Machine Learning Data Scientist

Soroor Salavati

Austin, TX, US ad5s1d@r.postjobfree.com +1-737-***-****

Permanent Resident of the United States

PROFESSIONAL SUMMARY

Highly skilled and motivated programmer and data scientist with extensive experience in data mining, statistical analysis, machine learning, and artificial intelligence. Demonstrated experience of applying advanced analytical skills and technical expertise to automate processes, enhance operational efficiency, and solve complex problems. Eager to leverage my problem-solving abilities and technical skills in a challenging role to drive innovation and achieve operational excellence.

WORK EXPERIENCE

Independent Software Developer and Data Science Consultant for Upwork.com - United States (Apr 2024 - May 2024)

• Deployed a LAMP (Python) RESTful API.

• Deployed scalable web applications using AWS EC2.

• Created scripts using AWS CLI and SDK to automate system updates and deployments.

• Administered Amazon RDS and DynamoDB to enhance operations and security.

• Set up AWS security groups, IAM roles, and policies to ensure robust data protection.

• Advised client on the most effective and efficient use of AWS services. Shell-funded project at Inistitute of Computing, University of Campinas - S ao Paulo, Brazil Data Scientist - Graduate Research Assistant (Mar 2020 - Apr 2024)

• Developed software to automate rock classification processes to enhance operational efficiency and reducing manual workload.

• Applied advanced and state-of-the-art machine learning techniques to enhance data accuracy and utility.

• Developed models (e.g., Decision Trees, SVMs, CNNs, ViTs, GANs, Diffusers) to improve prediction accuracy.

• Used Python libraries like Scikit-learn, Numpy, TensorFlow and PyTorch to enhance data analysis efficiency. Computer Engineering Department — University of Applied Science - Ahvaz, Iran Data Analyst and Instructor (Sep 2012 - Sep 2019)

Head of Computer Engineering Department - Instructor (Sep 2015 - Sep 2019)

• Conducted data analysis projects to improve educational performance and efficiency.

• Managed the Computer Engineering Department, planned courses, and coordinated student activities.

• Taught a variety of computer engineering courses (e.g., Data structures, Algorithms Design, and Program- ming languages such as Python, Java, C++, and C#)

Chamran University - Ahvaz, Iran

Graduate Research Assistant (Sep 2011 - Mar 2013)

Undertook key projects:

• Efficient Neuro-Evolutionary Algorithm for Mobile Robot Navigation

– Implemented a multi-neural network approach, using three neural networks for robot navigation to enhance the performance of the learning procedure.

– Integrated fuzzy logic for obstacle avoidance to provide initial knowledge to the neuro-evolution algorithm and reducing the learning time and iterations needed to achieve optimal navigation.

• Internet Traffic Classification using Efficient Machine Learning Techniques

– Developed and implemented advanced machine learning models to accurately identify and categorize different types of internet traffic.

• City Facilities Locator Using Semantic Web Technologies

– Developed an ontology-based platform using Prot eg e to locate city facilities like hospitals and schools. 1

– Integrated real-world geographical and facility data for efficient and precise location-based queries.

– Implemented a user-friendly interface and back-end logic to process user inputs and return relevant results.

Azad University - Shushtar, Iran

Data Analyst and Instructor (Sep 2008 - Mar 2011)

• Developed a comprehensive SQL database to automate administrative tasks related to student courses and faculty management.

• Taught lab courses including Operating Systems Lab, Database Lab, and Programming Languages (C++, Java, C#).

Water and Electricity Organization - Ahvaz, Iran

Summer Internship (Jul 2007 - Sep 2007)

• Created an SQL database to modernize access to archival data.

• Supported IT infrastructure improvements for enhancing operational efficiency. CORE QUALIFICATIONS

Programming and Development:

• Proficient in Python, C, C++, C#, Java, MAT-

LAB, and T-SQL

• Experienced with PyTorch, TensorFlow, Mat-

plotlib, among others

Data Science and Analysis:

• Advanced skills in Machine Learning and Deep

Learning, Clustering, and Classification

• Expertise in Data Analytics, Statistical Model-

ing, and Quantitative Analysis

• Proficient in Natural Language Processing (NLP)

• Skilled in Data Visualization and Predictive

Analysis

Systems and Platforms:

• Knowledgeable in operating systems Windows

and Linux

• Database management and querying

Additional Technical Skills:

• Strong mathematical foundation

• Experienced in debugging and problem-solving

EDUCATION

PhD - Computer Science Sep 2024

University of Campinas (UNICAMP), Campinas, Brazil Dissertation: Image-based rock classification using machine learning techniques.

• Completed all research work and coursework, pending acceptance of a journal paper to proceed with dissertation defense.

• Engaged in advanced coursework including Machine Learning, Deep Learning, Image Analysis, Efficient Energy Computing, Graph Analysis, and Language Implementation.

• Undertook key projects:

– Tuning machine learning models to detect bots on Twitter.

– Conducting structural analysis of criminal networks and predicting hidden links using graph analysis.

– Automating car plate detection using image analysis techniques.

– Developing a facial recognition system based on Siamese networks.

– Enhancing model performance and accuracy in image-based rock classification. M.Sc. - Artificial Intelligence Sep 2013

Shahid Chamran University, Ahvaz, Iran

Thesis: Internet Traffic Classification using Efficient Machine Learning Techniques. Coursework: Machine Learning, Neural Networks, Pattern Recognition, Image Processing, Operating Systems, Robotics, Fuzzy Systems, Semantic Web.

Achievement: Ranked 2nd among graduates in the master’s program. B.Sc. - Software Engineering Sep 2008

Shahid Chamran University, Ahvaz, Iran

Capstone Project: Fingerprint Recognition Using Artificial Intelligence Algorithms. 2

SOFT SKILLS

• Team Collaboration: A dedicated team player who consistently meets deadlines and quickly adapts to new technologies.

• Adaptability and Learning: Highly motivated and capable of handling varied tasks and team environ- ments, with a strong eagerness to learn and master new technologies.

• Problem Solving: Strong problem-solving abilities, effectively tackling dynamic and challenging situa- tions with innovative solutions.

LANGUAGES

English, Persian, and Portuguese (Beginner)

PUBLICATIONS

Journal Papers

• Salavati, S., Mendes J unior, P. R., Rocha, A., Alexandre (2024). ”Adaptive Loss Optimization for En- hanced Learning Performance,” Ready for submission.

• Mendes J unior, P.R., Salavati, S., Cuadros Linares, O ., Gon calves, M.M., Zampieri, M.F., Ferreira, V.H.S., Castro Avila, M., Werneck, R.O., Moura, R., Morais, E., Lusquino Filho, L., Dav olio, A., Ferreira, A., Schiozer, D.J., Rocha, A. (2024). ”Rock-type classification: A (critical) machine-learning perspective,” Computers and Geosciences, Review Article, Section/Category: Image Analysis, under revision.

• Lusquino Filho, L.A.D., Werneck, R., Castro, M., Mendes Junior, P., Lustosa, A., Zampieri, M., Linares, O., Moura, R., Morais, E., Amaral, M., Salavati, S., Loomba, A., Esmin, A., Gon calves, M., Schiozer, D.J., Ferreira, A., Dav olio, A., Rocha, A. (2024). ”A multi-modal approach for mixed-frequency time series forecasting,” Neural Computing and Applications, under review.

• Fouladvand, S., Salavati, S., Masajedi, P., Ghanbarzadeh, A. (2015). ”A modified neuro-evolutionary algorithm for mobile robot navigation: Using fuzzy systems and combination of artificial neural networks,” International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 19, no. 2, pp. 125-133. DOI:10.3233/KES-150317

• Mirzaei-Paiaman, A., Salavati, S. (2013). ”A New Empirical Correlation for Sonic Simultaneous Flow of Oil and Gas Through Wellhead Chokes for Persian Oil Fields,” Energy Sources, Part A, 35 (9), pp. 817-825.

• Mirzaei-Paiaman, A., Salavati, S. (2012). ”Application of Artificial Neural Networks for Prediction of Oil Production Flow Rate,” Energy Sources, Part A, 34 (19), pp. 1834-1843. Conference Papers

• Vargas, A.R.S., Werneck, R.O., Gon calves, M.M., Pereira, E.S.P., Filho, L.A.D., Salavati, S., et al. (2022).

”Anomaly Detection in Production Data Using Machine Learning Techniques,” presented at the Rio Oil and Gas Conference, Brazil.

• Gon calves, M.M., Hossain, M., Vargas, A.S.S., Castro, M., J unior, P.R.M., Salavati, S., et al. (2022). ”Use of Production Data to Assess Correlation and Interwell Connectivity,” presented at the Rio Oil and Gas Conference, Brazil.

• Souza, S.M.P.C., Rezende, T.B., Nascimento, J., Chaves, L.G., Soto, D.H.P., Salavati, S. (2020). ”Tuning Machine Learning Models to Detect Bots on Twitter,” presented at the Workshop on Communication Networks and Power Systems (WCNPS).

• Salavati, S., Osareh, A., Shadgar, B. (2014). ”Internet Traffic Classification with Efficient Machine Learning Techniques,” presented at the 1st Conference on Computer Networks, Qom, Iran, February 2014.

• Salavati, S., Hajjarzadeh, S., Mazloom, M. (2009). ”An Optimized Method for Solving Zebra Puzzle,” presented at the 2nd International Conference on Computer and Electrical Engineering (ICCEE 2009), Dubai, UAE, December 2009. DOI:http://dx.doi.org/10.1109/ICCEE.2009.16 3

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