The Department

Recent technological advancements in Computer Science associated with the large scale of digitization is challenging the way people live. These changes create conveniences and ways of problem-solving that were never possible before. Artificial intelligence is one such are that has revolutionized the world and has stormed in to all walks of human life. It is everywhere is is influencing the day-to-day life. Artificial intelligence can now mimic human speech, translate languages, diagnose cancers, draft legal documents and play games with capabilities to beat human competitors. Today systems can accomplish tasks that were in the exclusive domain of human capabilities. The capabilities of non-human systems will continue to expand. Increasingly capable systems, computer systems being put into use everywhere, and  increasingly quantified society have been the driving forces in this information technology innovations.

Huge amounts of data generated every couple of hours is that this data can be  caught, captured and sorted,  those who own it and control it have an insight into human lived experience beyond anything that anyone in the past could ever have dreamed of like

  • What people think
  • What people care about
  • How people feel
  • Where do they go
  • What they buy
  • Who they speak to
  • What they say
  • How do people use data provided to them etc.

People leave a trail of these things which offers a window into the soul both individually and collectively that dwarfs anything that the philosophers or the kings or the priests of the past could have dreamed of.

These three trends are accelerating, and it seems highly unlikely that humans are going to be unchanged in the way people live together as a result of them. For the first in the history of human civilization, people are required to live alongside such powerful non-human systems. It was unimaginable that a day would dawn where people would be surrounded by technology that’s never switched off.

In order to address these developments, train and prepare students for handling these disruptive technologies in an efficient manner and apply for good cause of the society, ACE has introduced a four year course in AI & ML commencing from the academic year 2020. Within  a year of its introduction, the intake has been increased to 180.

The department has enviable infrastructural facilities to train the students.

Salient Features:

  • Regular academics of technical and technological skills blended to develop students as global professionals.
  • Faculty team comprises people with proven track record in their own domains of engineering education covering such diverse areas as Artificial Intelligence, Machine learning, Deep Learning, Full stack web development, and Data Analytics, in addition to the ever expanding core areas of Computer Networks, Operating Systems, Computer Organization, Database Management systems, Algorithms Design etc., well balanced by the programming skills of different paradigms that are essential for the Machine learning Engineers.
  • Highly proactive department in its responsibility for the Industry-Institution- Interaction by organizing expert lectures at regular intervals with the experienced and expert practitioners from the industry.
  • Center for Artificial Intelligence and Machine Learning with 14 GPU Processors for both academic & research work.
  • Mentoring for personality development, social skills like communication and behavioral skills, ethical skills like adherence to well-mannered conduct in a group.
  • Counselling sessions are additional but necessary skills are expected to help students evolve into engineers who are highly motivated with practical, creative, and management skills that would go a long way in scripting their careers as both employees as well as employers.
  • Plan Schedule and Conduct add-on courses and programs that are helpful for the student to pursue their career in a right path.
  • Having Institutional membership of Computer Society of India.

Vision:

To be an epicenter of excellence in education by offering cutting edge technologies, research and product based opportunities for the students and make them to succeed in global professional competitions with an attitude of core knowledge, entrepreneurial skills, ethical values and social concern.

Mission:

Imparting quality Technical Education to young Computer Engineer by providing them

M1: Impart quality technical Education with State of-the-art laboratories, Analytical and Core Technical Skills with International
standards by qualified and experienced faculty.

M2: Prepare for Global professional competitions, examinations for higher studies / Employment in product based companies.

M3: Develop professional attitude, Research aptitude, Critical Reasoning, Problem solving skills and technical consultancy by
providing training in cutting edge technologies.

M4: Endorse and Nurture knowledge, Life-long learning, Entrepreneurial practices, ethical values and social concern.

Program Educational Objectives(PEOs)

PEO 1: To prepare the students for successful careers in Computer Science and Engineering and fulfill the need by providing training to excel incompetitive examinations for higher education and employment.

PEO 2: To provide students a broad-based curriculum with a firm foundation in Computer Science and Engineering, Applied Mathematics & Sciences. To impart high quality technical skills for designing, modeling, analyzing and critical problem solving with global competence.

PEO 3:To inculcate professional, social, ethical, effective communication skills and entrepreneurial practice among their holistic growth.

PEO 4:To provide Computer Science and Engineering students with an academic environment and members associated with student related to professional bodies for multi-disciplinary approach and for lifelong learning.

PEO 5:To develop research aptitude among the students in order to carry out research in cutting-edge technologies, solve real world problems and provide technical consultancy services.

Program Outcomes (POs & PSOs)

PO1: An ability to apply knowledge of Mathematics, Science, and Engineering and knowledge of Fundamental Principles               .

PO2.: An ability to Identify, formulate and solve engineering problems.

PO3:  An ability to design a Model, component, or process to meet desired needs in Artificial Intelligence and Machine Learning within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability and sustainability, Design and Modeling.

PO4: An ability to design and conduct real time experiments, as well as to analyze and interpret data by doing Engineering Analysis.

PO5: An ability to use the techniques, skills and modern Computer Science and Engineering and Machine Learning tools necessary for system design with embedded engineering practice.

PO6: Apply reasoning informed by the contextual core knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
PO7:  The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context.

PO8: An understanding of global professional competency and ethical responsibility in building the models.

PO9: An ability to function on multidisciplinary teams.

PO10: An ability to communicate effectively with large spectrum of clients and stakeholders, who spread across globally.

PO11: Demonstrate the core knowledge and understanding of the engineering and management principles in showcasing of project work, which is carried out as a member or leader in a project team.

PO12: A recognition of the need for, and an ability to engage in life-long learning in the process of growing as a global professional.

Program Specific Outcomes (PSOs):

PSO1: To prepare the students ready for industry usage by providing required training in cutting edge technologies.

PSO2: An Ability to use the core concepts of computing and optimization techniques to develop more efficient and effective computing mechanisms.

Short term Goals:

  • To establish state of the art GPU cluster facilities in Center for Artificial Intelligence and Machine Learning.
  • Encourage Faculty to Publish Research papers in most reputed International Scopus, Web of science and UGC indexed Journals.
  • Introducing best practices to enhance teaching learning process.
  • To organize International Conferences/ Workshops in association with Springer, ACM and IEEE journals.

Long Term Goals:

  • To become self-sufficient through R&D and Consultancy getting funded Projects from UGC/DST/AICTE / MHRD
  • Recognition and Teaching excellence in the field of Artificial Intelligence and Machine Learning
  • To develop Research activities and organize Ph.D. programmes in the field of Artificial Intelligence and Machine Learning.

Objectives of Artificial Intelligence Lab:

From the day of Dr. Robert Hecht-Nielsen, who first invented neuro computing, a lot of research is on in the area of Artificial Intelligence and Machine Learning. The demand for engineers and scientists with knowledge in Machine Learning and Artificial Intelligence is high. Machine Learning Engineer, Robotic Scientist, Data Scientist, Research Scientist, Business Intelligence Developer are certain job roles for students who excel in this field.

ACE Engineering College is in the forefront to start a Center of Excellence (AI& ML Lab). The lab is being established in the month of November, 2019 with inputs from Academia, eminent personalities in Industry, experienced experts of the field to give required confidence for the students who are undergoing this course and make them able to cater to the needs of the market.

The laboratory activities aim towards:

  • Identify innovative research directions in Artificial Intelligence, Machine Learning and Big Data analytics.
  • Integrating and reasoning with information from disparate data sources.
  • Designing and implementing distributed systems for information exploitation, collaboration and decision making.
  • Data-intensive agent-based toolsProviding quality education and practical skills to the students and faculty.
  • Assist in the development of partnerships with Industry regarding Internships, Summer Jobs, Publications and students’ Placements.
  • Establish, refine and implement strategies to take the idea in to students and faculty fraternity.
  • Create sustainable funding models for societal and ACE related efforts.
  • Encouraging students to publish research articles, patents and starting their start-ups In the campus.

Achievements of Center of AI & ML:

  • The center has initiated with 5 NVIDIA 1060 GPUs with 60 Clients to cater the needs AI aspirants and stakeholders of Institute.
  • Right form the Inception Center has guided around 62 students in IV B.Tech and 35 in III B.Tech CSE & ECE students.
  • Center is collaborating with Leading India.ai an AICTE approved consortium in association with Bennett University in completion of a project titled” Windows malware Detection” using CNN techniques.
  • Four students Secured Internship in Applied AI Corporation Pvt. Ltd., Hyderabad and two of them absorbed by Applied AI.
  • 12 students have taken Machine Learning, a NPTEL course as a part of MOOCs supported by JNTUH in Lieu of the university open elective. All Successfully cleared with an average of 85%.

MOUs:

 

                                               

gs cse
Name   Dr.  G. Sreenivasulu
Designation Professor & HOD
Qualification M.Tech, Ph.D
Professional Exp. 13 Years
Research Interests Machine Learning
Registration Number 22150403-202837
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R.P.VENKATESWARA-RAO
Name   Dr. P. Venkateswara Rao
Designation Associate Professor
Qualification Ph.D(CSE)
Professional Exp. 13.6 Years
Research Interests Machine Learning
Registration Number 9572-210503-115008
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B.SREELATHA
Name   Mrs. B. Sreelatha
Designation Assistant Professor
Qualification M.TECH
Professional Exp. 3 Years
Research Interests Cyber Security
Registration Number 0934-170103-132946
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Faculty Contributions:

  • Dr.G.Sreenivasulu certified in Data Science for Engineers course, a NPTEL course as a part of MOOCs supported by AICTE and MHRD to guide the students in machine learning and AI related projects.
  • Dr.Ganti Krishna Sharma certified in Machine Learning a NPTEL course as a part of MOOCs supported by AICTE and MHRD to train the students
  • Mr.YounusShariff, Mr. Shashank Tiwari Certified in Joy of Computing Python a NPTEL course as a part of MOOCs supported by AICTE and MHRD to train the students in Python Programming.(Which is a backbone of AI & ML).
  • Ms.LakshmiRohita, Assistant professor of CSE attended a two week faculty Development Program on “Machine and Deep Learning” at VBIT, Hyderabad from 25th Nov to 07th Dec, 2019.
  • Majority of the faculty members across all the department working collectively in strengthening the center for AI & ML.
  • 3 faculty members ( Dr.G.Sreenivasulu , V.Maheswara Reddy and Mr.Shashank Tiwari) from CSE were certified in AI and Deep learning and also from NVIDIA Deep Learning Institute, USA.

Workshops and Faculty Development Programs:

  • Conducted One week faculty development program on “Machine and Deep Learning” organized in association with “Leading India.ai and Bennett University during Nov, 2018.
  • Conducting One week faculty development program on “Data Science” Sponsored by AICTE-New Delhi as a part of STTP.(16th to 22nd Dec, 2019).
  • Conducted one day workshop on “Artificial Intelligence” for III B.Tech CSE & ECE students, In association with TASK, Hyderabad.

Research Publications :

  1. G.Sreenivasulu, S.Viswanadha Raju et al.” A Threshold for clustering Concept – Drifting Categorical Data”, IEEE 3 rd International Conference on Machine Learning and Computing (ICMLC), Volume 3, pp. 383-387.( ISBN: 978-1-4244-9253/11/$26.00@2011 IEEE).
  2. G.Sreenivasulu, S.Viswanadha Raju et al.” Data Labeling Method Based On Rough Entropy For Categorical Data Clustering”, International Conference On Electronics, Communication And Computational Engineering – ICECCE 2014, pp. 383-387.(ISBN: 978-1-1170-1175/11/$31.00@2018 IEEE).
  3. G.Sreenivasulu, S.Viswanadha Raju et al. “A Review of clustering techniques ”, International Conference on Data Engineering and Communication Technology (ICDECT), Springer, March-J ISSN: 2250-3439).
  4. G.Sreenivasulu, S.Viswanadha Raju. “A Proficient approach for clustering of large categorical data cataloguing”, International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) March- 2016),IEEE, ISSN978-1-4673-9939-5/16/$31.00 .
  5. G.Sreenivasulu, S.Viswanadha Raju. et al. “Data Labeling method for genome DNA data based on Cluster similarity using Rough Entropy for Categorical Data Clustering”, International Journal of Engineering and Technology, June-2019. (Accepted).

Patents :

  1. Dr.G.Sreenivasulu et., filed a patent on “Design and Development of fault diagnosis by using Fuzzy neural networks for Hydroponic systems”. Application no: 201941048257 at Controller general of patents , Designs and Trademarks , Govt. of India.
  2. Dr.G.Sreenivasulu proposing a patent on ”Malaria Detection using Convolution Neural Networks” at Controller general of patents , Designs and Trademarks , Govt. of India. (Application number awaited)
  3. Dr.G.Sreenivasulu proposing a patent on ”An Efficient approach for clustering categorical data ” at Controller general of patents , Designs and Trademarks , Govt. of India. (Application number awaited)
  4. Dr.G.Sreenivasulu proposing a patent on ”Text summarization using Deep learning techniques ” at Controller general of patents , Designs and Trademarks , Govt. of India. (Drafting completed and about to file).