Kalai Ramea, David S. Bunch, Sonia Yeh, Christopher Yang, Joan M. Ogden. Endogenizing Behavioral Effects and Infrastructure Investments in COCHIN-TIMES model (2016). International Energy Workshop.

  • David L. McCollum, Charlie Wilson, Hazel Pettifor, Kalai Ramea, Volker Krey, Keywan Riahi, Christoph Bertram, Zhenhong Lin, Oreane Y. Edelenbosch, Sei Fujisawa. Improving the behavioral realism of global integrated assessment models: An application to consumers’ vehicle choices (2016). Transportation Research Part D.

  • David Bunch, Kalai Ramea, Sonia Yeh, Chris Yang. Incorporating Behavioral Effects from Vehicle Choice Models into Bottom-Up Energy Sector Models (2015). UC Davis Research Report.

  • Kalai Ramea, David Bunch, Chris Yang, Sonia Yeh. COCHIN-TIMES: Consumer Choice Integration in TIMES and their Implications on Climate Policy Analysis (2015). International BE4 Workshop.

  • Chris Yang, Sonia Yeh, Saleh Zakerinia, Kalai Ramea, David McCollum. Achieving California's 80% greenhouse gas reduction target in 2050: Technology, policy and scenario analysis using CA-TIMES energy economic systems model (2015). Energy Policy.

  • Hannah Daly, Kalai Ramea, Alessandro Chiodi, Sonia Yeh, Maurizio Gargiulio, Brian O Gallachoir. Incorporating travel behaviour and travel time into TIMES energy system models (2014). Applied Energy.

  • Chris Yang, Sonia Yeh, Kalai Ramea, Saleh Zakerinia, David McCollum, David Bunch, Joan Ogden. Summary for Policymakers: Modeling Optimal Transition Pathways to a Low Carbon Economy in California (2014). UC Davis Research Report.

  • Kalai Ramea, David McCollum. Integrating Vehicle Consumer Choice into the MESSAGE Integrated Assessment Model: Implications for Energy Efficiency and Advanced Technology (2013). Integrated Assessment Modeling Consortium.

  • Hannah Daly, Kalai Ramea, Alessandro Chiodi, Sonia Yeh, Maurizio Gargiulo, Brian Ó Gallachóir. Modelling transport modal choice and its impacts on climate mitigation (2012). International Energy Workshop.

  • Kalai Ramea, Sonia Yeh, Christopher Yang, Joan M. Ogden. Energy-Economic-Environment Model for Policy Analysis in California: Elastic Demand & Sensitivity Analysis in MARKAL/TIMES (2011). International Energy Workshop.

IN THE PRESS