SOUMYASHREE SAHOO 

Soumyashree.sahoo@uconn.edu || (480) 435-2763 || linkedin.com/in/soumyashree-sahoo-2008626b ||

Website: https://soumyashree-sahoo1.webnode.page/ || GitHub: github.com/soumyashreesahoo2024

EDUCATION

August 2025 Ph.D. Computer Science & Engineering – UNIVERSITY OF CONNECTICUT, STORRS, CT

(expected) Focus: Machine Learning and Deep Learning for Depression monitoring | Advisor: Dr. Bing Wang

May 2011 M. Tech Computer Science & Engineering – BIJU PATNAIK UNIVERSITY OF TECHNOLOGY, ODISHA,

INDIA | Overall Percentage: 87.5/100%

May 2007 B. Tech Information Technology– BIJU PATNAIK UNIVERSITY OF TECHNOLOGY, ODISHA,

INDIA | Overall Percentage: 74.7/100%

AWARDS AND CERTIFICATES

- Conference Participation Award Fall 2024, University of Connecticut, Storrs, CT

- University of Connecticut, School of Computing, Predoctoral Reward (Outstanding Scholarly and Research

Accomplishments) Award 2024

- National Science Foundation Student Travel Award 2024

- iTeach Essentials requirements (BPOP & Badges) certificate of completion as defined by the Educational Technology

Council of the Connecticut Community Colleges

- Cigna Graduate Fellowship 2020-2021, University of Connecticut, Storrs, CT

RESEARCH INTEREST

My research primarily focuses on data science, IoT, ubiquitous computing, sensor analytics, and the application of machine

learning for depression prediction. I am particularly interested in leveraging data from sensors and connected devices to

develop predictive models that support mental health treatment

PUBLICATIONS

[1] Using Mobile Daily Mood and Anxiety Self-ratings to Predict Depression Symptom Improvement

Soumyashree Sahoo, Chinmaey Shende, Md Zakir Hossain, Parit Patel, Xinyu Wang, Md Ishtyaq Mahmud, Jinbo Bi,

Jayesh Kamath, Alexander Russell, Dongjin Song and Bing Wang. 2024 IEEE/ACM Conference on Connected Health:

Applications, Systems and Engineering Technologies (CHASE) .

[2] Predicting Symptom Improvement During Depression Treatment Using Sleep Sensory Data

Chinmaey Shende, Soumyashree Sahoo, Stephen Sam, Parit Patel, Reynaldo Morillo, Xinyu Wang, Shweta Ware, Jinbo

Bi, Jayesh Kamath, Alexander Russell, Dongjin Song, Bing Wang. Proceedings of the ACM on Interactive, Mobile, Wearable

and Ubiquitous Technologies 2023, Volume 7, Issue .

[3] Secure routing in wireless sensor networks

Soumyashree Sahoo, Pradipta Kumar Mishra, Rabi Narayan Satpathy. International Journal of Computer Science Issues

(IJCSI) 2012, Volume 9, Issue 1.

[4] C2: A Modern Approach to Disaster Management

Kumar Surjeet Chaudhury, Arpita Nibedita, Soumyashree Sahoo. International Journal of Computer Applications, Volume

51, Issue 6.

[5] Under Review: Vote with Your Feet: Predicting Depression Treatment Outcome Using Daily Step Count

Sensory Data

Md Zakir Hossain, Chinmaey Shende, Soumyashree Sahoo, Parit Patel, Reynaldo Morillo, Xinyu Wang, Jinbo Bi, Jayesh

Kamath, Alexander Russell, Dongjin Song and Bing Wang.

[6] Under Review: Cross-platform Prediction of Depression Treatment Outcome Using Location Sensory Data on

Smartphones

Soumyashree Sahoo, Chinmaey Shende, Md Zakir Hossain, Parit Patel, Yushuo Niu, Xinyu Wang, Shweta Ware, Jinbo

Bi, Jayesh Kamath, Alexander Russell, Dongjin Song, Qian Yang and Bing Wang.

[7] Under Review: Smartphone Data Gathered Early in Depression Treatment Predicts Treatment Outcome.

Anonymous.


WORKSHOPS AND INVITED TALKS

• Participated and presented "Cross-platform Prediction of Depression Treatment Outcome Using Location Sensory

Data on Smartphones" in Women in STEM Frontiers in Research Expo (WiSFiRE 2023) in University of

Connecticut, Storrs, CT.

• Presented "Using Mobile Daily Mood and Anxiety Self-ratings to Predict Depression Symptom Improvement"

at 2024 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies

(CHASE) in Wilmington, Delaware, USA.

TEACHING EXPERIENCE

January 2024 Teaching Assistant – UNIVERSITY OF CONNECTICUT, STORRS, CT

present CSE 2102: Software Engineering Spring 2024

  • Conduct office hours and assist students to solve the homework and programming assignments.
  • Design rubrics, grade the assignments and help to publish the result for class of 50 students.

CSE 1010: Introduction to Computing Fall 2024

  • Design tutorials and conduct lab sessions for better understanding of students.
  • Design automatic evaluation tests for the programming assignments for class 90 students.
  • Perform teaching assistant duties

Lecturer – UNIVERSITY OF CONNECTICUT, STORRS, CT

CSE 3000: Contemporary Issues in Computer Science and Engineering Spring 2025

  • Present lectures to students.
  • Read and evaluate assignment papers per student.
  • Grade exams and maintain student records.

August 2018 Instructor – CONNECTICUT STATE COMMUNITY COLLEGE THREE RIVERS, NORWICH, CT

January 2024

• Planned designed and revised syllabi curriculum instruction content and other materials as required,

helped develop DTS 203: Machine Learning course proposal during Spring 2021 semester.

• Completed biennial reviews of online courses, including C++, Database Development, Intro to

Programming, Java, and Software Applications, ensuring quality and relevance in the CT State

Community College system as part of maintaining high standards in online education and supporting

student success. This included leveraging Blackboard to deliver interactive and engaging online

learning experiences, incorporating tools such as discussion boards, quizzes, and grade management

for effective student monitoring.

• Proficiently used Blackboard for developing course content (lecture slides, recorded sessions and

assignments), conducting asynchronous and synchronous classes.

• Techie Camp Instructor (Summer 2023): Coordinated and implemented day-to-day activities for a

week-long STEM camp designed for elementary and middle school students organized at CT State

Three Rivers campus. Teach students to create interactive stories and games with TWINE, an open￾source tool that supports advanced customization with HTML, CSS, and JavaScript for more complex

projects.

• Successfully served administrative responsibility for degree and/or certificate programs, developed

new courses and course schedules, advised students on their academic career goals based on their

program of study.

• Subjects taught: CSC K108 (Python Programming), CSC K223 (JAVA Programming-I), CSC K233

(Database Development-I), CSA K105 (Intro Software Applications), CSC 233 (Advanced JAVA),

CSC K216 (Intermediate C++ Programming), CSC K241 (Data Structures & Algorithms), CST K145

(Digital Circuits & Logic), CSC 1271 (Web Development & Design-I), CSC K265 (Software

Engineering).


August 2019 Adjunct Faculty – EASTERN CONNECTICUT STATE UNIVERSITY, WILLIMANTIC, CT

May 2021

• Subjects taught: CSC110(Intro to Computing & Problem Solving), CSC210(JAVA Programming-I),

CSC 231(JAVA Programming-II), CSC 202(Machine Intelligence), CSC 305(Data Science).

July 2007 Assistant Professor – BIJU PATNAIK UNIVERSITY OF TECHNOLOGY, ODISHA, INDIA

November 2013

• Develop and implement effective teaching strategies that inculcate technology into lessons to make

them more interesting and useful.

• Developed a new lab (Computer Organization) and created lab manuals for students.

ACADEMIC PROJECTS

August 2020 Prediction of mental health

Research Assistant, CSE department, UConn, Storrs. Collaborating with Department of Psychiatry, UConn Health

• Enroll participants in the research study following IRB guidelines.

• Design and develop DepWatch system, that collects sensory data passively from smartphones and wristbands,

without any user interactions.

• Assist in developing and maintaining mobile applications (Android and iOS) for participant data collection

contributing to the release of a new iOS app version with added features.

• Perform exploration statistical analysis of time series sensory data related to location, mood, anxiety, and sleep,

along with data engineering to extract features.

• Design and implement machine learning algorithms to predict depression treatment outcomes using sensory data.

• Develop and maintain a web server and application to display patient details, survey responses, and sensory data

for use in patient treatment. Supported a web portal for doctors to track participants' treatment progress.

• Collaborate with fellow students to brainstorm and review ideas, while providing support to newly admitted PhD

students in the lab.

• Assist clinicians at UConn Health with data analysis and publications, ensuring clear communication regarding

patient data collection issues

Spring 2021 LSBNGNN – Location-Based Social Network Graph Neural Network

Student, CSE 5717 (Big Data Analytics) course project

• Designed and implemented a novel Graph Neural Network (GNN)-based model to predict user friendships and

locations in Location-Based Social Networks (LBSNs), integrating user mobility and social relationship data.

• Utilized hypergraph embeddings to capture complex interactions between users, locations, and activities,

leveraging LBSN2Vec and LBSN2Vec++ models to enhance prediction accuracy.

• Applied GNN-FiLM, a neural network-based technique, to modulate node embeddings and capture high-order

relationships in the LBSN hypergraph, outperforming traditional graph embedding methods.

Fall 2022 Amazon AWS Deep Racer (Autonomous racing with Reinforcement Learning)

Student, CSE 5820 (Advanced Machine Learning) course project

• Developed reinforcement learning models using policy optimization techniques to train autonomous driving

agents.

• Achieved 100% task completion on a simulated track by designing reward functions focused on balancing track

adherence and speed efficiency.

• Gained experience in reinforcement learning concepts, including reward shaping, policy optimization, and

environment simulation

TOOLS AND SKILLS

• Programming Languages: Python, Java, C, C++, SQL, MATLAB

• Web Development: Flask,JavaScript, HTML/CSS, PostgreSQL

• Data Analysis: Pandas, NumPy, Matplotlib, Seaborn


• Deep Learning: TensorFlow, Keras, PyTorch

• Data Collection and Tools: Experience with smartphone apps for data collection

• Document Preparation: LaTeX


© 2020 Mary Mitchell. 12 Pike St, New York, NY 10002
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