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AI-Driven Intervention System for Student Success [DICESUMMER 01_ALI]

Project Description Massive Open Online Courses (MOOCs) are a rapidly developing field that enables efficient and effective higher education. These courses not only allow students to study remotely from anywhere at any time but also facilitate the incorporation of new technologies to enhance the learning experience. However, these platforms often reduce human interaction, limiting the ability of educators to intervene when students face challenges that hamper their motivation or perseverance.

At Aalto University, the "Basic Course in C Programming" has been offered as an online course for several years. Thanks to the expertise and data accumulated over time, it is now possible to develop a prediction system to identify potential students who would benefit from early intervention.

We are looking for a summer assistant to develop a system that analyzes student performance and habits on the platform to detect those who need support. The system will categorize students for targeted interventions, such as:

• Email reminders about deadlines.
• Guidance on course organization.
• One-on-one meetings with course staff or the responsible teacher.

We are looking for summer job candidates who are strongly self-initiated and who can work independently.

Requirements

• Working language is English.
• Fluent in Python programming.
• Experience with ML methods and data science libraries (e.g., scikit-learn, pandas, NumPy).
• Ability to use Python tools to interact with remote servers and retrieve data via APIs.
• Experience deploying systems or Python applications on remote servers is a plus.

For more information, please contact University Lecturer Yusein Ali, yusein.ali@aalto.fi

Developing the content for course Speech Synthesis [DICESUMMER 02_BÄCKSTRÖM]

The old course “Speech Processing Project” will be replaced by “Speech Synthesis”. It is very similar in structure, just the use-case changes from speech coding to synthesis; it is a project course, where groups of 2-3 students choose datasets, implement a speech synthesiser, and evaluate the results. 

The purpose of this intern position is to create a baseline/reference implementation of speech synthesis: to help define the workload of the course, to define the evaluation framework, to create a baseline to which we can compare students’ implementations and to provide a backup solution, if something fails in the group projects.

Pre-requisites: 

• Experience with machine learning (mandatory)
• Experience with speech, audio or language processing is highly beneficial but not mandatory.

For more information, please contact Professor Tom Bäckström (tom.backstrom@aalto.fi) or Professor Lauri Juvela (lauri.juvela@aalto.fi)

Multimodal FIN-ENG lecture translation by LLMs [DICESUMMER 03_KURIMO]

We are looking for talented and hard-working students at Aalto University who have experience in speech and language processing and machine learning. All programming skills are also valuable. The topic and content of the work can be adjusted according to the candidate's interests and skills.  Please describe in your motivation letter why you are interested in joining the research group, what your relevant skills are and how your previous work or study history could support you in this project.

To provide Finnish language, terminology and education support for latest technology, we will experiment with multimodal lecture translation for our own speech recognition and natural language processing courses. Depending on the intern’s skills and ambition we will try to translate recorded speech, text and videos utilizing auxiliary text and speech material and the latest deep learning models and technology, such as LLMs.

The intern will have the opportunity to work in and be supervised by Aalto’s famous automatic speech recognition (ASR) research group that has top rankings in international competitions and is providing latest models and benchmarks for Finnish, Swedish, Sámi and other less commonly taught languages.

Relevant skills and courses: Finnish (fluent) and English, speech and sound processing, speech recognition, statistical natural language processing, machine learning, deep learning, deep generative learning.

For more information, please contact Professor Mikko Kurimo, mikko.kurimo@aalto.fi

Deep learning methods for automatic assessment of spoken language [DICESUMMER 04_KURIMO]

We are looking for talented and hard-working students at Aalto University who have experience in speech and language processing and machine learning. All programming skills are also valuable. The topic and content of the work can be adjusted according to the candidate's interests and skills.  Please describe in your motivation letter why you are interested in joining the research group, what your relevant skills are and how your previous work or study history could support you in this project.

To learn to speak a new language, one must both be frequently exposed to it, try to produce it and receive immediate and accurate feedback. Even today with all the available technology, the typical bottleneck in learning is the availability of feedback, since it requires frequent real-time communication with teachers or fluent speakers of the language. The lack is particularly severe in less commonly taught languages, such as Finnish, Swedish and Sámi. In AaltoASR research group we develop automatic speaking assessment (ASA) systems that utilize large speech and automatic speech recognition (ASR) models to provide a proficiency rating and feedback for pronunciation, fluency, vocabulary and grammar in various speaking tasks. In DALAI project funded by the Strategic Research Council of Finland we study the rating of automatically generated speaking tasks that adjust to the learner’s skills and success in previous tasks.  The intern will join the AaltoASR research group that has top rankings in international competitions and is providing latest models and benchmarks for Finnish, Swedish, Sámi and other less commonly taught languages, to take part in the development of automatic rating and ASR systems for Finnish language learners.

Relevant skills and courses (Finnish language skills are not required): speech recognition, statistical natural language processing, machine learning, deep learning, deep generative learning.

For more information, please contact Professor Mikko Kurimo, mikko.kurimo@aalto.fi 

Robust speech recognition for Sámi [DICESUMMER 05_KURIMO]

We are looking for talented and hard-working students at Aalto University who have experience in speech and language processing and machine learning. All programming skills are also valuable. The topic and content of the work can be adjusted according to the candidate's interests and skills.  Please describe in your motivation letter why you are interested in joining the research group, what your relevant skills are and how your previous work or study history could support you in this project.

Sámi languages are indigenous and endangered languages spoken in Finland and its neighboring countries in the arctic region. For revitalization and decolonization, one important task for speech and language technology is to develop tools to assist language learning. The number of speakers is small, so collecting and transcribing large amounts of speech data for training large models is not feasible. In SaameAI project funded by the Finnish Cultural Foundation, we study deep learning methods to develop speech models from limited data resources. The first application is an automatic speech recognition (ASR) based transcription system to generate parallel speech and text data from interviews, podcasts and other spoken material that exists. The intern will join the AaltoASR research group that has top rankings in international competitions and is providing latest models and benchmarks for Finnish, Swedish, Sámi and other less commonly taught languages, to take part in the development of a robust Sámi ASR system for conversational speech.

Relevant skills and courses (Finnish or Sámi language skills are not required): speech recognition, statistical natural language processing, machine learning, deep learning, deep generative learning.

For more information, please contact Professor Mikko Kurimo, mikko.kurimo@aalto.fi 

Creating exercises for the Signals and Systems course [DICESUMMER 06_NUMMI]

The summer trainee position offers an opportunity to develop and improve the Signals and Systems (ELEC-A7200) course, which is common to all Bachelor's students in electrical engineering. The task is to create new exercises and their automatic graders in collaboration with the teaching staff, as well as to supplement the course theory material and application examples together with the staff. The course exercises cover the fundamental principles and applications of signal and system analysis.

The task requires command of (at least most of) the aforementioned tools, some programming skills, good ideation skills, teamwork skills, an interest in developing education, and initiative. The position requires fluent skills in both Finnish and English. 

Previous experience in creating automatic graders for the A+ system is beneficial.

For more information, please contact University Lecturer Patrik Nummi, patrik.nummi@aalto.fi

Development of teaching materials for a new course on Cognitive Modeling [DICESUMMER 07_OULASVIRTA]

Want to learn how to apply computational methods to understand how human mind works? This is your chance!

Background: We are launching a new course entitled “ELEC-E7770 Computational Cognitive Modeling” for students interested in modeling how humans think and act. Students learn modern approaches including neural network -based cognitive models, reinforcement learning, and Bayesian cognition, with applications in human decision-making, perception, and action. Emphasis is placed on hands-on experience (e.g., Python notebooks) and real-world relevance: students will create and validate cognitive models using real behavioral dataset.

Work: This internship consists of development of notebooks for the course, in collaboration with the teacher Prof. Oulasvirta. The contents of the course center on key methods in computational cognitive models including, but not limited to: neural networks, language models, reinforcement learning, Bayesian decision theory, and statistical models.

Internship experience: The selected intern will join the Computational Behavior Lab together with our ASCI summer interns. All interns get a space in the modern Kide building at the group’s premises and are invited to group activities.

Requirements: This internship does not require close familiarity with all of the methods listed above; however, some familiarity with intelligent systems / AI / ML is a prerequisite. Experience with Python is a requirement. Interest in PhD studies is a plus.

For more information, please contact Professor Antti Oulasvirta, antti.oulasvirta@aalto.fi 

Developing Internet Traffic Measurement and Analysis Course [DICESUMMER 08_PEUHKURI]

Internet Traffic Measurement and Analysis course (ELEC-E7131) is one of courses where students are handed large, real-world size volumes of data (hundreds of gigabytes) to be work on. Based on the course feedback, there has been a steep learning curve to many if tools are not familiar to start with. You can help them to avoid BDS! (Big Data Shock).

The course format will change for the study year 2026 onwards and adapting the assignments for the upcoming change will need one to have very critical view on the existing assignments and how students are guided towards mastering big data analysis.

Ideally, the applicant has taken the course, has experience on big data analysis, knows his/her way around Linux and can write clear instructive texts. Most importantly one can think outside of existing box.

For more information, please contact Laboratory Manager Markus Peuhkuri, markus.peuhkuri@aalto.fi

Renewing the Laboratory Course in Networking and Cloud Technologies [DICESUMMER 09_PEUHKURI]

Student laboratory at DICE provides opportunities for students to have their hands dirty with real networking hardware. To get the best learning opportunities for our students, we both develop new tasks and improve existing ones. We would like you to have a good knowledge of networking technology (at least courses ELEC-E7310, ELEC-C7240 or equivalent knowledge). You should be able to work with real and virtual devices (routers, other network devices, Linux, FreeBSD, Windows) and produce good documentation. Previous experience of  laboratory courses ELEC-E7330/ELEC-E7331 and different cloud technologies are also valued highly.

Last academic year (2024-2025) Laboratory Course in Networking and Cloud Technologies was among the best 10 master courses at ELEC, welcome aboard to make the course even better! And more importantly, this is a great opportunity to show your skills and extend your knowledge in the area of networking!

For more information, please contact Laboratory Manager Markus Peuhkuri, markus.peuhkuri@aalto.fi

Developing exercises for the course FPGA for communication systems [DICESUMMER 10_RUTTIK]

In this summer work the aim is to design new laboratory exercises for the FPGA course. The exercises contain analog signal generation and reception with an FPGA and serial protocol testing. The exercises will be tested on Gatemate FPGA platform. We have developed an AD/DA teaching board that will be used in the exercises. Our intention is to use the ADALM open source software platform to generate serial protocol signals and test them with logic analyzer. The work includes developing the measurement system, testing the setup and writing measurement instructions together with the background information. We would like you to have good knowledge in Verilog programming (at least course ELEC-E7555). 

For more information, please contact Senior University Lecturer Kalle Ruttik, kalle.ruttik@aalto.fi 

Translating wireless communications and ubiquitous computing course materials to Finnish [DICESUMMER 11_SIGG]

The task is to translate the materials of the two courses ”Wireless Systems” and “Ubiquitous computing” from English to Finnish.

We require:

• good understanding of communication engineering and distributed computing
• the two courses passed
• knowledge of LateX
• good skills in Finnish

For more information, please contact Professor Stephan Sigg (stephan.sigg@aalto.fi), Professor Risto Wichman (risto.wichman@aalto.fi) or Project specialist Alexis Dowhuszko (alexis.dowhuszko@aalto.fi)

Translate wireless communications course materials to Finnish [DICESUMMER 12_TIRKKONEN]

The task is to translate the materials of the three courses ”Digital Wireless Communications”, “Signal Processing for Wireless Communications” and “Coding Methods” from English to Finnish.

We require:

• good understanding of physical layer communications
• at least 2 of the three courses passed
• knowledge of LateX
• good skills in Finnish 

For more information, please contact Professor Olav Tirkkonen (olav.tirkkonen@aalto.fi), Professor Risto Wichman (risto.wichman@aalto.fi) or Professor Patric Östergård (patric.ostergard@aalto.fi)