Neha Singh

adkblr@r.postjobfree.com +*(***) *** – **** Google Scholar Github MyWebsite LinkedIn PERSONAL STATEMENT

Ph.D. candidate working in the Artificial Intelligence research area. Experienced with structured/unstructured data analysis and apply a variety of state-of-the-art Deep Learning (DL) and Natural Language Processing (NLP) models to extract crucial insights in emergency management and assist emergency managers in rescue/aid operations. Skilled in Python, SQL, R programming languages and worked on various research project collaborations to present the analysis and insights in well-known conferences. Excellent communication and writing skills due to my teaching and research publication background along with various presentations, concept articulation and lecture delivery skills. EDUCATION

Doctor of Philosophy Information Systems Jan 2017-Dec 2021(Expected) University of Maryland, Baltimore County (UMBC), MD, USA Master of Technology Computer Science and Technology Jul 2012-Nov 2014 Jawaharlal Nehru University (JNU), New Delhi, India Bachelor of Technology Computer Science and Engineering. Jul 2007- June 2011 Hindustan College of Science and Technology, Uttar Pradesh, India. TECHNICAL SKILLS

• Programming/software skills: Python, R, MATLAB, Java, SQL, PL/SQL, WEKA, LATEX, C/C++

• Data Processing: Statistical Summary, Data Cleaning & Wrangling, Feature Extraction & Selection Frameworks/Libraries Used:

Data Visualization: GGplot, Matplotlib, Seaborn

Data Manipulation/operations: NumPy, Pandas, SciPy Natural Language Processing: Natural Language Toolkit (NLTK), genism, Spacy Machine Learning: TensorFlow, Keras, ScikitLearn

WORK AND RESEARCH EXPERIENCE

Summer ORISE Fellow FDA Jun 2020-August 2020

Achieved and presented meaningful information and associations towards drug usage and policy making using machine learning and statistical analysis methods with existing clinical trials data using R Graduate Assistant UMBC Jan 2017-Present

Instructor

Information Systems Logic and Structured Design, Class of ~27 students Restructure some course content, designed new quiz, Exams, HomeWorks, Grading, Student advising Teaching Assistant

Database Application Development, Class of ~80 students, Labs, Grading Introduction to Cybersecurity, Online Class of ~30 students, Grading Research Assistant

Published various research papers working with Machine & Deep Learning, Transfer Learning Models, Time Series & Forecasting Analysis, Natural Language Processing Methods while working on Cyber- Physical System for Flash Flood Monitoring and Detection Junior Research Fellow JNU, India. Jul 2012-Apr 2015 Researched on various topics under Nature Inspired Computing and Big Data to solve the problem of Distributed Database Query Optimization with published results RESEARCH PROJECTS

• Flash Flood Monitoring and Detection: Deployed Sensors and used WSN based predictive data analytics to forecast the severity of flash floods and classify relevant social media data using Transfer Learning models and Transformers. Machine Learning and NLP methods were used to detect and assess emergent flood situations in real environments and developed a holistic and scalable disaster management framework towards fusing multiple data sources to build a robust, reliable flood monitoring and detection system. We also collaborated with city partners to measure and compare the key performance improvements over existing municipal systems as part of the NSF Global City Team Challenge program. News feature UMBC NEW, NSF NEWS, MSN, YAHOO, EARTH.com, Baltimore local

• Assessing the Impact on House Valuation Based on Multi Modal Data Fusion: Housing Data (Zillow) fused with other socio-economic data such as regional income level and crime rate in order to assess the impact on house price using the multi-model data fusion method and evaluate its performance in predicting house price. Incorporating reliable and consistent external features related to zip code area could help the model to improve the prediction of home price. Total average Income in the respective zip code area has shown some relation with the price of homes located in the area.

• Exploiting the Deep Relationship between Music and Stress for Healthy Living: Reported stress level through physiological sensor data collected from wearable device. Machine Learning classification algorithms such as One-R, Naïve Bayes, KNN, Decision Tree, Random forest were applied to classify the stress or non- stress related data while performing stressful activities and listening to their favorite music. Results show that electrodermal activity (EDA) and heart rate (HR) data among other physiological sensors data are strong indicators for stress detection, and that random forest performed the best among all the classifiers. AWARDS

Nominated as “TOP GA” from my Department & served as a Panelist in GA orientation@UMBC Fall 2020. Awarded FDA CDER ORISE Fellowship for summer 2020. Technical Program Committee member for PERCOM Artifact Track in PERCOM (IEEE Pervasive Computing and Communication conference) 2020.

Received Graduate Student Professional Development grant for attending AAAI Fall symposium 2019, DC. Received IS departmental travel grant for IEEE SMARTCOMP 2019, AAAI Fall Symposium 2019, DC. Received National Science Foundation’s (NSF) travel award for attending IEEE SMARTCOMP 2018, Italy. VOLUNTEER ROLES

Internship at Esurgi Inc. to be familiar with Arduino programming and Annikken Andee hardware (Arduino shield for mobile control) for Healthcare app and sensor notifications. Aug 2016-Oct 2016 Information & Planning role at American Red Cross (ARC) for Disaster Service Cycle workforce engagement towards information dissemination, financial & statistical information and situation mapping during any emergency or preparation/recovery. Jan 2021- Present

PEER REVIEWED PUBLICATIONS

Bipendra Basnyat, Neha Singh, Nirmalya Roy, Aryya Gangopadhyay, Vision Powered Conversational AI for Easy Human Dialogue Systems, IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems

(MASS), IITR, NCR, India 2020.

Neha Singh, Bipendra Basnyat, Nirmalya Roy, Aryya Gangopadhyay, Flood Detection Framework Fusing The Physical Sensing & Social Sensing, 6th IEEE International Workshop on Sensors and Smart Cities, SmartComp, Italy, September 2020

Bipendra Basnyat, Neha Singh, Nirmalya Roy, Aryya Gangopadhyay, Design and Deployment of a Flash Flood Monitoring IoT: Challenges and Opportunities, 6th IEEE International Workshop on Sensors and Smart Cities, SmartComp, Italy, September 2020

Neha Singh, Nirmalya Roy, and Aryya Gangopadhyay. Localized Flood Detection with Minimal Labeled Social Media Data Using Transfer Learning, Association for the Advancement of Artificial Intelligence Fall Symposium, AI for Social Good, Arlington, Virginia, Nov 2019, arXiv preprint arXiv:2003.04973 (2020). Neha Singh, Nirmalya Roy, Aryya Gangopadhyay, Analyzing The Emotions of Crowd For Improving The Emergency Response Services, Pervasive and Mobile Computing, 2019, ISSN 1574-1192 Neha Singh, Nirmalya Roy, & Aryya Gangopadhyay (2018, June). Analyzing the Sentiment of Crowd for Improving the Emergency Response Services. In 2018 IEEE International Conference on Smart Computing

(SMARTCOMP) (pp. 1-8). IEEE Nominated for Best Paper Award in SMARTCOMP 2018 Neha Singh, "PhD Forum: Monitoring and Detecting Flood by Fusing the Sensor and Social Media Data Streams," 2018 IEEE International Conference on Smart Computing (SMARTCOMP), Taormina, Sicily, Italy, 2018, pp. 250-251. doi:10.1109/SMARTCOMP.2018.00065 Bipendra Basnyat, Amrita Anam, Neha Singh, Arrya Gangopadhyay, & Nirmalya Roy (2017, May). Analyzing Social Media Texts and Images to Assess the Impact of Flash Floods in Cities. In Smart Computing

(SMARTCOMP), 2017 IEEE International Conference on (pp. 1-6). IEEE. Neha Singh, Jay Prakash, & T. V. Kumar, (2016). Distributed Query Plan Generation Using Firefly Algorithm. International Journal of Organizational and Collective Intelligence (IJOCI), 6(1), 29-50. Jay Prakash, Neha Singh & T. V. Kumar (2017). Distributed Query Plan Generation using Bacterial Foraging Optimization. International Journal of Knowledge and Systems Science (IJKSS), 8(1), 1-26.

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